Healthcare monitoring at your fingertips: validation of a smartphone alternative to routine measures of skin sensibility

Healthcare monitoring at your fingertips: validation of a smartphone alternative to routine measures of skin sensibility | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Healthcare monitoring at your fingertips: validation of a smartphone alternative to routine measures of skin sensibility Owen Lindsay, Hanan Hammad, James Baysic, Abbey Young, Nasir Osman, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3694234/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Aug, 2024 Read the published version in Scientific Reports → Version 1 posted 14 You are reading this latest preprint version Abstract The capacity to perceive tactile input at the fingertips, referred to as tactile sensibility, is known to diminish with age due to regressive changes to mechanoreceptor density and morphology. Sensibility is measured as perceptual responses to stimuli of varying intensity. Contrary to traditional sensibility monitoring instruments, smartphones are uniquely suited for remote assessment and have shown to deliver highly calibrated stimuli along a broad spectrum of intensity, which may improve test reliability. The aim of this study was to evaluate a vibration-emitting smartphone application, the Vibratus App, as a mode of estimating tactile sensory thresholds in the aging adult. The peripheral nerve function of 40 neurologically healthy volunteers (ages 18–71) was measured using monofilaments, a 128-Hz tuning fork, the Vibratus App, and nerve conduction studies (NCS). Between group differences were analyzed to determine each measurement’s sensitivity to age. Spearman correlation coefficients depicted the associative strength between hand-held measurements and sensory nerve action potential (SNAP) amplitude. Inter-rater reliability of traditional instruments and the software-operated smartphone were assessed by intraclass correlation coefficient (ICC 2, k ). Measurements taken with Vibratus App were sensitive to the age-related decline in tactile sensitivity (t(30.643) = -3.480, p = .002). The inter-rater reliability of smartphone and tuning fork testing was moderate (ICC 2,k = 0.57 and 0.51, respectively), whereas monofilament testing was good (ICC 2,k = 0.83). The findings of this study support further investigation of smartphones as remote tactile sensitivity monitoring devices. Biological sciences/Neuroscience/Somatosensory system/Touch receptors Biological sciences/Neuroscience/Neural ageing smartphone vibrotactile nerve conduction aging psychophysics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Skin sensibility plays an important role in navigating the external environment and executing goal-directed actions. The fluidity and precision with which dexterous motor tasks are executed is functionally limited by the hand’s capacity to discern the frequency and intensity of various tactile stimuli (Dellon and Kallman 1983 ; King 1997 ; Ebied et al. 2004 ; Melchior et al. 2007 ). It is postulated that age-related changes affecting mechanoreceptors of the hand are the primary cause of diminished tactile sensibility in the elderly (Cauna and Mannan 1958 ; Daly and Odland 1979 ; Gescheider et al. 2002 ; Tremblay et al. 2003 ; Bowden and McNulty 2013 ; Ennis et al. 2016 ; García-Piqueras et al. 2019 ). Additionally, other contributing factors, such as skin dehydration and altered elasticity, have also been identified as secondary limitations to cutaneous sensation with advanced age (Daly and Odland 1979 ; Potts et al. 1984 ). Manipulation of the hand is controlled by sensory feedback from low-threshold cutaneous receptors, known as Meissner’s and Pacinian corpuscles, Ruffini endings, and Merkel cells (Johansson and Vallbo 1979b ). These receptors and their afferents densely innervate the fingertips (Johansson and Vallbo 1979b ), allowing us to functionally integrate tactile feedback during tasks requiring precision (Kelly et al. 2005 ; Corniani and Saal 2020 ). Histological studies (Cauna and Mannan 1958 ; Garcia-Piqueras et al. 2019 ) have identified a reduction to Pacinian and Meissner’s Corpuscle density with age, as well as morphological changes. These regressive changes to the physical form and number of afferents disrupts the mechanisms driving cutaneous feedback, which has been associated with clumsy and slowed dexterity (Ebied et al. 2004 ; MacKinnon 2018 ). Due to the heterogeneity of age-related sensory loss among healthy adults, there is mixed evidence regarding which mechanoreceptors are reduced in number and at what rate they are lost (Cauna and Mannan 1958 ; Garcia-Piqueras et al. 2019 ); However, a general consensus has been reached that those over 55 years of age become considerably higher risk of developing abnormal upper-limb sensory and motor function with time (Kenshalo 1986 ; Tong et al. 2004 ; Bowden and McNulty 2013 ). Since the onset and progression of symptoms relating to age-related sensory loss vary significantly among older adults, treatment strategies based on frequent and precise sensibility testing may benefit the elderly. One way of monitoring symptom progression with high frequency is to utilize methods that can be operated remotely. Contrary to traditional approaches to sensibility testing, such as Semmes-Weinstein monofilament (SWMF) testing and 128-Hz tuning fork (TF) testing, smartphones are ubiquitous and employ software-operated procedure, suggesting they are possibly a useful tool for developing targeted interventions, and by extension, may address the need for accurate and remote healthcare. Given the potential of smartphones as an at-home alternative to traditional approaches of sensibility monitoring, there is a need to establish the validity and reliability of smartphone-based testing by comparing it to criterion- and reference-standard approaches. Nerve conduction studies (NCS), an electrodiagnostic evaluation of evoked sensory or motor compound action potentials, is widely regarded to be the criterion standard with which other test modalities are validated against. Specifically, sensory nerve action potential (SNAP) amplitude is a metric derived from NCS identified as a highly sensitive marker of age, owing to a reduction to the number of nerve fibers over the lifespan (Tong et al. 2004 ; Preston and Shapiro 2013 ; García-Piqueras et al. 2019 ). Conversely, manual instruments evoke perceptual responses that reflect mechanical properties of the skin, such as elasticity and hydration, as well as altered mechanoreceptor density and morphology. As an initial step toward achieving remote sensibility monitoring, the theoretical utility of smartphones must be demonstrated in applied contexts, with reference to criterion-standard and manual approaches for comparison. Purpose Smartphones are poised to relay frequent and accurate information about a patient’s functional sensibility to healthcare providers, which may promote informed decision-making when strategizing treatment options, leading to improved outcomes and quality of life. Additionally, remote sensibility monitoring enabled by smartphone technology may increase access to care for elderly adults who have difficulty visiting the clinic. The aim of this study was to (1) evaluate the Vibratus App (VA) as a mode of estimating tactile sensitivity across ages, drawing on the performance of traditional instruments and NCS for comparison, and (2) compare the inter-rater reliability of estimates of tactile sensibility using human- versus software-standardized testing procedures. There may be a benefit to measuring sensibility using an approach that minimally involves practitioners, as it mitigates the influence of human error on the outcome of examination. Therefore, we hypothesize that measurements taken with VA will demonstrate an associative strength to NCS that exceeds SWMF and TF testing. Similarly, we hypothesize that VA will detect higher (poorer) perceptual thresholds among older adults compared to young adults, indicating regressive age-related changes to sensibility. We also hypothesize that VA will demonstrate a higher level of reliability in comparison to the manual instruments. Material and methods Participants A sample of 47 adults were recruited using convenience sampling from May 2021 to April 2022. For inclusion in the research study, participants had to be between the ages of 18–35 or over 55 years, and have no neurological disease or injury, lesions of the palmar surface of the right index finger, history of cardiac arrhythmia, or external pacemaker. A total of 6 participants were excluded from the study and 1 was lost to follow-up following incomplete data collection; 4 participants fell outside of these age ranges and two others self-reported symptoms of neurological disease (numbness and tingling in the fingers). 20 young adults (13 women, 7 men) between the ages of 18 to 29 (22.15 ± 2.78 yrs) and 20 older adults (10 women, 10 men) between the ages of 55 to 71 (61.90 ± 5.61 yrs) met the inclusion criteria and participated in the study (n = 40). Experimental protocols were explained to all participants, and informed and written consent was obtained. Ethical approval to conduct this research was granted by the Clinical Health Research Ethics Board of Alberta in accordance with the Alberta Health Information Act and the declarations of Helsinki. Procedure Participants underwent assessments of clinical skin sensibility using SWMF, TF, and VA testing, in addition to electrophysiological examination. Assessments of sensibility were administered to all participants by three undergraduate raters; raters completed six hours of training lead by an expert researcher prior to data collection. Raters were blinded to the others’ results, and rater and diagnostic test order was randomized for each participant. Neurological exams were administered on each participant during a single session at the University of Calgary’s Integrative Sensorimotor Neuroscience Laboratory. Clinical assessments of sensibility were performed in a seated position with the participant’s right arm resting comfortably on a tabletop. Vision was occluded using a custom-made dividing screen, placed between the participant and rater during testing, to eliminate any visual cues that could confound test results (Fig. 1 ). All testing was performed unilaterally on the right arm. All subjects were right-handed by self-report. Semmes-Weinstein Monofilament Monofilament testing was conducted using 20-monofilaments of differing stiffnesses, each with an associated gram-force. Monofilaments were applied perpendicular to the pulp of the right index finger (Figure 1). When applied to a surface, filaments deliver increasing force until buckling, at which point the pressure remains constant. Light gram-force monofilaments are prone to slipping during application, which is sometimes more easily felt than direct pressure. Raters were instructed to repeat a trial if a filament slid across the surface of the skin or made repeated contact upon application. Monofilaments were applied to the skin for ~1 second. Participants were asked to indicate whether they could or could not perceive a given stimulus by answering “yes” or “no” after each monofilament was applied. Psychophysical tests of this nature are susceptible to false positive responses, given that a participant may say they can feel a stimulus, when in fact they cannot. To ensure threshold values were not underestimated, participants were specifically instructed to say “yes” if they were certain they could feel the stimulus. Further, three “sham applications” were intermixed during each testing block to verify that participants were responding honestly. During a sham trial, the rater would mimic the application of a monofilament without applying it to the skin. In the instance that a participant responded “yes” following multiple sham trials or if they responded before the application of a filament multiple times, testing was terminated, and their data were discounted. Following complete collection of all participant data, cleansing revealed no participants were missing data for monofilament threshold values. In clinical contexts, detection of a single 10-g monofilament is typically used alternatively to the complete 20-piece monofilament kit for simplicity and timeliness. Neurologically healthy adults exhibit sensitivity thresholds well below 10-g of force, so selection of a more sensitive and reliable approach was necessary for this study. Monofilament thresholds estimated using a ‘staircase’ paradigm have shown an insensitivity to rater experience, suitable for novice raters who have undergone a single training session (Snyder et al. 2016 ). Thus, touch-pressure thresholds were estimated from SWMF testing using a 4-2-1 staircase algorithm, as described previously by Dyck and colleagues (Dyck et al. 1993 ). Staircase procedures begin with the delivery of a high-intensity stimulus – easily detectable by participants – followed by delivery of less intense stimuli by standardized increments (“steps”). The 2-g monofilament was selected as a starting point for our staircase procedure based on previous literature (Snyder et al. 2016 ), and was found to be easily detected by all participants. The 4-2-1 staircase procedure began with the application of monofilaments in descending stiffness by 4-step increments with each correct perception of the stimuli (Fig. 2 ). Once a stimulus went incorrectly perceived, monofilaments would be applied in ascending stiffness by 2-step increments. Stimulus intensity would ‘reverse’ again in 1-step increments once a stimulus was correctly perceived. Any change in perception from this point would trigger a 1-step reversal in monofilament stiffness by the rater. A total of 20 trials were administered during a single examination. Touch-pressure threshold values were estimated to be the average gram-force detectable during 1-step reversal points. Tuning Fork Numerous methods exist to employ the 128 Hz tuning fork. The ‘timed on-off’ technique stands out among the many methods to evaluate vibrotactile perception, namely because it allows the practitioner to quantify a patient’s perception with reference to his/her own (Fig. 1 ). This quality contributes to the method’s high overall validity (sensitivity: 80%, specificity: 98%) (Olaleye et al. 2001 ), and may in part explain why the technique is preferred over others. The tuning fork is activated by striking it forcefully against the palm of the hand, but not so forceful that ringing can be heard. Raters were asked to control the force used to activate the fork from trial-to-trial, though some variability in force was guaranteed due to human error. The fork is then applied perpendicular to the dorsal surface of the participant’s right index finger at the distal interphalangeal joint. Raters hold the stem of the tuning fork between their index finger and thumb and are asked to control force of application between trials. The timed on-off technique was performed by asking participants to indicate the moment the tuning fork was applied (“On”) and the exact point vibration dissipated beyond perception (“Off”). Once participants verbally indicated vibration had ended, raters began counting time using a stopwatch. Finally, raters stopped counting time once vibration diminished beyond their own perception. The elapsed time (i.e., discrepancy between participant versus rater perception of stimulus duration) was recorded to the nearest 100th of a second. In alignment with common practice (Martina et al. 1998 ; Temlett 2009 ; Marcuzzi et al. 2019 ), an average of three trials was used for analysis to improve reliability of testing a single skin site. Smartphone Application Smartphone testing was completed using a standard iPhone 11 Pro (Apple, CA, USA), placed screen-side facing upward on a hard surface. VA (Vibratus Inc., AB, Canada) was developed for the purpose of assessing vibrotactile sensitivity. The app harnesses Apple’s Taptic Engine (Apple, CA, USA), a vibrating motor embedded within all iPhone models 8 and onward. VA was pre-calibrated to deliver 128 Hz vibration (Haptic Sharpness: 0.47) along an array of amplitudes (Intensity: 0.05–1.00) allowable by Apple’s Taptic Engine. Instructions were provided to participants directly from the user interface, displayed at the top of the iPhone screen (Fig. 3 ). Participants were instructed to lightly press the pad of their right index finger against a fingerprint icon, displayed centrally on the interface. Perceptual testing was carried out using two-interval, two-alternative, forced-choice trials (Fig. 3 ). They were then instructed to keep their finger pressed against the screen, while two stimulus intervals denoted by the numbers “1” and “2” sequentially appeared for 1 second each on the screen, separated by a 1 second inter-stimulus interval. During a single trial, one of these stimulus intervals would be randomly selected to deliver vibration; participants were prompted to discern which interval was accompanied with vibration by selecting either option “1” or “2”, as displayed on the screen following both intervals. If unsure of which interval was accompanied by vibration, the participant was forced to make a choice (i.e., forced choice). A total of 20 trials were completed to estimate perception threshold. A 4-2-1 staircase procedure identical to SWMF testing operationalized participants’ responses to determine what stimulus intensity would be delivered in subsequent trials. Vibration was delivered at maximal intensity (intensity: 1.00) during the first trial and was adjusted by increments of 5% thereafter. A total of 20 trials were completed during a single examination. The average stimulus intensity of all 1-step reversal points, described as a percentage (%) of maximum deliverable vibration amplitude, was recorded to estimate perception threshold. Ultrasound Imaging Ultrasound images of the right median nerve were obtained from a trained researcher. Nerve imaging was completed using a GE Logiq E9 Ultrasound Machine System (General Electric Company, MA, USA) equipped with a 15 MHz wide-band linear transducer. Participants were instructed to extend their arm in supinated position, while the researcher supported the arm from underneath. The median nerve was cross sectioned 2 cm proximal to the distal wrist crease. After obtaining an image of the nerve, the probe was centered over the nerve, and a mark was placed central to the probe to locate the nerve during nerve conduction studies. Sensory Nerve Conduction Studies NCS are widely accepted as the most valid and comprehensive assessment of peripheral nerve function (sensitivity = 0.88, specificity = 0.93) (Strickland and Gozani 2011 ). Sensory nerve compound action potentials (SNAPs) were recorded from an active and reference electrode positioned at the metacarpal-phalangeal joint of the right index finger and centrally to the distal interphalangeal joint (3–4 cm distal to active electrode) of the same finger, respectively (Fig. 1 ). A ground electrode was placed on the proximal palmar crease to reduce stimulus artifact. Transcutaneous electrical stimulation was delivered antidromically to the median nerve using a handheld external stimulator, with the cathode of the stimulator positioned 14 cm proximal to the active electrode. The room temperature was maintained at 20 o C to mitigate the effects of segmental cooling on NCS parameters. To improve conductance, all skin surfaces in contact with the stimulating probe and electrodes were wiped with 70% alcohol solution and conductive gel (Spectro Gel, Parker Laboratories) was applied to each ring electrode. SNAP recordings were made with ring electrodes connected to a Neurolog NL844 pre-amplifier (gain set to x1000, band-pass filter 10–10,000 Hz; Digitimer) and Neurolog NL820 amplifier (gain set to x2; Digitimer). Stimulus signals were generated in LabVIEW 10 (National Instruments) and sent as voltage values at 10 kHz via a real-time data acquisition system (PXI-6289, BNC-2090, National Instruments) to an isolated bipolar current stimulator (Stimsola, Biopac). Stimulus impulses were delivered as single 0.1 ms duration square current pulses beginning with 5 mA and increasing in 5 mA increments until a maximal response was achieved. A supramaximal current, defined as 20% greater than that required to elicit maximal SNAP amplitude, was delivered during data collection to minimize SNAP amplitude variability between pulses (Preston and Shapiro 2013 ). Testing consisted of delivering 10 pulses of constant supramaximal current, interspersed by periods of rest (~ 5–10 second inter-stimulus intervals). SNAP recordings and stimulus waveforms were sampled at 10 kHz via a Power 1401 data acquisition system running Spike2.0 (Cambridge Electronic Design). A fourth order Butterworth low-pass IIR filter (cut-off = 2 kHz) was applied, and SNAPs were electronically averaged across 10 trials offline with Spike 2.0. Participants spent ~ 30 minutes in our climate-controlled lab space prior to evaluation to reduce the effect of temperature on nerve conduction parameters. Segmental limb temperature was recorded for each participant prior to NCS (31.1 ± 3.3 o C). SNAPs were analyzed for amplitude (µV), calculated from baseline to negative peak. DATA ANALYSIS Sample Size The required sample size was calculated to be 29 participants (Stephen B. Hulley 2013) using the following formula N = [(Z α +Z β )/C] 2 + 3 = 29 where Z α = 1.9600 (the standard normal variate of α ) Z β = 0.8416 (the standard normal variate of β) r = 0.5 (a large effect) N = total number of subjects required C = 0.5 * ln[(1 + r)/(1-r)] = 0.5493 However, a total 40 participants were recruited (β = 0.08) based on previous research conducted on similar topics (Peters et al. 2016 ). Statistical Analysis All statistical analyses were conducted using SPSS Statistics 26 with alpha set at 5%. There was one instance where recording error interfered with collection of VA for a young adult who was later lost to follow-up. Missing data from this participant were managed by recruiting an entirely different participant belonging to the same demographic through convenience sampling (Donders et al. 2006 ). For simplicity, data following a non-normal distribution was analyzed using non-parametric tests where possible, whereas data was transformed logarithmically when parametric tests did not have acceptable non-parametric alternatives (i.e., ICC(2, k )). Shapiro-Wilk testing was performed to determine normality of data. Mean differences between young and older adults were conducted using independent sample t-tests for normally distributed data and using the Mann-Whitney U test for non-normally distributed data. Correlation analysis was performed using Spearman rank correlation coefficient of all measures for consistency, but no acceptable non-parametric surrogate to intraclass-correlation coefficient was found for assessing inter-rater reliability ( k = 3) of continuous data. Instead, data were corrected using log 10 transformation during analysis of reliability. Mean differences between groups are reported alongside their respective t statistic, degrees of freedom, and p values when t-tests were performed, whereas the U statistic and p values are reported for Mann-Whitney U test. Correlations between SNAP amplitude and perceptual thresholds are reported as Spearman correlation coefficient ( r ), with degrees of freedom, p-values, and coefficients of determination (R 2 ) included. No standard criteria for acceptable limits of coefficient of determination is agreed upon, so R 2 values were compared relatively between measures. Correlations were classified according to Cohen’s criteria (1988) wherein an effect of r = 0.1 is small, r = 0.3 is medium, and r = 0.5 is large (Cohen 1988 ). ICC estimates and their 95% confidence intervals were calculated using SPSS statistical package version 26 (SPSS Inc, Chicago, IL) based on mean-rating ( k = 3), absolute agreement, 2-way random effects model (ICC 2,k )to assess inter-rater reliability between single measures of cutaneous sensibility for VA, SWMF, and TF (Shrout and Fleiss 1979 ; Koo and Li 2016 ). This model was chosen because our raters were selected from a sample of students who learned to perform procedural skills characteristic of routine neurological assessments but were not practicing physicians (Koo and Li 2016 ). Absolute agreement was chosen over inter-rater consistency because routine assessments are described quantitatively and compared to absolute normative values for the purposes of discerning abnormal sensibility (McGraw and Wong 1996 ).. While no benchmark values of normal sensibility currently exist for VA, the app was developed with the intent to establish benchmark values, suggesting absolute agreement should be assessed for VA as well. The calculated ICC, and 95% confidence limits are reported here. Although no standard criteria exist for acceptable reliability, general guidelines maintain that 90 is excellent (Koo and Li 2016 ). Results Normality Shapiro-Wilk test of normality identified that all outcome variables were normally distributed within age groups except for SWMF values in the young adult group, which departed significantly from normality (W (20) = .831, p = .003). Thus, A Mann-Whitney U test was used to compare threshold means between-groups for SWMF testing, whereas VA and TF testing were assessed using independent samples t-tests. Levene’s test identified that all outcome variables analyzed parametrically had distributions of equal variance except VA (F(1,38) = 6.082, p = .018). To adjust for this, equal variance was not assumed when calculating between-group differences for VA. Data were collapsed between age groups for comparison of test modalities and rater performance. When data were combined across ages for each outcome variable, positively skewed bimodal distributions were present. Shapiro-Wilk testing revealed significant deviations from normality for values of SWMF (W (40) = .841, p < .001) and VA (W (40) = .970, p = .003). For consistency, all outcome variables underwent log 10 transformation to adjust for positive skew prior to analysis of reliability. Between-group differences Touch-pressure thresholds were statistically significantly lower for young adults (Mdn = 0.02g) compared to older adults (Mdn = 0.06g), U = 29.0, p < .001 (Fig. 5 ). Independent sample t-tests were used to compare inter-group differences for measures of VA, TF, and SNAP amplitude. Perception thresholds were statistically significantly lower for young adults (26.9 ± 9.1%) compared to older adults (40.9 ± 15.6%) when VA was used (t(30.643) = -3.480, p = .002), but no systematic difference was observed between young (3.4 ± 1.4s) and older adults (3.5 ± 1.7) when TF testing was used (t(38) = -0.214, p = 0.831) (Fig. 4 ). SNAP amplitude also showed a statistically significant difference between young (63.2 ± 14.4µV) and older adults (34.6 ± 20.2 µV), t(38) = 5.140, p < .001 (Fig. 4 ). Correlations Two-tailed Spearman rank correlations were computed between perceptual thresholds and SNAP amplitude (Table 1 ). An average of the three raters' perceptual threshold estimates for each instrument (SWMF, TF, and VA) was used in the correlation analysis. A strong and significant correlation was found between SWMF testing and SNAP amplitude (r (38) = -0.60, p < .001) with a coefficient of determination of 35.9% (Fig. 5 ). A non-significant correlation was found between SNAP amplitude and TF testing (r (38) = 0.23, p = .149), as well as with SNAP amplitude and VA (r (38) = -0.22, p = .167). Coefficients of determination showed that 5.3% of the variation between SNAP amplitude and TF thresholds is explained, while 5.0% between SNAP amplitude and VA thresholds is explained. Table 1 Spearman rank correlations between outcome measures Spearman Correlation SWMF TF VA SNAP Amplitude SNAP Amplitude − .60** .23 − .22 1 Notes : SWMF testing strongly and significantly correlated with SNAP amplitude. Significance: p < .005 = *, p < .001 = ** Intraclass Correlation Coefficients Intraclass correlation coefficients were computed by averaging threshold estimates within each test modality and comparing them between raters (Table 2 ). VA was found to demonstrate a poor to good level of inter-rater reliability with an average measured ICC of 0.57 and 95% confidence interval of 0.274 and 0.756 (F(39,78) = 2.327, p < .001). A moderate to excellent level of inter-rater reliability was observed for estimates of sensibility using SWMF testing. The average measured ICC for SWMF was 0.83 with a 95% confidence interval from 0.72 to 0.906 (F(39, 78) = 6.305, p < .001). TF testing was found to demonstrate a poor to moderate level of inter-rater reliability with an average ICC of 0.511 and a 95% confidence interval from 0.18 and 0.73 (F(39,78) = 2.045, p = .004). Table 2 Intraclass correlation coefficient (ICC) estimates and their 95% confidence intervals were calculated based on logarithmically transformed mean-ratings (k = 3) Intraclass Correlation 95% Confidence Interval F Test with True Value 0 Lower Bound Upper Bound Value df 1 df 2 Sig SWMF .834 .719 .906 6.305 39 78 < .001 TF .511 .176 .725 2.045 39 78 .004 VA .568 .274 .756 2.327 39 78 < .001 Notes: Absolute agreement, 2-way random effects model was used to assess inter-rater reliability between single measures of cutaneous sensibility for measurements of SWMF, TF, and VA. Abbreviations: SWMF, Semmes-Weinstein Monofilament; TF, 128-Hz Tuning Fork; VA, Vibratus App. Abbreviations: SWMF, Semmes-Weinstein Monofilament; VA, Vibratus App; SNAP, Sensory Nerve Action Potential; TF, 128-Hz Tuning Fork. Discussion Through our study, we have demonstrated that smartphone generated vibrations delivered via the Vibratus App may be used to identify age-related (and thereby, other neurological disease-related) skin sensitivity loss, and that the Vibratus App produces a similar level of reliability to traditional methods. Regressive and age-related changes to sensory function were also demonstrated through NCS, which showed a gradual reduction in SNAP amplitude with advanced age. Measurements of sensibility taken with monofilaments and the Vibratus App showed a significant reduction in tactile sensibility with age; however, no difference was observed between young and older adults when tuning fork testing was used. Perceptual threshold estimates obtained by three raters demonstrated a nearly identical level of reliability when the Vibratus App and 128-Hz tuning fork testing were compared. This study has uncovered novel evidence that vibrations generated by smartphones may possibly be used to monitor gradual loss of tactile sensibility with equal reliability to 128-Hz tuning fork testing. Reduced Sensation with Age Assessments of sensibility are fundamentally psychophysical, meaning they measure the relationship between perceived versus physical stimuli (Johansson and Vallbo 1979a ). On the basis that no current measure of sensibility optimally combines accessibility with calibrated stimuli and standardized psychophysical procedure, the development of new measures is ongoing (Bril et al. 1997 ; Martina et al. 1998 ; Azzopardi et al. 2018 ). Recent innovation of mobile devices has encouraged their application as remote sensibility monitoring instruments, driven primarily by their ubiquity, but also by their ability to flexibly pair controlled vibration with validated psychophysical procedures (May and Morris 2017 ; Jasmin et al. 2021 ). The Vibratus App is an early example of a such an alternative to traditional sensibility monitoring devices, combining software-standardized testing procedure with calibrated haptics, but prior to this study, had yet to be validated as a measure of age-related sensory loss. Effective monitoring devices are characterized by the ability to delineate subtle changes in functional status. The onset of age-related changes to sensibility occurs early in adulthood but progresses rather gradually until old age (> 55 years) (Bowden and McNulty 2013 ). Age is therefore a useful marker of how sensitivity monitoring devices can discern subtle changes in functional status. Neurological disease or injury such as Diabetic and chemotherapy-induced neuropathy, stroke, and spinal or peripheral nerve damage-induced loss of sensation is far more rapid and profound. Therefore, given age-related loss is detectable using the Vibratus App, we suggest that multiple other neurological patients with sensory loss will also benefit from this novel testing modality. Between-group differences in sensibility were most pronounced when thresholds were estimated using SWMF testing, and to a lesser extent VA testing, though no group difference was observed when perceptual thresholds were estimated using the timed on-off TF method. VA detected a higher-than-normal average perception threshold in the older adult group, which is consistent with more than 30 years of evidence indicating that sensation becomes diminished with age (Thornbury and Mistretta 1981 ; Kenshalo 1986 ). In this study, we utilized the complete 20-piece monofilament kit to evaluate tactile sensibility. Previous studies that employed a similar methodology reported a strong association between SWMF testing and age (Thornbury and Mistretta 1981 ), as well as upper-limb motor function (Dellon and Kallman 1983 ; King 1997 ; Melchior et al. 2007 ). While less evidence has substantiated vibration perception thresholds as a predictor of upper-limb motor control (Dellon and Kallman 1983 ), similar performance between SWMF and VA testing in this study suggests that detection of altered motor function in the elderly may be a possible application of VA in the future. The high associative cost and procedural skillset required to administer the complete 20-piece monofilament kit act as barriers to its adoption in fast paced settings. These barriers may be circumvented through a smartphone-based approach, such as VA, suggesting that future research should investigate the associative strength of VA and upper-limb motor function. The results of our study depicted that SNAP amplitude was significantly reduced in older adults compared to young adults (Fig. 4 ). Diminished SNAP amplitude was expected by our older adult group, as SNAPs generated from nerve excitation directly correspond to the quantity of functioning nerve fibers, which are lost at a relatively constant and gradual rate following maturation (Adalbert and Coleman 2013 ). We were surprised to find that SNAP amplitude and VA were not significantly associated given that VA detected a significant difference between age groups. However, it's important to note that age-related sensory loss is multifactorial and cannot be solely attributed to nerve fiber attrition. As a tool of exploration and manipulation, the human hand is routinely subjected to mechanical stress of varying intensity on a day-to-day basis, causing compensatory changes to properties of the skin over time, such as dermal thickening or increased rigidity (Daly and Odland 1979 ; Potts et al. 1984 ; Baroni et al. 2012 ; Venkatesan et al. 2015 ). Mechanical properties of the skin are unavoidably factored into sensibility estimation when using hand-held instruments, whereas NCS is a purely physiological evaluation of peripheral nerve function, which may explain why VA showed a sensitivity to age, but not to SNAP amplitude. Instrument Reliability A secondary purpose of this study was to evaluate the reliability of VA in contrast to two commonly used hand-held instruments. Manual instruments are burdened by human error and poor standardization, and thus, the application of smartphones offers an excellent opportunity to circumvent this form of bias through software standardization. As proof of this concept, we evaluated the inter-rater reliability of testing using SWMF, TF, and VA to determine the clinical utility of software-operated testing procedures in comparison to human operated instruments when the protocol was standardized. Our study confirmed that perception threshold estimation using smartphone technology is a reliable surrogate to traditional sensibility monitoring devices. TFs are entrenched in fast-paced clinical environments, namely because they are easily accessible, highly durable, and estimate sensibility with acceptable levels of reliability (Lai et al. 2014 ). The findings of this study indicate that smartphone-based assessments can achieve higher inter-rater reliability when estimating vibration perception thresholds compared to traditional tuning forks. This technology is more widely available and easily accessible, indicating that smartphones may possibly serve as a feasible and convenient alternative to tuning forks in fast-paced clinical settings, and critically, can be performed by the user at home, which has important ramifications in remote contexts when access to neurological clinics is limited (e.g., global pandemics, remote communities, and even long-duration space flight). Future directions Given the Vibratus smartphone application may provide sensitive and moderately reliable estimates of cutaneous sensitivity across ages, a logical next step toward achieving remote patient monitoring capabilities is to examine criteria of validity and reliability in environments where the examiners are absent (e.g., at-home testing). Additional research should serve to uncover which variables typical of at-home testing, if any, may confound the outcomes of smartphone testing to ensure test-retest reliability is optimized. Examining the influence of various testing procedures, such as variable testing surfaces, phone cases, and phone models should be explored. This study has shown that smartphones may be used to evaluate age-related decrements to sensation, though pathological causes of tactile sensory loss should also be investigated as they often present hyposensitivity alongside painful sensations which can significantly reduce quality of life. Future research should aim to recruit and test a cohort of participants with and without diagnoses of peripheral and central neural pathology to determine the diagnostic threshold, sensitivity, and specificity of VA as a screening device. As well, inclusion of professional raters with unique experiences in future research may elucidate the influence of rater experience on diagnosing neurological disease when using a smartphone for examination. The innovation of smartphones as instruments of estimating sensory thresholds should be the focus of future research, as it is entirely plausible that the scientific evidence provided here could contribute toward the eventual validation of a remote approach to diagnosing and monitoring neurological disease. Conclusion This study provides novel evidence that delivery of smartphone generated vibrations using a software-standardized testing paradigm may provide a sensitive and moderately reliable measure of tactile sensibility. Physician operated testing modalities require frequent visitation to clinic, which acts as a barrier to precise symptom monitoring for patients who live in remote areas or experience accelerated, progressive loss of sensation. Given that the effect of age on sensibility is perhaps the most gradual of all pathologies, the findings of this study provide evidence in support of the theoretical utility of smartphones as tactile sensitivity monitoring instruments, suggesting that at-home sensitivity monitoring may be a possibility soon. Additional research should be dedicated to investigating which variables – controlled and uncontrolled for in in this study – may impact the outcomes of smartphone derived estimates of tactile sensitivity. Abbreviations SWMF Semmes-Weinstein Monofilament TF 128-Hz Tuning Fork VA Vibratus App. Declarations Data Availability The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Author Contribution O.L. and R.P. conceived of and designed the study, analyzed the data, and created the figures. O.L. wrote the original draft of the manuscript. O.L., H.H., J.B., and A.Y., collected the data. N.O. and R.P. wrote the Vibratus Application software. All authors edited the manuscript. References Adalbert R, Coleman MP. 2013. Review: Axon pathology in age-related neurodegenerative disorders. Neuropathol Appl Neurobiol. 39(2):90–108. Azzopardi K, Gatt A, Chockalingam N, Formosa C. 2018. Hidden dangers revealed by misdiagnosed diabetic neuropathy: A comparison of simple clinical tests for the screening of vibration perception threshold at primary care level. Prim Care Diabetes. 12(2):111–115. Baroni A, Buommino E, De Gregorio V, Ruocco E, Ruocco V, Wolf R. 2012. Structure and function of the epidermis related to barrier properties. Clin Dermatol. 30(3):257–262. Booth J, Young MJ. 2000. Differences in the performance of commercially available 10-g monofilaments. Diabetes Care. 23(7):984–988. Bowden JL, McNulty PA. 2013. Age-related changes in cutaneous sensation in the healthy human hand. Age (Dordr). 35(4):1077–1089. Bril V, Kojic J, Ngo M, Clark K. 1997. Comparison of a neurothesiometer and vibration in measuring vibration perception thresholds and relationship to nerve conduction studies. Diabetes Care. 20(9):1360–1362. Cauna N, Mannan G. 1958. The structure of human digital pacinian corpuscles (corpus cula lamellosa) and its functional significance. J Anat. 92(1):1–20. Cohen J. 1988. Statistical power analysis for the behavioral sciences. 2nd ed. Hillside, NJ: Lawrence Erlbaum Associates. Corniani G, Saal HP. 2020. Tactile innervation densities across the whole body. J Neurophysiol. 124(4):1229–1240. Daly CH, Odland GF. 1979. Age-related changes in the mechanical properties of human skin. J Invest Dermatol. 73(1):84–87. Dellon AL, Kallman CH. 1983. Evaluation of functional sensation in the hand. J Hand Surg Am. 8(6):865–870. Donders AR, van der Heijden GJ, Stijnen T, Moons KG. 2006. Review: a gentle introduction to imputation of missing values. J Clin Epidemiol. 59(10):1087–1091. Dyck PJ, O'Brien PC, Kosanke JL, Gillen DA, Karnes JL. 1993. A 4, 2, and 1 stepping algorithm for quick and accurate estimation of cutaneous sensation threshold. Neurology. 43(8):1508–1512. Ebied AM, Kemp GJ, Frostick SP. 2004. The role of cutaneous sensation in the motor function of the hand. J Orthop Res. 22(4):862–866. Ennis SL, Galea MP, O'Neal DN, Dodson MJ. 2016. Peripheral neuropathy in the hands of people with diabetes mellitus. Diabetes Res Clin Pract. 119:23–31. Garcia-Piqueras J, Garcia-Mesa Y, Carcaba L, Feito J, Torres-Parejo I, Martin-Biedma B, Cobo J, Garcia-Suarez O, Vega JA. 2019. Ageing of the somatosensory system at the periphery: age-related changes in cutaneous mechanoreceptors. J Anat. 234(6):839–852. García-Piqueras J, García‐Mesa Y, Cárcaba L, Feito J, Torres‐Parejo I, Martín‐Biedma B, Cobo J, García‐Suárez O, Vega JA. 2019. Ageing of the somatosensory system at the periphery: age‐related changes in cutaneous mechanoreceptors. Journal of Anatomy. 234(6):839–852. Gescheider GA, Bolanowski SJ, Pope JV, Verrillo RT. 2002. A four-channel analysis of the tactile sensitivity of the fingertip: frequency selectivity, spatial summation, and temporal summation. Somatosens Mot Res. 19(2):114–124. Jasmin M, Yusuf S, Syahrul S, Abrar EA. 2021. Validity and Reliability of a Vibration-Based Cell Phone in Detecting Peripheral Neuropathy among Patients with a Risk of Diabetic Foot Ulcer. Int J Low Extrem Wounds.15347346211037411. Johansson RS, Vallbo AB. 1979a. Detection of tactile stimuli. Thresholds of afferent units related to psychophysical thresholds in the human hand. J Physiol. 297(0):405–422. Johansson RS, Vallbo AB. 1979b. Tactile sensibility in the human hand: relative and absolute densities of four types of mechanoreceptive units in glabrous skin. The Journal of Physiology. 286(1):283–300. Kelly EJ, Terenghi G, Hazari A, Wiberg M. 2005. Nerve fibre and sensory end organ density in the epidermis and papillary dermis of the human hand. Br J Plast Surg. 58(6):774–779. Kenshalo DR, Sr. 1986. Somesthetic sensitivity in young and elderly humans. J Gerontol. 41(6):732–742. King PM. 1997. Sensory function assessment. A pilot comparison study of touch pressure threshold with texture and tactile discrimination. J Hand Ther. 10(1):24–28. Koo TK, Li MY. 2016. A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. J Chiropr Med. 15(2):155–163. Lai S, Ahmed U, Bollineni A, Lewis R, Ramchandren S. 2014. Diagnostic accuracy of qualitative versus quantitative tuning forks: outcome measure for neuropathy. J Clin Neuromuscul Dis. 15(3):96–101. Lipsitz LA, Lough M, Niemi J, Travison T, Howlett H, Manor B. 2015. A shoe insole delivering subsensory vibratory noise improves balance and gait in healthy elderly people. Arch Phys Med Rehabil. 96(3):432–439. MacKinnon CD. 2018. Sensorimotor anatomy of gait, balance, and falls. Handb Clin Neurol. 159:3–26. Marcuzzi A, Wainwright AC, Costa DSJ, Wrigley PJ. 2019. Vibration testing: Optimizing methods to improve reliability. Muscle Nerve. 59(2):229–235. Martina IS, van Koningsveld R, Schmitz PI, van der Meche FG, van Doorn PA. 1998. Measuring vibration threshold with a graduated tuning fork in normal aging and in patients with polyneuropathy. European Inflammatory Neuropathy Cause and Treatment (INCAT) group. J Neurol Neurosurg Psychiatry. 65(5):743–747. May JD, Morris MWJ. 2017. Mobile phone generated vibrations used to detect diabetic peripheral neuropathy. Foot Ankle Surg. 23(4):281–284. McGraw KO, Wong SP. 1996. Forming Inferences About Some Intraclass Correlation Coefficients. Psychological Methods. 1(1):30–46. Melchior H, Vatine JJ, Weiss PL. 2007. Is there a relationship between light touch-pressure sensation and functional hand ability? Disabil Rehabil. 29(7):567–575. Olaleye D, Perkins BA, Bril V. 2001. Evaluation of three screening tests and a risk assessment model for diagnosing peripheral neuropathy in the diabetes clinic. Diabetes Res Clin Pract. 54(2):115–128. Peters RM, McKeown MD, Carpenter MG, Inglis JT. 2016. Losing touch: age-related changes in plantar skin sensitivity, lower limb cutaneous reflex strength, and postural stability in older adults. J Neurophysiol. 116(4):1848–1858. Potts RO, Buras EM, Jr., Chrisman DA, Jr. 1984. Changes with age in the moisture content of human skin. J Invest Dermatol. 82(1):97–100. Preston DC, Shapiro BE. 2013. Electromyography and Neuromuscular Disorders: Clinical-Electrophysiologic Correlations Vol. 3rd ed.. London: Saunders. Shrout PE, Fleiss JL. 1979. Intraclass correlations: uses in assessing rater reliability. Psychol Bull. 86(2):420–428. Snyder BA, Munter AD, Houston MN, Hoch JM, Hoch MC. 2016. Interrater and intrarater reliability of the semmes-weinstein monofilament 4-2-1 stepping algorithm. Muscle Nerve. 53(6):918–924. Stephen B. Hulley SRC, Warren S. Browner, Deborah G. Grady, Thomas B. Newman. 2013. Designing Clinical Research. 4 ed. Philadelphia, PA: Lippincott Williams and Wilkins. Strickland JW, Gozani SN. 2011. Accuracy of in-office nerve conduction studies for median neuropathy: a meta-analysis. J Hand Surg Am. 36(1):52–60. Tavee J. 2019. Nerve conduction studies: Basic concepts. Handb Clin Neurol. 160:217–224. Temlett JA. 2009. An assessment of vibration threshold using a biothesiometer compared to a C128-Hz tuning fork. J Clin Neurosci. 16(11):1435–1438. Thornbury JM, Mistretta CM. 1981. Tactile sensitivity as a function of age. J Gerontol. 36(1):34–39. Tong HC, Werner RA, Franzblau A. 2004. Effect of aging on sensory nerve conduction study parameters. Muscle Nerve. 29(5):716–720. Tremblay F, Wong K, Sanderson R, Cote L. 2003. Tactile spatial acuity in elderly persons: assessment with grating domes and relationship with manual dexterity. Somatosens Mot Res. 20(2):127–132. Venkatesan L, Barlow SM, Kieweg D. 2015. Age- and sex-related changes in vibrotactile sensitivity of hand and face in neurotypical adults. Somatosens Mot Res. 32(1):44–50. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 01 Aug, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 15 Apr, 2024 Reviews received at journal 02 Apr, 2024 Reviews received at journal 25 Mar, 2024 Reviewers agreed at journal 25 Mar, 2024 Reviews received at journal 22 Mar, 2024 Reviewers agreed at journal 18 Mar, 2024 Reviewers agreed at journal 18 Mar, 2024 Reviewers agreed at journal 20 Feb, 2024 Reviewers agreed at journal 17 Feb, 2024 Reviewers invited by journal 30 Jan, 2024 Editor assigned by journal 21 Jan, 2024 Editor invited by journal 07 Dec, 2023 Submission checks completed at journal 07 Dec, 2023 First submitted to journal 01 Dec, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3694234","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":258035314,"identity":"4581f111-5ed3-403d-9506-586cef541d4e","order_by":0,"name":"Owen Lindsay","email":"","orcid":"","institution":"University of Calgary","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Owen","middleName":"","lastName":"Lindsay","suffix":""},{"id":258035319,"identity":"bff2f940-adda-403a-bcea-05a29d97b6f7","order_by":1,"name":"Hanan Hammad","email":"","orcid":"","institution":"University of Calgary","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hanan","middleName":"","lastName":"Hammad","suffix":""},{"id":258035323,"identity":"bbb866bc-91fd-48c3-805b-54a25f119a67","order_by":2,"name":"James Baysic","email":"","orcid":"","institution":"University of Calgary","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"James","middleName":"","lastName":"Baysic","suffix":""},{"id":258035327,"identity":"3717d7c6-7199-4b86-8cbe-5ccba1e3efce","order_by":3,"name":"Abbey Young","email":"","orcid":"","institution":"University of Calgary","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Abbey","middleName":"","lastName":"Young","suffix":""},{"id":258035328,"identity":"1ed45146-4d25-47ba-a479-7a5bb2907914","order_by":4,"name":"Nasir Osman","email":"","orcid":"","institution":"University of Calgary","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Nasir","middleName":"","lastName":"Osman","suffix":""},{"id":258035332,"identity":"e68a3fe4-d9e4-4428-8f90-4131c7ce3bdd","order_by":5,"name":"Reed Ferber","email":"","orcid":"","institution":"University of Calgary","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Reed","middleName":"","lastName":"Ferber","suffix":""},{"id":258035336,"identity":"e1456184-fb4a-44c5-9625-2378354727f8","order_by":6,"name":"Nicole Culos-Reed","email":"","orcid":"","institution":"University of Calgary","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Nicole","middleName":"","lastName":"Culos-Reed","suffix":""},{"id":258035340,"identity":"075d4447-85bf-4f47-a252-51d8cff1a82e","order_by":7,"name":"Ryan Peters","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDUlEQVRIie2RsUoDQRBAZw3kmsG1nKCQX9gQMAje3a/csZA0SSWEVJJqq0PbA+38BEFSbtjimsXa8kC4KkUkIOnixk5hJXaC+2CGYZjHDAxAIPDX0WuXjg+dJhdsWbrc/o3SMniIMihlU7PF5TU/rWoTq6Tb5g/NBiHp+pSzl+FAMDukzs1YmImSPUVN/w5B9ua+gyg7J6YMCYvgFM0U6X4LQTO/Mnp3yo5SG9XmQulUUbXZK6lfGe+3aBIIwrgiV7z43JJ7FVxNKbeyU1oUy+JZSkV4xe6FlF4lGj3R2yLhvIhe19tpEt/y6hFWsyT2KXCSAXy9gTI4QuGbd3Dt3j7/1mHbH4xAIBD4d3wAkO5R4dMxh0YAAAAASUVORK5CYII=","orcid":"","institution":"University of Calgary","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Ryan","middleName":"","lastName":"Peters","suffix":""}],"badges":[],"createdAt":"2023-12-01 20:14:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3694234/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3694234/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-68579-1","type":"published","date":"2024-08-01T15:57:14+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":47983783,"identity":"255302b5-e17e-483f-82e8-60058f201697","added_by":"auto","created_at":"2023-12-11 14:31:36","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":214576,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRoutine neurological assessments of peripheral nerve function. \u003c/strong\u003eA. Nerve conduction studies, performed by sending electrical impulses to the median nerve and recording the latency and amplitude of compound action potential at the finger. B. Timed tuning fork testing, performed by applying an activated 128-Hz tuning fork to the finger and asking participants to indicate when they no longer feel vibration. C. Semmes-Weinstein monofilament testing, performed by applying monofilaments of varying stiffness to the finger and asking participants to indicate whether they can or cannot feel the stimulus.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3694234/v1/f8f325b0b5d47304bd77dd49.jpg"},{"id":47982566,"identity":"ce8b74e8-226f-4c90-9b37-46236b059b3b","added_by":"auto","created_at":"2023-12-11 14:23:36","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":27185,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic representation of 4-2-1 staircase procedure. \u003c/strong\u003eThe psychophysical paradigm begins mid-way between the least and most intense stimuli. Stimulus intensity changes intensity in 4-step increments with each correct response initially, reversing intensity in 2-step increments at the first incorrect response, and reversing intensity in 1-step increments at each change in response thereafter. The mean of 1-step reversals was used to estimate threshold intensity.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3694234/v1/8e67139bcb03da8661f3bb22.jpg"},{"id":47982568,"identity":"574304a8-df93-4ece-af66-5c485b0fc489","added_by":"auto","created_at":"2023-12-11 14:23:36","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":89462,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVibrotactile detection threshold estimation using the Vibratus App. \u003c/strong\u003eApp screenshots from left to right depict the sequence of events occurring on a single trial. Each trials begins when the user places their fingertip or other skin surface onto the screen (First screen). Following this, two sequentially presented intervals denoted “1” and “2” are provided. Vibration is applied randomly during one of these two intervals, and the user must then select which interval (“1” or “2”) contained the vibration by pressing buttons on the screen (fourth screen). This is a two-alternative forced choice (2AFC) trial structure. Based on whether the user responds correctly on each trial, the amplitude of vibration is stepped up or down using a 4-2-1 staircase algorithm. Vibrotactile detection is estimated as the lowest detectable vibratory “intensity” ranging from 0.05 – 1 (fifth screen).\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3694234/v1/626bbe1ac672e081176c4f91.jpg"},{"id":47984371,"identity":"c1e57f32-86a5-4742-89ef-33b2660e2967","added_by":"auto","created_at":"2023-12-11 14:39:36","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":51660,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe Vibratus App, as well as monofilaments and nerve conduction studies, provides sensitive estimates of age-related changes to tactile sensitivity.\u003c/strong\u003e A-D: Bar graphs showing raw mean values (±SD) of perceptual thresholds (A-C) and sensory nerve action potential amplitude (D) between young and older adults.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3694234/v1/48894e6b4c8bc6105f2e072f.jpg"},{"id":47982569,"identity":"7f6f5b73-e498-4560-899c-67de33d1140c","added_by":"auto","created_at":"2023-12-11 14:23:36","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":68341,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMeasurements taken with monofilaments showed a strong association with sensory nerve action potential amplitude, whereas the Vibratus App and tuning fork testing did not. \u003c/strong\u003eA-C: Scatter plots showing the association between age-related decline of sensibility and sensory nerve action potential amplitude.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3694234/v1/fd843eb911c5ea00a9a88c33.jpg"},{"id":61793434,"identity":"6b308aa1-4809-4566-befd-6d3752bebb05","added_by":"auto","created_at":"2024-08-05 16:12:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1111675,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3694234/v1/190d88a4-8111-4ac9-908c-5d94722ae5be.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Healthcare monitoring at your fingertips: validation of a smartphone alternative to routine measures of skin sensibility","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSkin sensibility plays an important role in navigating the external environment and executing goal-directed actions. The fluidity and precision with which dexterous motor tasks are executed is functionally limited by the hand\u0026rsquo;s capacity to discern the frequency and intensity of various tactile stimuli (Dellon and Kallman \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1983\u003c/span\u003e; King \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Ebied et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Melchior et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). It is postulated that age-related changes affecting mechanoreceptors of the hand are the primary cause of diminished tactile sensibility in the elderly (Cauna and Mannan \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1958\u003c/span\u003e; Daly and Odland \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1979\u003c/span\u003e; Gescheider et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Tremblay et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Bowden and McNulty \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Ennis et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Garc\u0026iacute;a-Piqueras et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Additionally, other contributing factors, such as skin dehydration and altered elasticity, have also been identified as secondary limitations to cutaneous sensation with advanced age (Daly and Odland \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1979\u003c/span\u003e; Potts et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1984\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eManipulation of the hand is controlled by sensory feedback from low-threshold cutaneous receptors, known as Meissner\u0026rsquo;s and Pacinian corpuscles, Ruffini endings, and Merkel cells (Johansson and Vallbo \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1979b\u003c/span\u003e). These receptors and their afferents densely innervate the fingertips (Johansson and Vallbo \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1979b\u003c/span\u003e), allowing us to functionally integrate tactile feedback during tasks requiring precision (Kelly et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Corniani and Saal \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Histological studies (Cauna and Mannan \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1958\u003c/span\u003e; Garcia-Piqueras et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) have identified a reduction to Pacinian and Meissner\u0026rsquo;s Corpuscle density with age, as well as morphological changes. These regressive changes to the physical form and number of afferents disrupts the mechanisms driving cutaneous feedback, which has been associated with clumsy and slowed dexterity (Ebied et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; MacKinnon \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Due to the heterogeneity of age-related sensory loss among healthy adults, there is mixed evidence regarding which mechanoreceptors are reduced in number and at what rate they are lost (Cauna and Mannan \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1958\u003c/span\u003e; Garcia-Piqueras et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e); However, a general consensus has been reached that those over 55 years of age become considerably higher risk of developing abnormal upper-limb sensory and motor function with time (Kenshalo \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1986\u003c/span\u003e; Tong et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Bowden and McNulty \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Since the onset and progression of symptoms relating to age-related sensory loss vary significantly among older adults, treatment strategies based on frequent and precise sensibility testing may benefit the elderly. One way of monitoring symptom progression with high frequency is to utilize methods that can be operated remotely. Contrary to traditional approaches to sensibility testing, such as Semmes-Weinstein monofilament (SWMF) testing and 128-Hz tuning fork (TF) testing, smartphones are ubiquitous and employ software-operated procedure, suggesting they are possibly a useful tool for developing targeted interventions, and by extension, may address the need for accurate and remote healthcare.\u003c/p\u003e \u003cp\u003eGiven the potential of smartphones as an at-home alternative to traditional approaches of sensibility monitoring, there is a need to establish the validity and reliability of smartphone-based testing by comparing it to criterion- and reference-standard approaches. Nerve conduction studies (NCS), an electrodiagnostic evaluation of evoked sensory or motor compound action potentials, is widely regarded to be the criterion standard with which other test modalities are validated against. Specifically, sensory nerve action potential (SNAP) amplitude is a metric derived from NCS identified as a highly sensitive marker of age, owing to a reduction to the number of nerve fibers over the lifespan (Tong et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Preston and Shapiro \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Garc\u0026iacute;a-Piqueras et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Conversely, manual instruments evoke perceptual responses that reflect mechanical properties of the skin, such as elasticity and hydration, as well as altered mechanoreceptor density and morphology. As an initial step toward achieving remote sensibility monitoring, the theoretical utility of smartphones must be demonstrated in applied contexts, with reference to criterion-standard and manual approaches for comparison.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eSmartphones are poised to relay frequent and accurate information about a patient\u0026rsquo;s functional sensibility to healthcare providers, which may promote informed decision-making when strategizing treatment options, leading to improved outcomes and quality of life. Additionally, remote sensibility monitoring enabled by smartphone technology may increase access to care for elderly adults who have difficulty visiting the clinic. The aim of this study was to (1) evaluate the Vibratus App (VA) as a mode of estimating tactile sensitivity across ages, drawing on the performance of traditional instruments and NCS for comparison, and (2) compare the inter-rater reliability of estimates of tactile sensibility using human- versus software-standardized testing procedures. There may be a benefit to measuring sensibility using an approach that minimally involves practitioners, as it mitigates the influence of human error on the outcome of examination. Therefore, we hypothesize that measurements taken with VA will demonstrate an associative strength to NCS that exceeds SWMF and TF testing. Similarly, we hypothesize that VA will detect higher (poorer) perceptual thresholds among older adults compared to young adults, indicating regressive age-related changes to sensibility. We also hypothesize that VA will demonstrate a higher level of reliability in comparison to the manual instruments.\u003c/p\u003e \u003c/div\u003e"},{"header":"Material and methods","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n\u003ch2\u003eParticipants\u003c/h2\u003e\n\u003cp\u003eA sample of 47 adults were recruited using convenience sampling from May 2021 to April 2022. For inclusion in the research study, participants had to be between the ages of 18\u0026ndash;35 or over 55 years, and have no neurological disease or injury, lesions of the palmar surface of the right index finger, history of cardiac arrhythmia, or external pacemaker. A total of 6 participants were excluded from the study and 1 was lost to follow-up following incomplete data collection; 4 participants fell outside of these age ranges and two others self-reported symptoms of neurological disease (numbness and tingling in the fingers). 20 young adults (13 women, 7 men) between the ages of 18 to 29 (22.15\u0026thinsp;\u0026plusmn;\u0026thinsp;2.78 yrs) and 20 older adults (10 women, 10 men) between the ages of 55 to 71 (61.90\u0026thinsp;\u0026plusmn;\u0026thinsp;5.61 yrs) met the inclusion criteria and participated in the study (n\u0026thinsp;=\u0026thinsp;40). Experimental protocols were explained to all participants, and informed and written consent was obtained. Ethical approval to conduct this research was granted by the Clinical Health Research Ethics Board of Alberta in accordance with the Alberta Health Information Act and the declarations of Helsinki.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eProcedure\u003c/h3\u003e\n\u003cp\u003eParticipants underwent assessments of clinical skin sensibility using SWMF, TF, and VA testing, in addition to electrophysiological examination. Assessments of sensibility were administered to all participants by three undergraduate raters; raters completed six hours of training lead by an expert researcher prior to data collection. Raters were blinded to the others\u0026rsquo; results, and rater and diagnostic test order was randomized for each participant. Neurological exams were administered on each participant during a single session at the University of Calgary\u0026rsquo;s Integrative Sensorimotor Neuroscience Laboratory.\u003c/p\u003e\n\u003cp\u003eClinical assessments of sensibility were performed in a seated position with the participant\u0026rsquo;s right arm resting comfortably on a tabletop. Vision was occluded using a custom-made dividing screen, placed between the participant and rater during testing, to eliminate any visual cues that could confound test results (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). All testing was performed unilaterally on the right arm. All subjects were right-handed by self-report.\u003c/p\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n\u003ch2\u003eSemmes-Weinstein Monofilament\u003c/h2\u003e\n\u003cp\u003eMonofilament testing was conducted using 20-monofilaments of differing stiffnesses, each with an associated gram-force. Monofilaments were applied perpendicular to the pulp of the right index finger (Figure 1). When applied to a surface, filaments deliver increasing force until buckling, at which point the pressure remains constant. Light gram-force monofilaments are prone to slipping during application, which is sometimes more easily felt than direct pressure. Raters were instructed to repeat a trial if a filament slid across the surface of the skin or made repeated contact upon application. Monofilaments were applied to the skin for ~1 second. Participants were asked to indicate whether they could or could not perceive a given stimulus by answering \u0026ldquo;yes\u0026rdquo; or \u0026ldquo;no\u0026rdquo; after each monofilament was applied. Psychophysical tests of this nature are susceptible to false positive responses, given that a participant may say they can feel a stimulus, when in fact they cannot. To ensure threshold values were not underestimated, participants were specifically instructed to say \u0026ldquo;yes\u0026rdquo; if they were certain they could feel the stimulus. Further, three \u0026ldquo;sham applications\u0026rdquo; were intermixed during each testing block to verify that participants were responding honestly. During a sham trial, the rater would mimic the application of a monofilament without applying it to the skin. In the instance that a participant responded \u0026ldquo;yes\u0026rdquo; following multiple sham trials or if they responded before the application of a filament multiple times, testing was terminated, and their data were discounted. Following complete collection of all participant data, cleansing revealed no participants were missing data for monofilament threshold values.\u003c/p\u003e\n\u003cp\u003eIn clinical contexts, detection of a single 10-g monofilament is typically used alternatively to the complete 20-piece monofilament kit for simplicity and timeliness. Neurologically healthy adults exhibit sensitivity thresholds well below 10-g of force, so selection of a more sensitive and reliable approach was necessary for this study. Monofilament thresholds estimated using a \u0026lsquo;staircase\u0026rsquo; paradigm have shown an insensitivity to rater experience, suitable for novice raters who have undergone a single training session (Snyder et al. \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). Thus, touch-pressure thresholds were estimated from SWMF testing using a 4-2-1 staircase algorithm, as described previously by Dyck and colleagues (Dyck et al. \u003cspan class=\"CitationRef\"\u003e1993\u003c/span\u003e). Staircase procedures begin with the delivery of a high-intensity stimulus \u0026ndash; easily detectable by participants \u0026ndash; followed by delivery of less intense stimuli by standardized increments (\u0026ldquo;steps\u0026rdquo;). The 2-g monofilament was selected as a starting point for our staircase procedure based on previous literature (Snyder et al. \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e), and was found to be easily detected by all participants. The 4-2-1 staircase procedure began with the application of monofilaments in descending stiffness by 4-step increments with each correct perception of the stimuli (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Once a stimulus went incorrectly perceived, monofilaments would be applied in ascending stiffness by 2-step increments. Stimulus intensity would \u0026lsquo;reverse\u0026rsquo; again in 1-step increments once a stimulus was correctly perceived. Any change in perception from this point would trigger a 1-step reversal in monofilament stiffness by the rater. A total of 20 trials were administered during a single examination. Touch-pressure threshold values were estimated to be the average gram-force detectable during 1-step reversal points.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003eTuning Fork\u003c/h2\u003e\n\u003cp\u003eNumerous methods exist to employ the 128 Hz tuning fork. The \u0026lsquo;timed on-off\u0026rsquo; technique stands out among the many methods to evaluate vibrotactile perception, namely because it allows the practitioner to quantify a patient\u0026rsquo;s perception with reference to his/her own (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). This quality contributes to the method\u0026rsquo;s high overall validity (sensitivity: 80%, specificity: 98%) (Olaleye et al. \u003cspan class=\"CitationRef\"\u003e2001\u003c/span\u003e), and may in part explain why the technique is preferred over others. The tuning fork is activated by striking it forcefully against the palm of the hand, but not so forceful that ringing can be heard. Raters were asked to control the force used to activate the fork from trial-to-trial, though some variability in force was guaranteed due to human error. The fork is then applied perpendicular to the dorsal surface of the participant\u0026rsquo;s right index finger at the distal interphalangeal joint. Raters hold the stem of the tuning fork between their index finger and thumb and are asked to control force of application between trials. The timed on-off technique was performed by asking participants to indicate the moment the tuning fork was applied (\u0026ldquo;On\u0026rdquo;) and the exact point vibration dissipated beyond perception (\u0026ldquo;Off\u0026rdquo;). Once participants verbally indicated vibration had ended, raters began counting time using a stopwatch. Finally, raters stopped counting time once vibration diminished beyond their own perception. The elapsed time (i.e., discrepancy between participant versus rater perception of stimulus duration) was recorded to the nearest 100th of a second. In alignment with common practice (Martina et al. \u003cspan class=\"CitationRef\"\u003e1998\u003c/span\u003e; Temlett \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e; Marcuzzi et al. \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e), an average of three trials was used for analysis to improve reliability of testing a single skin site.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003eSmartphone Application\u003c/h2\u003e\n\u003cp\u003eSmartphone testing was completed using a standard iPhone 11 Pro (Apple, CA, USA), placed screen-side facing upward on a hard surface. VA (Vibratus Inc., AB, Canada) was developed for the purpose of assessing vibrotactile sensitivity. The app harnesses Apple\u0026rsquo;s Taptic Engine (Apple, CA, USA), a vibrating motor embedded within all iPhone models 8 and onward. VA was pre-calibrated to deliver 128 Hz vibration (Haptic Sharpness: 0.47) along an array of amplitudes (Intensity: 0.05\u0026ndash;1.00) allowable by Apple\u0026rsquo;s Taptic Engine.\u003c/p\u003e\n\u003cp\u003eInstructions were provided to participants directly from the user interface, displayed at the top of the iPhone screen (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Participants were instructed to lightly press the pad of their right index finger against a fingerprint icon, displayed centrally on the interface. Perceptual testing was carried out using two-interval, two-alternative, forced-choice trials (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). They were then instructed to keep their finger pressed against the screen, while two stimulus intervals denoted by the numbers \u0026ldquo;1\u0026rdquo; and \u0026ldquo;2\u0026rdquo; sequentially appeared for 1 second each on the screen, separated by a 1 second inter-stimulus interval. During a single trial, one of these stimulus intervals would be randomly selected to deliver vibration; participants were prompted to discern which interval was accompanied with vibration by selecting either option \u0026ldquo;1\u0026rdquo; or \u0026ldquo;2\u0026rdquo;, as displayed on the screen following both intervals. If unsure of which interval was accompanied by vibration, the participant was forced to make a choice (i.e., forced choice). A total of 20 trials were completed to estimate perception threshold. A 4-2-1 staircase procedure identical to SWMF testing operationalized participants\u0026rsquo; responses to determine what stimulus intensity would be delivered in subsequent trials. Vibration was delivered at maximal intensity (intensity: 1.00) during the first trial and was adjusted by increments of 5% thereafter. A total of 20 trials were completed during a single examination. The average stimulus intensity of all 1-step reversal points, described as a percentage (%) of maximum deliverable vibration amplitude, was recorded to estimate perception threshold.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003eUltrasound Imaging\u003c/h2\u003e\n\u003cp\u003eUltrasound images of the right median nerve were obtained from a trained researcher. Nerve imaging was completed using a GE Logiq E9 Ultrasound Machine System (General Electric Company, MA, USA) equipped with a 15 MHz wide-band linear transducer. Participants were instructed to extend their arm in supinated position, while the researcher supported the arm from underneath. The median nerve was cross sectioned 2 cm proximal to the distal wrist crease. After obtaining an image of the nerve, the probe was centered over the nerve, and a mark was placed central to the probe to locate the nerve during nerve conduction studies.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003eSensory Nerve Conduction Studies\u003c/h2\u003e\n\u003cp\u003eNCS are widely accepted as the most valid and comprehensive assessment of peripheral nerve function (sensitivity\u0026thinsp;=\u0026thinsp;0.88, specificity\u0026thinsp;=\u0026thinsp;0.93) (Strickland and Gozani \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e). Sensory nerve compound action potentials (SNAPs) were recorded from an active and reference electrode positioned at the metacarpal-phalangeal joint of the right index finger and centrally to the distal interphalangeal joint (3\u0026ndash;4 cm distal to active electrode) of the same finger, respectively (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). A ground electrode was placed on the proximal palmar crease to reduce stimulus artifact. Transcutaneous electrical stimulation was delivered antidromically to the median nerve using a handheld external stimulator, with the cathode of the stimulator positioned 14 cm proximal to the active electrode. The room temperature was maintained at 20\u003csup\u003eo\u003c/sup\u003eC to mitigate the effects of segmental cooling on NCS parameters. To improve conductance, all skin surfaces in contact with the stimulating probe and electrodes were wiped with 70% alcohol solution and conductive gel (Spectro Gel, Parker Laboratories) was applied to each ring electrode.\u003c/p\u003e\n\u003cp\u003eSNAP recordings were made with ring electrodes connected to a Neurolog NL844 pre-amplifier (gain set to x1000, band-pass filter 10\u0026ndash;10,000 Hz; Digitimer) and Neurolog NL820 amplifier (gain set to x2; Digitimer). Stimulus signals were generated in LabVIEW 10 (National Instruments) and sent as voltage values at 10 kHz via a real-time data acquisition system (PXI-6289, BNC-2090, National Instruments) to an isolated bipolar current stimulator (Stimsola, Biopac). Stimulus impulses were delivered as single 0.1 ms duration square current pulses beginning with 5 mA and increasing in 5 mA increments until a maximal response was achieved. A supramaximal current, defined as 20% greater than that required to elicit maximal SNAP amplitude, was delivered during data collection to minimize SNAP amplitude variability between pulses (Preston and Shapiro \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). Testing consisted of delivering 10 pulses of constant supramaximal current, interspersed by periods of rest (~\u0026thinsp;5\u0026ndash;10 second inter-stimulus intervals). SNAP recordings and stimulus waveforms were sampled at 10 kHz via a Power 1401 data acquisition system running Spike2.0 (Cambridge Electronic Design). A fourth order Butterworth low-pass IIR filter (cut-off =\u0026thinsp;2 kHz) was applied, and SNAPs were electronically averaged across 10 trials offline with Spike 2.0. Participants spent\u0026thinsp;~\u0026thinsp;30 minutes in our climate-controlled lab space prior to evaluation to reduce the effect of temperature on nerve conduction parameters. Segmental limb temperature was recorded for each participant prior to NCS (31.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3\u003csup\u003eo\u003c/sup\u003eC). SNAPs were analyzed for amplitude (\u0026micro;V), calculated from baseline to negative peak.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003ch2\u003eDATA ANALYSIS\u003c/h2\u003e\n\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\n\u003ch2\u003eSample Size\u003c/h2\u003e\n\u003cp\u003eThe required sample size was calculated to be 29 participants (Stephen B. Hulley 2013) using the following formula\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n\u003cp\u003eN = [(Z\u003csub\u003e\u0026alpha;\u003c/sub\u003e+Z\u003csub\u003e\u0026beta;\u003c/sub\u003e)/C]\u003csup\u003e2\u003c/sup\u003e + 3\u0026thinsp;=\u0026thinsp;29\u003c/p\u003e\n\u003cp\u003ewhere\u003c/p\u003e\n\u003cp\u003eZ\u003csub\u003e\u0026alpha;\u003c/sub\u003e = 1.9600 (the standard normal variate of \u003cem\u003e\u0026alpha;\u003c/em\u003e)\u003c/p\u003e\n\u003cp\u003eZ\u003csub\u003e\u0026beta;\u003c/sub\u003e = 0.8416 (the standard normal variate of \u0026beta;)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.5 (a large effect)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;total number of subjects required\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n\u003cp\u003eC\u0026thinsp;=\u0026thinsp;0.5 * ln[(1\u0026thinsp;+\u0026thinsp;r)/(1-r)]\u0026thinsp;=\u0026thinsp;0.5493\u003c/p\u003e\n\u003cp\u003eHowever, a total 40 participants were recruited (\u0026beta;\u0026thinsp;=\u0026thinsp;0.08) based on previous research conducted on similar topics (Peters et al. \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n\u003cp\u003eAll statistical analyses were conducted using SPSS Statistics 26 with alpha set at 5%. There was one instance where recording error interfered with collection of VA for a young adult who was later lost to follow-up. Missing data from this participant were managed by recruiting an entirely different participant belonging to the same demographic through convenience sampling (Donders et al. \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eFor simplicity, data following a non-normal distribution was analyzed using non-parametric tests where possible, whereas data was transformed logarithmically when parametric tests did not have acceptable non-parametric alternatives (i.e., ICC(2,\u003cem\u003ek\u003c/em\u003e)). Shapiro-Wilk testing was performed to determine normality of data. Mean differences between young and older adults were conducted using independent sample t-tests for normally distributed data and using the Mann-Whitney U test for non-normally distributed data. Correlation analysis was performed using Spearman rank correlation coefficient of all measures for consistency, but no acceptable non-parametric surrogate to intraclass-correlation coefficient was found for assessing inter-rater reliability (\u003cem\u003ek\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3) of continuous data. Instead, data were corrected using log\u003csub\u003e10\u003c/sub\u003e transformation during analysis of reliability.\u003c/p\u003e\n\u003cp\u003eMean differences between groups are reported alongside their respective t statistic, degrees of freedom, and p values when t-tests were performed, whereas the U statistic and p values are reported for Mann-Whitney U test. Correlations between SNAP amplitude and perceptual thresholds are reported as Spearman correlation coefficient (\u003cem\u003er\u003c/em\u003e), with degrees of freedom, p-values, and coefficients of determination (R\u003csup\u003e2\u003c/sup\u003e) included. No standard criteria for acceptable limits of coefficient of determination is agreed upon, so R\u003csup\u003e2\u003c/sup\u003e values were compared relatively between measures. Correlations were classified according to Cohen\u0026rsquo;s criteria (1988) wherein an effect of r\u0026thinsp;=\u0026thinsp;0.1 is small, r\u0026thinsp;=\u0026thinsp;0.3 is medium, and r\u0026thinsp;=\u0026thinsp;0.5 is large (Cohen \u003cspan class=\"CitationRef\"\u003e1988\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eICC estimates and their 95% confidence intervals were calculated using SPSS statistical package version 26 (SPSS Inc, Chicago, IL) based on mean-rating (\u003cem\u003ek\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3), absolute agreement, 2-way random effects model (ICC\u003csub\u003e2,k\u003c/sub\u003e)to assess inter-rater reliability between single measures of cutaneous sensibility for VA, SWMF, and TF (Shrout and Fleiss \u003cspan class=\"CitationRef\"\u003e1979\u003c/span\u003e; Koo and Li \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). This model was chosen because our raters were selected from a sample of students who learned to perform procedural skills characteristic of routine neurological assessments but were not practicing physicians (Koo and Li \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). Absolute agreement was chosen over inter-rater consistency because routine assessments are described quantitatively and compared to absolute normative values for the purposes of discerning abnormal sensibility (McGraw and Wong \u003cspan class=\"CitationRef\"\u003e1996\u003c/span\u003e).. While no benchmark values of normal sensibility currently exist for VA, the app was developed with the intent to establish benchmark values, suggesting absolute agreement should be assessed for VA as well. The calculated ICC, and 95% confidence limits are reported here. Although no standard criteria exist for acceptable reliability, general guidelines maintain that \u0026lt;\u0026thinsp;0.50 is poor, 0.50\u0026ndash;0.75 is moderate, 0.75\u0026ndash;0.90 is good, and \u0026gt;\u0026thinsp;90 is excellent (Koo and Li \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n\u003ch2\u003eNormality\u003c/h2\u003e\n\u003cp\u003eShapiro-Wilk test of normality identified that all outcome variables were normally distributed within age groups except for SWMF values in the young adult group, which departed significantly from normality (W (20)\u0026thinsp;=\u0026thinsp;.831, p\u0026thinsp;=\u0026thinsp;.003). Thus, A Mann-Whitney U test was used to compare threshold means between-groups for SWMF testing, whereas VA and TF testing were assessed using independent samples t-tests. Levene\u0026rsquo;s test identified that all outcome variables analyzed parametrically had distributions of equal variance except VA (F(1,38)\u0026thinsp;=\u0026thinsp;6.082, p\u0026thinsp;=\u0026thinsp;.018). To adjust for this, equal variance was not assumed when calculating between-group differences for VA. Data were collapsed between age groups for comparison of test modalities and rater performance. When data were combined across ages for each outcome variable, positively skewed bimodal distributions were present. Shapiro-Wilk testing revealed significant deviations from normality for values of SWMF (W (40)\u0026thinsp;=\u0026thinsp;.841, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and VA (W (40)\u0026thinsp;=\u0026thinsp;.970, p\u0026thinsp;=\u0026thinsp;.003). For consistency, all outcome variables underwent log\u003csub\u003e10\u003c/sub\u003e transformation to adjust for positive skew prior to analysis of reliability.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n\u003ch2\u003eBetween-group differences\u003c/h2\u003e\n\u003cp\u003eTouch-pressure thresholds were statistically significantly lower for young adults (Mdn\u0026thinsp;=\u0026thinsp;0.02g) compared to older adults (Mdn\u0026thinsp;=\u0026thinsp;0.06g), U\u0026thinsp;=\u0026thinsp;29.0, p\u0026thinsp;\u0026lt;\u0026thinsp;.001 (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). Independent sample t-tests were used to compare inter-group differences for measures of VA, TF, and SNAP amplitude. Perception thresholds were statistically significantly lower for young adults (26.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9.1%) compared to older adults (40.9\u0026thinsp;\u0026plusmn;\u0026thinsp;15.6%) when VA was used (t(30.643) = -3.480, p\u0026thinsp;=\u0026thinsp;.002), but no systematic difference was observed between young (3.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4s) and older adults (3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7) when TF testing was used (t(38) = -0.214, p\u0026thinsp;=\u0026thinsp;0.831) (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). SNAP amplitude also showed a statistically significant difference between young (63.2\u0026thinsp;\u0026plusmn;\u0026thinsp;14.4\u0026micro;V) and older adults (34.6\u0026thinsp;\u0026plusmn;\u0026thinsp;20.2 \u0026micro;V), t(38)\u0026thinsp;=\u0026thinsp;5.140, p\u0026thinsp;\u0026lt;\u0026thinsp;.001 (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n\u003ch2\u003eCorrelations\u003c/h2\u003e\n\u003cp\u003eTwo-tailed Spearman rank correlations were computed between perceptual thresholds and SNAP amplitude (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). An average of the three raters' perceptual threshold estimates for each instrument (SWMF, TF, and VA) was used in the correlation analysis. A strong and significant correlation was found between SWMF testing and SNAP amplitude (r (38) = -0.60, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) with a coefficient of determination of 35.9% (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). A non-significant correlation was found between SNAP amplitude and TF testing (r (38)\u0026thinsp;=\u0026thinsp;0.23, p\u0026thinsp;=\u0026thinsp;.149), as well as with SNAP amplitude and VA (r (38) = -0.22, p\u0026thinsp;=\u0026thinsp;.167). Coefficients of determination showed that 5.3% of the variation between SNAP amplitude and TF thresholds is explained, while 5.0% between SNAP amplitude and VA thresholds is explained.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eSpearman rank correlations between outcome measures\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSpearman\u003c/p\u003e\n\u003cp\u003eCorrelation\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSWMF\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTF\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eVA\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSNAP\u003c/p\u003e\n\u003cp\u003eAmplitude\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSNAP Amplitude\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;\u0026thinsp;.60**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e.23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026minus;\u0026thinsp;.22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003e\u003cstrong\u003eNotes\u003c/strong\u003e: SWMF testing strongly and significantly correlated with SNAP amplitude. Significance: p\u0026thinsp;\u0026lt;\u0026thinsp;.005 = *, p\u0026thinsp;\u0026lt;\u0026thinsp;.001 = **\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n\u003ch2\u003eIntraclass Correlation Coefficients\u003c/h2\u003e\n\u003cp\u003eIntraclass correlation coefficients were computed by averaging threshold estimates within each test modality and comparing them between raters (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). VA was found to demonstrate a poor to good level of inter-rater reliability with an average measured ICC of 0.57 and 95% confidence interval of 0.274 and 0.756 (F(39,78)\u0026thinsp;=\u0026thinsp;2.327, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). A moderate to excellent level of inter-rater reliability was observed for estimates of sensibility using SWMF testing. The average measured ICC for SWMF was 0.83 with a 95% confidence interval from 0.72 to 0.906 (F(39, 78)\u0026thinsp;=\u0026thinsp;6.305, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). TF testing was found to demonstrate a poor to moderate level of inter-rater reliability with an average ICC of 0.511 and a 95% confidence interval from 0.18 and 0.73 (F(39,78)\u0026thinsp;=\u0026thinsp;2.045, p\u0026thinsp;=\u0026thinsp;.004).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab2\" style=\"width: 453px;\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eIntraclass correlation coefficient (ICC) estimates and their 95% confidence intervals were calculated based on logarithmically transformed mean-ratings (k\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth style=\"width: 33px;\" align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth style=\"width: 69px;\" rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eIntraclass\u003c/p\u003e\n\u003cp\u003eCorrelation\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 161.323px;\" colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e95% Confidence Interval\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 132px;\" colspan=\"4\" align=\"left\"\u003e\n\u003cp\u003eF Test with True Value 0\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth style=\"width: 33px;\" align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth style=\"width: 81px;\" align=\"left\"\u003e\n\u003cp\u003eLower Bound\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 80.3229px;\" align=\"left\"\u003e\n\u003cp\u003eUpper Bound\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 41px;\" align=\"left\"\u003e\n\u003cp\u003eValue\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 24px;\" align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003edf\u003c/em\u003e1\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 24px;\" align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003edf\u003c/em\u003e2\u003c/p\u003e\n\u003c/th\u003e\n\u003cth style=\"width: 43px;\" align=\"left\"\u003e\n\u003cp\u003eSig\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 33px;\" align=\"left\"\u003e\n\u003cp\u003eSWMF\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 69px;\" align=\"left\"\u003e\n\u003cp\u003e.834\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 81px;\" align=\"left\"\u003e\n\u003cp\u003e.719\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 80.3229px;\" align=\"left\"\u003e\n\u003cp\u003e.906\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 41px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e6.305\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 24px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 24px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 43px;\" align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 33px;\" align=\"left\"\u003e\n\u003cp\u003eTF\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 69px;\" align=\"left\"\u003e\n\u003cp\u003e.511\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 81px;\" align=\"left\"\u003e\n\u003cp\u003e.176\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 80.3229px;\" align=\"left\"\u003e\n\u003cp\u003e.725\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 41px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.045\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 24px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 24px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 43px;\" align=\"left\"\u003e\n\u003cp\u003e.004\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 33px;\" align=\"left\"\u003e\n\u003cp\u003eVA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 69px;\" align=\"left\"\u003e\n\u003cp\u003e.568\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 81px;\" align=\"left\"\u003e\n\u003cp\u003e.274\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 80.3229px;\" align=\"left\"\u003e\n\u003cp\u003e.756\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 41px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.327\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 24px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 24px;\" align=\"char\" char=\".\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 43px;\" align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e Absolute agreement, 2-way random effects model was used to assess inter-rater reliability between single measures of cutaneous sensibility for measurements of SWMF, TF, and VA.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e SWMF, Semmes-Weinstein Monofilament; TF, 128-Hz Tuning Fork; VA, Vibratus App.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e SWMF, Semmes-Weinstein Monofilament; VA, Vibratus App; SNAP, Sensory Nerve Action Potential; TF, 128-Hz Tuning Fork.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThrough our study, we have demonstrated that smartphone generated vibrations delivered via the Vibratus App may be used to identify age-related (and thereby, other neurological disease-related) skin sensitivity loss, and that the Vibratus App produces a similar level of reliability to traditional methods. Regressive and age-related changes to sensory function were also demonstrated through NCS, which showed a gradual reduction in SNAP amplitude with advanced age. Measurements of sensibility taken with monofilaments and the Vibratus App showed a significant reduction in tactile sensibility with age; however, no difference was observed between young and older adults when tuning fork testing was used. Perceptual threshold estimates obtained by three raters demonstrated a nearly identical level of reliability when the Vibratus App and 128-Hz tuning fork testing were compared. This study has uncovered novel evidence that vibrations generated by smartphones may possibly be used to monitor gradual loss of tactile sensibility with equal reliability to 128-Hz tuning fork testing.\u003c/p\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eReduced Sensation with Age\u003c/h2\u003e \u003cp\u003eAssessments of sensibility are fundamentally psychophysical, meaning they measure the relationship between perceived versus physical stimuli (Johansson and Vallbo \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1979a\u003c/span\u003e). On the basis that no current measure of sensibility optimally combines accessibility with calibrated stimuli and standardized psychophysical procedure, the development of new measures is ongoing (Bril et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Martina et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Azzopardi et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Recent innovation of mobile devices has encouraged their application as remote sensibility monitoring instruments, driven primarily by their ubiquity, but also by their ability to flexibly pair controlled vibration with validated psychophysical procedures (May and Morris \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Jasmin et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The Vibratus App is an early example of a such an alternative to traditional sensibility monitoring devices, combining software-standardized testing procedure with calibrated haptics, but prior to this study, had yet to be validated as a measure of age-related sensory loss.\u003c/p\u003e \u003cp\u003eEffective monitoring devices are characterized by the ability to delineate subtle changes in functional status. The onset of age-related changes to sensibility occurs early in adulthood but progresses rather gradually until old age (\u0026gt;\u0026thinsp;55 years) (Bowden and McNulty \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Age is therefore a useful marker of how sensitivity monitoring devices can discern subtle changes in functional status. Neurological disease or injury such as Diabetic and chemotherapy-induced neuropathy, stroke, and spinal or peripheral nerve damage-induced loss of sensation is far more rapid and profound. Therefore, given age-related loss is detectable using the Vibratus App, we suggest that multiple other neurological patients with sensory loss will also benefit from this novel testing modality.\u003c/p\u003e \u003cp\u003eBetween-group differences in sensibility were most pronounced when thresholds were estimated using SWMF testing, and to a lesser extent VA testing, though no group difference was observed when perceptual thresholds were estimated using the timed on-off TF method. VA detected a higher-than-normal average perception threshold in the older adult group, which is consistent with more than 30 years of evidence indicating that sensation becomes diminished with age (Thornbury and Mistretta \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1981\u003c/span\u003e; Kenshalo \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1986\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, we utilized the complete 20-piece monofilament kit to evaluate tactile sensibility. Previous studies that employed a similar methodology reported a strong association between SWMF testing and age (Thornbury and Mistretta \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1981\u003c/span\u003e), as well as upper-limb motor function (Dellon and Kallman \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1983\u003c/span\u003e; King \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Melchior et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). While less evidence has substantiated vibration perception thresholds as a predictor of upper-limb motor control (Dellon and Kallman \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1983\u003c/span\u003e), similar performance between SWMF and VA testing in this study suggests that detection of altered motor function in the elderly may be a possible application of VA in the future. The high associative cost and procedural skillset required to administer the complete 20-piece monofilament kit act as barriers to its adoption in fast paced settings. These barriers may be circumvented through a smartphone-based approach, such as VA, suggesting that future research should investigate the associative strength of VA and upper-limb motor function.\u003c/p\u003e \u003cp\u003eThe results of our study depicted that SNAP amplitude was significantly reduced in older adults compared to young adults (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Diminished SNAP amplitude was expected by our older adult group, as SNAPs generated from nerve excitation directly correspond to the quantity of functioning nerve fibers, which are lost at a relatively constant and gradual rate following maturation (Adalbert and Coleman \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). We were surprised to find that SNAP amplitude and VA were not significantly associated given that VA detected a significant difference between age groups. However, it's important to note that age-related sensory loss is multifactorial and cannot be solely attributed to nerve fiber attrition. As a tool of exploration and manipulation, the human hand is routinely subjected to mechanical stress of varying intensity on a day-to-day basis, causing compensatory changes to properties of the skin over time, such as dermal thickening or increased rigidity (Daly and Odland \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1979\u003c/span\u003e; Potts et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Baroni et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Venkatesan et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Mechanical properties of the skin are unavoidably factored into sensibility estimation when using hand-held instruments, whereas NCS is a purely physiological evaluation of peripheral nerve function, which may explain why VA showed a sensitivity to age, but not to SNAP amplitude.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eInstrument Reliability\u003c/h2\u003e \u003cp\u003eA secondary purpose of this study was to evaluate the reliability of VA in contrast to two commonly used hand-held instruments. Manual instruments are burdened by human error and poor standardization, and thus, the application of smartphones offers an excellent opportunity to circumvent this form of bias through software standardization. As proof of this concept, we evaluated the inter-rater reliability of testing using SWMF, TF, and VA to determine the clinical utility of software-operated testing procedures in comparison to human operated instruments when the protocol was standardized. Our study confirmed that perception threshold estimation using smartphone technology is a reliable surrogate to traditional sensibility monitoring devices.\u003c/p\u003e \u003cp\u003eTFs are entrenched in fast-paced clinical environments, namely because they are easily accessible, highly durable, and estimate sensibility with acceptable levels of reliability (Lai et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The findings of this study indicate that smartphone-based assessments can achieve higher inter-rater reliability when estimating vibration perception thresholds compared to traditional tuning forks. This technology is more widely available and easily accessible, indicating that smartphones may possibly serve as a feasible and convenient alternative to tuning forks in fast-paced clinical settings, and critically, can be performed by the user at home, which has important ramifications in remote contexts when access to neurological clinics is limited (e.g., global pandemics, remote communities, and even long-duration space flight).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eFuture directions\u003c/h2\u003e \u003cp\u003eGiven the Vibratus smartphone application may provide sensitive and moderately reliable estimates of cutaneous sensitivity across ages, a logical next step toward achieving remote patient monitoring capabilities is to examine criteria of validity and reliability in environments where the examiners are absent (e.g., at-home testing). Additional research should serve to uncover which variables typical of at-home testing, if any, may confound the outcomes of smartphone testing to ensure test-retest reliability is optimized. Examining the influence of various testing procedures, such as variable testing surfaces, phone cases, and phone models should be explored.\u003c/p\u003e \u003cp\u003eThis study has shown that smartphones may be used to evaluate age-related decrements to sensation, though pathological causes of tactile sensory loss should also be investigated as they often present hyposensitivity alongside painful sensations which can significantly reduce quality of life. Future research should aim to recruit and test a cohort of participants with and without diagnoses of peripheral and central neural pathology to determine the diagnostic threshold, sensitivity, and specificity of VA as a screening device. As well, inclusion of professional raters with unique experiences in future research may elucidate the influence of rater experience on diagnosing neurological disease when using a smartphone for examination.\u003c/p\u003e \u003cp\u003eThe innovation of smartphones as instruments of estimating sensory thresholds should be the focus of future research, as it is entirely plausible that the scientific evidence provided here could contribute toward the eventual validation of a remote approach to diagnosing and monitoring neurological disease.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides novel evidence that delivery of smartphone generated vibrations using a software-standardized testing paradigm may provide a sensitive and moderately reliable measure of tactile sensibility. Physician operated testing modalities require frequent visitation to clinic, which acts as a barrier to precise symptom monitoring for patients who live in remote areas or experience accelerated, progressive loss of sensation. Given that the effect of age on sensibility is perhaps the most gradual of all pathologies, the findings of this study provide evidence in support of the theoretical utility of smartphones as tactile sensitivity monitoring instruments, suggesting that at-home sensitivity monitoring may be a possibility soon. Additional research should be dedicated to investigating which variables \u0026ndash; controlled and uncontrolled for in in this study \u0026ndash; may impact the outcomes of smartphone derived estimates of tactile sensitivity.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSWMF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSemmes-Weinstein Monofilament\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e128-Hz Tuning Fork\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVibratus App.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch3\u003eData Availability\u003c/h3\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eO.L. and R.P. conceived of and designed the study, analyzed the data, and created the figures. O.L. wrote the original draft of the manuscript. O.L., H.H., J.B., and A.Y., collected the data. N.O. and R.P. wrote the Vibratus Application software. All authors edited the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdalbert R, Coleman MP. 2013. Review: Axon pathology in age-related neurodegenerative disorders. Neuropathol Appl Neurobiol. 39(2):90\u0026ndash;108.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAzzopardi K, Gatt A, Chockalingam N, Formosa C. 2018. Hidden dangers revealed by misdiagnosed diabetic neuropathy: A comparison of simple clinical tests for the screening of vibration perception threshold at primary care level. Prim Care Diabetes. 12(2):111\u0026ndash;115.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaroni A, Buommino E, De Gregorio V, Ruocco E, Ruocco V, Wolf R. 2012. Structure and function of the epidermis related to barrier properties. 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Validity and Reliability of a Vibration-Based Cell Phone in Detecting Peripheral Neuropathy among Patients with a Risk of Diabetic Foot Ulcer. Int J Low Extrem Wounds.15347346211037411.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohansson RS, Vallbo AB. 1979a. Detection of tactile stimuli. Thresholds of afferent units related to psychophysical thresholds in the human hand. J Physiol. 297(0):405\u0026ndash;422.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohansson RS, Vallbo AB. 1979b. Tactile sensibility in the human hand: relative and absolute densities of four types of mechanoreceptive units in glabrous skin. The Journal of Physiology. 286(1):283\u0026ndash;300.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKelly EJ, Terenghi G, Hazari A, Wiberg M. 2005. Nerve fibre and sensory end organ density in the epidermis and papillary dermis of the human hand. Br J Plast Surg. 58(6):774\u0026ndash;779.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKenshalo DR, Sr. 1986. Somesthetic sensitivity in young and elderly humans. J Gerontol. 41(6):732\u0026ndash;742.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKing PM. 1997. Sensory function assessment. A pilot comparison study of touch pressure threshold with texture and tactile discrimination. J Hand Ther. 10(1):24\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoo TK, Li MY. 2016. A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. J Chiropr Med. 15(2):155\u0026ndash;163.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLai S, Ahmed U, Bollineni A, Lewis R, Ramchandren S. 2014. Diagnostic accuracy of qualitative versus quantitative tuning forks: outcome measure for neuropathy. J Clin Neuromuscul Dis. 15(3):96\u0026ndash;101.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLipsitz LA, Lough M, Niemi J, Travison T, Howlett H, Manor B. 2015. A shoe insole delivering subsensory vibratory noise improves balance and gait in healthy elderly people. Arch Phys Med Rehabil. 96(3):432\u0026ndash;439.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMacKinnon CD. 2018. Sensorimotor anatomy of gait, balance, and falls. Handb Clin Neurol. 159:3\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarcuzzi A, Wainwright AC, Costa DSJ, Wrigley PJ. 2019. Vibration testing: Optimizing methods to improve reliability. Muscle Nerve. 59(2):229\u0026ndash;235.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartina IS, van Koningsveld R, Schmitz PI, van der Meche FG, van Doorn PA. 1998. Measuring vibration threshold with a graduated tuning fork in normal aging and in patients with polyneuropathy. European Inflammatory Neuropathy Cause and Treatment (INCAT) group. J Neurol Neurosurg Psychiatry. 65(5):743\u0026ndash;747.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMay JD, Morris MWJ. 2017. Mobile phone generated vibrations used to detect diabetic peripheral neuropathy. Foot Ankle Surg. 23(4):281\u0026ndash;284.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcGraw KO, Wong SP. 1996. Forming Inferences About Some Intraclass Correlation Coefficients. Psychological Methods. 1(1):30\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMelchior H, Vatine JJ, Weiss PL. 2007. Is there a relationship between light touch-pressure sensation and functional hand ability? Disabil Rehabil. 29(7):567\u0026ndash;575.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOlaleye D, Perkins BA, Bril V. 2001. Evaluation of three screening tests and a risk assessment model for diagnosing peripheral neuropathy in the diabetes clinic. Diabetes Res Clin Pract. 54(2):115\u0026ndash;128.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeters RM, McKeown MD, Carpenter MG, Inglis JT. 2016. Losing touch: age-related changes in plantar skin sensitivity, lower limb cutaneous reflex strength, and postural stability in older adults. J Neurophysiol. 116(4):1848\u0026ndash;1858.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePotts RO, Buras EM, Jr., Chrisman DA, Jr. 1984. Changes with age in the moisture content of human skin. J Invest Dermatol. 82(1):97\u0026ndash;100.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePreston DC, Shapiro BE. 2013. Electromyography and Neuromuscular Disorders: Clinical-Electrophysiologic Correlations Vol. 3rd ed.. London: Saunders.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShrout PE, Fleiss JL. 1979. Intraclass correlations: uses in assessing rater reliability. Psychol Bull. 86(2):420\u0026ndash;428.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSnyder BA, Munter AD, Houston MN, Hoch JM, Hoch MC. 2016. Interrater and intrarater reliability of the semmes-weinstein monofilament 4-2-1 stepping algorithm. Muscle Nerve. 53(6):918\u0026ndash;924.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStephen B. Hulley SRC, Warren S. Browner, Deborah G. Grady, Thomas B. Newman. 2013. Designing Clinical Research. 4 ed. Philadelphia, PA: Lippincott Williams and Wilkins.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStrickland JW, Gozani SN. 2011. Accuracy of in-office nerve conduction studies for median neuropathy: a meta-analysis. J Hand Surg Am. 36(1):52\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTavee J. 2019. Nerve conduction studies: Basic concepts. Handb Clin Neurol. 160:217\u0026ndash;224.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTemlett JA. 2009. An assessment of vibration threshold using a biothesiometer compared to a C128-Hz tuning fork. J Clin Neurosci. 16(11):1435\u0026ndash;1438.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThornbury JM, Mistretta CM. 1981. Tactile sensitivity as a function of age. J Gerontol. 36(1):34\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTong HC, Werner RA, Franzblau A. 2004. Effect of aging on sensory nerve conduction study parameters. Muscle Nerve. 29(5):716\u0026ndash;720.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTremblay F, Wong K, Sanderson R, Cote L. 2003. Tactile spatial acuity in elderly persons: assessment with grating domes and relationship with manual dexterity. Somatosens Mot Res. 20(2):127\u0026ndash;132.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVenkatesan L, Barlow SM, Kieweg D. 2015. Age- and sex-related changes in vibrotactile sensitivity of hand and face in neurotypical adults. Somatosens Mot Res. 32(1):44\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"smartphone, vibrotactile, nerve conduction, aging, psychophysics","lastPublishedDoi":"10.21203/rs.3.rs-3694234/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3694234/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe capacity to perceive tactile input at the fingertips, referred to as tactile sensibility, is known to diminish with age due to regressive changes to mechanoreceptor density and morphology. Sensibility is measured as perceptual responses to stimuli of varying intensity. Contrary to traditional sensibility monitoring instruments, smartphones are uniquely suited for remote assessment and have shown to deliver highly calibrated stimuli along a broad spectrum of intensity, which may improve test reliability. The aim of this study was to evaluate a vibration-emitting smartphone application, the Vibratus App, as a mode of estimating tactile sensory thresholds in the aging adult. The peripheral nerve function of 40 neurologically healthy volunteers (ages 18\u0026ndash;71) was measured using monofilaments, a 128-Hz tuning fork, the Vibratus App, and nerve conduction studies (NCS). Between group differences were analyzed to determine each measurement\u0026rsquo;s sensitivity to age. Spearman correlation coefficients depicted the associative strength between hand-held measurements and sensory nerve action potential (SNAP) amplitude. Inter-rater reliability of traditional instruments and the software-operated smartphone were assessed by intraclass correlation coefficient (ICC\u003csub\u003e2,\u003cem\u003ek\u003c/em\u003e\u003c/sub\u003e). Measurements taken with Vibratus App were sensitive to the age-related decline in tactile sensitivity (t(30.643) = -3.480, p\u0026thinsp;=\u0026thinsp;.002). The inter-rater reliability of smartphone and tuning fork testing was moderate (ICC\u003csub\u003e2,k\u003c/sub\u003e = 0.57 and 0.51, respectively), whereas monofilament testing was good (ICC\u003csub\u003e2,k\u003c/sub\u003e = 0.83). The findings of this study support further investigation of smartphones as remote tactile sensitivity monitoring devices.\u003c/p\u003e","manuscriptTitle":"Healthcare monitoring at your fingertips: validation of a smartphone alternative to routine measures of skin sensibility","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-12-11 14:23:31","doi":"10.21203/rs.3.rs-3694234/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-04-15T07:13:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-02T13:46:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-03-26T01:11:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"c54ab61e-ceec-473e-a627-0b358e0ee173","date":"2024-03-25T09:54:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-03-22T12:03:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"664b9937-87e2-4d52-8957-be2fa0882ee5","date":"2024-03-18T19:22:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"0ed2888a-0f9e-4794-8e55-053fdfbdc485","date":"2024-03-18T08:42:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"535e877a-5db7-4f94-95ae-6f6dfe5e8833_SNPRID","date":"2024-02-21T02:23:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6cdbf285-62f2-4d0e-a07e-d50e6c0ef4dd","date":"2024-02-18T00:03:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-30T09:17:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-21T22:30:06+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2023-12-07T10:38:45+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-12-07T10:02:07+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2023-12-01T20:05:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"255f0132-e3c0-4134-b9ac-b5a01e807e08","owner":[],"postedDate":"December 11th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":27246252,"name":"Biological sciences/Neuroscience/Somatosensory system/Touch receptors"},{"id":27246253,"name":"Biological sciences/Neuroscience/Neural ageing"}],"tags":[],"updatedAt":"2024-08-05T16:01:29+00:00","versionOfRecord":{"articleIdentity":"rs-3694234","link":"https://doi.org/10.1038/s41598-024-68579-1","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-08-01 15:57:14","publishedOnDateReadable":"August 1st, 2024"},"versionCreatedAt":"2023-12-11 14:23:31","video":"","vorDoi":"10.1038/s41598-024-68579-1","vorDoiUrl":"https://doi.org/10.1038/s41598-024-68579-1","workflowStages":[]},"version":"v1","identity":"rs-3694234","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3694234","identity":"rs-3694234","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}