Eye-Tracking Technology: A Promising Tool for Assessing Cognitive Functions in DOC Patients. Results from a Multicenter Clinical Trial

Eye-Tracking Technology: A Promising Tool for Assessing Cognitive Functions in DOC Patients. 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Results from a Multicenter Clinical Trial Żurek Grzegorz, Kryś-Noszczyk Karolina, Kunka Bartosz, Binder Marek This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6580794/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted 13 You are reading this latest preprint version Abstract Background. The proper assessment of cognitive functioning is the subject of numerous scientific studies. Current behavioral methods essentially preclude this assessment in patients with disorders of consciousness (DOC). However, the development of eye-tracking technology and the establishment of contact via this channel have created an opportunity to diagnose the cognitive function (CF) of DOC patients. The purpose of this study was to assess the level of CF of DOC patients for whom vision is the only channel of communication, conducted using eye tracking technology. Methods. The clinical multicenter study involved 31 DOC patients, whose attention, language functions, visual-spatial functions, personal orientation, memory, and abstract thinking were assessed three times (T1-T3) using the Cognitive Functions Assessment (CFA) scale, installed on the C-EYE X system. The data obtained were compared with the CF assessment results obtained with the CRS-R, and then statistically analyzed. Results. There were no statistically significant differences between different time points. Patients scoring higher on the CRS-R receive progressively lower values on the CFA. Statistically significant and moderate correlations were found between the CFA and CRS-R. Conclusions. The results of the study indicate that the diagnosis of CF made with the use of the CFA takes greater account of the diversity of CFs as well as makes their assessment independent of the experience of the examiner and the cooperation of the patient. The use of eye tracking technology, without reducing the quality of the examination, reduces the cost of working with patients by reducing the workload of qualified personnel. The study was registered on the ClinicalTrials.gov clinical trials platform ID NCT05536921. Health sciences/Neurology Health sciences/Diseases/Neurological disorders DOC cognitive functions eye movements eye tracking in neurological diagnosis cognitive profile of non-verbal patients Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background A reliable and detailed neuropsychological diagnosis is of vital importance in the process of patient recovery [1]. At the core of the diagnostic assessment are preserved cognitive functions (CF), because they are essential for information processing. They include ability to recognize people and situations and assign the correct meaning to them [2]. Another key role plays memory, which is important for learning, performing daily tasks, and maintaining social relationships [3]. In turn, learning is the basis of adaptation to changing conditions and situations [4]. A proper adaptation requires the correct assessment and analysis of the information gathered, and applying to both simple and highly complex situations [5,6]. The appropriate level of spared CF is also important for maintaining mental health, due to its support for coping with stress, anxiety, and depression [7]. The assessment of CF is particularly challenging when it must be done for patients with disorders of consciousness (DOC) who are unable to communicate verbally. Due to the high level of misdiagnosis of DOC patients, CF assessment should not be limited to observations of the overt spontaneous behaviors and responses to environmental stimuli [8]. There is no doubt that assessing CF can serve as an indicator of the degree of brain dysfunction and it can predict possible recovery of consciousness [9]. Utilization of the preserved CF offers a basis for cooperation in the rehabilitation process, while at the same time, they are also a conduit for the use of assistive communication technologies (e.g. eye-tracking technique) [10]. For DOC patients, even a basic ability to process information is important both for the quality of the health care and for the assessment of their clinical condition [11], and may affect decisions regarding care and therapy [12,13]. Diagnosing the CF of DOC patients poses special challenges, as it requires going beyond the current pattern of thinking. Many solutions have been proposed so far, including fMRI, PET, and EEG [14], interviews with family and caregivers [15], the therapist's subjective assessment [16], as well as consultations with specialists (i.a. neurologists, psychologists) [17]. A significant segment of assessment is the observation of responses to sensory stimulation [18], that can be effective in assessing baseline CF [19]. Another useful indicator is the assessment of procedural memory [20], spatial working memory [21], motor abilities and visual perception [22], as well as observational scales for DOC patients [23]. Recently eye-trackers have been also used to successfully assess functions such as attention [24], visuospatial function [25,26], language function [27], and memory [28]. Results indicate that the way images are visually processed, as well as discernible gaze patterns, can provide information on working memory processes [29-30], as well as for assessing working memory in patients with aphasia and other communication problems [31,32]. The purpose of this study was to assess the validity of the tool based on eye-tracking technology in the assessment of the profile of CF of DOC patients for whom vision is the only channel of communication. Upon positive validation, this tool can be implemented in clinical practice. Material and Methods 2.1 Participants and Study Design Approval for the research was granted by the Senate Committee on Research Ethics at the Wroclaw University of Health and Sport Sciences (Decision 11/2022), as well as being aligned with the regulations of the 1975 Declaration of Helsinki. The study was registered on the ClinicalTrials.gov clinical trials platform ID NCT05536921. This multicenter study was conducted between July 2022 and February 2023 across five Polish centers (located in Krakow, Sawice, Częstochowa, Wrocław, and Zawiercie) and one German clinical center (University Clinical Hospital Oldenburg). The study enrolled patients with severe brain injury who were undergoing neurorehabilitation. A positive medical qualification, based on meeting the inclusion criteria, was a prerequisite for participation: 1) age ≥ 18 years, 2) legal guardian's consent to participate in the study and access to medical records, 3) a medical diagnosis indicating damage to the central nervous system (CNS), 4) possession of and access to an imaging examination reports (MR or CT) and, as an alternative, of the oculometric test, ophthalmic examination, and hearing assessment, 5) providing a list of medications used by the patient that may affect the results obtained in tests of cognitive function, 6) physician’s approval (e.g., neurologist, neurosurgeon, internist) for participation in the clinical trial, following the review of the study protocol, including the ability to communicate solely thorough eye-gaze interaction (no verbal, sign language, or other forms of communication possible), the absence of dementia and aphasic disorders prior to the event that caused the CNS damage and the patient's current condition, preservation of at least one functioning eyeball (ability to establish cooperation with an eye tracker). The exclusion criteria were: 1) a vision impairment (refractive error) diagnosed before the injury, requiring the use of glasses with lenses of more than ± 3 diopters, 2) the inclusion of pharmacological treatment during the study (observation), which may affect the patient's cognitive functioning – both in terms of an increase in cognitive abilities, as well as their impairment/dementia. A total of 68 patients were recruited for the study (66 in Poland and 2 in Germany). Due to the small number of patients, Oldenburg Hospital / Germany was excluded from the study. The remaining patients underwent medical screening, and 19 were excluded either for not meeting the inclusion criteria or for meeting the exclusion criteria (Fig. 1 ). Of the 47 patients who qualified for further procedure, 31 (66,0%) underwent successful calibration to assess their cognitive function. Time since injury is presented in Table 1 . The aetiology of brain damage in the patients whose results were analyzed varied; the most common causes were stroke (31,4%) and craniocerebral trauma (28,6%). Details of aetiology and demographics are shown in Table 1 . Table 1 Basic demographics and clinical data patients qualified for the clinical study. Category N % Sex Men 16 51,6 Women 15 48,4 Nature of the brain injury Craniocerebral trauma 10 28,6 Stroke 11 31,4 Hypoxia due to cardiovascular causes 6 17,1 Hypoxia due to respiratory causes 4 11,4 Status epilepticus 2 5,7 Metabolic disease 1 2,9 Other 1 2,9 Variable Mean SD Min Q1 Median Q3 Max GCS 6,9 1,9 3,0 6,0 7,0 8,0 11,0 Time since injury [months] 15.7 28.0 0 3.0 6.0 14.0 150.0 To better illustrate the state of consciousness of the patients included in the study, the GCS scale score was included in the description of their clinical condition. It is used in clinical centers in Poland and other European countries to diagnose patients with chronic DOC and those in the acute phase of the disease. The range of variability in the score that a patient can obtain ranges from 3–15 points; the lower the values, the more severe the disturbance of consciousness [ 33 ]. 2.2 Study procedure and data collection methods The level of cognitive functioning of participating patients was assessed using the proprietary Cognitive Functions Assessment (CFA) scale, installed on the C-EYE X device. This scale was created by a team that included i.a. the authors of this paper, consisting of researchers and practitioners in neuropsychology, medicine, nursing, neurorehabilitation, and computer science to assess selected cognitive functions: attention, language functions, visual-spatial functions, personal orientation, memory, and abstract thinking. The CFA scale consists of a set of clinical tests designed touse the meaningful eye movement responses to assess the level of cognitive function. Once it was developed, it was adapted into an eye tracker for patients who do not communicate verbally. The C-Eye X consists of a 19-inch moving screen mounted on a tripod, so it is possible to rotate the screen to place it 60 cm in front of the subject's face. The device does not require the subject's head to be stabilized, as it can compensate for small head movements. The infrared-emitting iluminators are located below the monitor screen and do not interfere with the patient's use of the device. The technical parameters of the C-Eye X are as follows: sampling rate of 33 Hz, accuracy of 0.5 degrees of visual angle, speed threshold of 40 cm/s. Because the C-Eye X is tailored to patients who have one or both eyeballs functioning, either monocular or binocular eye-tracking mode can be used. Each test was preceded by a single-point calibration to determine the location of the subject's eye fixation point (the 2D image from the IR camera is processed on the device's screen). The eye tracker determined the direction of the user's gaze - i.e., the eye fixation point the user was looking at based on the location of the center of the pupil and two infrared reflections (corneal reflections, called “glints”) on the cornea of the eye. Calibration consisted of the patient looking at and keeping his or her gaze on a flashing red dot, surrounded by a white border, which was presented in the center of the screen. The fixation of the patient's gaze lasted no more than 10 seconds and was considered complete by the device when the system detected the correct fixation of the patient's gaze on the calibration dot. If proper gaze fixation did not occur during this time, the system aborted the calibration process, informing the patient and the examiner that the calibration had failed and should be repeated. The system recorded the patient's response if the dwell time on the target area exceeded 1.2 seconds. Theinitial visit (visit 1) was aimed at collecting basic sociodemographic and clinical information about the patient, including establishing information on the results of the state of consciousness upon admission to the rehabilitation centers and the diagnosis made. Visits 2–4 (designated hereafter as measurement points T1, T2, T3) were devoted to assessing the studypatients cognitive functions using CFA; each visit was preceded by the administration of CRS-R. The cognitive function testing protocol consisted of administering CFA three times over 14 days, with intervals of at least 1 day. The examinations at each center were conducted by the neurorehabilitation specialists trained in working withan eye tracker and certified in the administration of CRS-R. The duration of one patient testing session did not exceed 60 minutes and depended on the level of cooperation between the patient and examiner. Each CFA administration was preceded by an assessment of the patient's level of neurocognitive functioning done with CRS-R [ 34 ], now considered an accurate tool for evaluating patients with chronic DOC. CRS-R enables differential diagnosis, prognostic evaluation, and treatment planning based on the assessment of selected perceptual, motor, and cognitive abilities, consisting of six subscales: auditory, visual, motor, and oral-motor/verbal, as well as communication and arousal abilities [ 35 ]. The last visit (no 5) was dedicated to clinical diagnosis performed by the attending physician. The collected patient data was processed using the GoInsights™ platform, which meets all FDA 21 CFR Part 11 and GCP 5.5.3 requirements for electronic data. The safeguards used in GoInsights™ as well as the quality procedures for data collection minimize the risk of incomplete data entry. All data has been recorded in the electronic patient record (eCRF). 2.3 Data analysis The actual study was preceded by the preparation of a Statistical Analysis Plan. The distribution of variables was evaluated using a quantile-quantile (Q-Q) chart and the results of the Shapiro-Wilk test. Depending on the distribution of the data, the mean and standard deviation, median and lower and upper quartiles, as well as maximum and minimum values were calculated. Homogeneity of variance was assessed using Levene's test, assuming a statistical significance level of α < 0.05. The raw CFA and CRS-R scores were normalized to the percentage of the maximum possible total score for each tool (denoted as total CFA score % and total CRS-R score %, respectively). For each subsequent visit (T1-T3), the percentage changes in total and subscale scores compared to T1 are presented. Measurement equivalence of the methods used was assessed using Passing-Bablok regression. All analyses were performed using the R statistical package, ver. 3.6.3 [ 36 ]. Results Table 2 . shows the sums of the patients' scores at each time point, the raw change between T3 and T1, and the sums of the totals for all tests. There were no statistically significant differences in mean values between different time points (T1 vs T2 vs T3) for each test. There was no difference between CFA and CRS-R in the raw change between time points T3 and T1, or in the summary percentage points from all time points (2.42% ± 10.08% vs 0.28% ± 5.38%; p = 0.27), or in the summary percentage points from all time points (T1 - T3; 41.67% ± 22.03% vs 54.32% ± 29.77%; p = 0.18). Table 2 Comparison of the CFA with the CRS-R and the ANOVA-type results of repeated measurements comparison between the CFA and the CRS-R. Time CFA Total % points CRS-R Total % points Mean ± SD Median (Q1 – Q3) T1 40.86% ± 23.56% 37.50% (25.00% − 47.92%) 54.14% ± 29.82% 52.17% (26.09% − 78.26%) T2 40.86% ± 23.11% 33.33% (25.00% − 45.83%) 54.42% ± 30.72% 56.52% (23.91% − 80.43%) T3 43.28% ± 21.29% 37.50% (31.25% − 47.92%) 54.42% ± 29.68% 52.17% (21.74% − 80.43%) Relative % change T3 vs T1 2.42% ± 10.08% 4.17% (-4.17% − 12.50%) 0.28% ± 5.38% 0.00% (-4.35% − 0.00%) Sum (T1-T3) of total % points 41.67% ± 22.03% 31.94% (30.56% − 45.83%) 54.32% ± 29.77% 52.17% (22.46% − 79.71%) Factor F ratio p Test type 3.576 0.0640 Time 1.312 0.2793 Interaction Test x Time 1.064 0.3535 The next step in the analysis was a two-way ANOVA to see if there were statistical differences between the CRS-R total % results and theCFA Total % score (Test type factor) concerning time points (Time factor). We observed a tendency to statistically significant difference between CFA and CRS-R independently of time (p = 0.06) - main effect of Test type, but no statistically significant effects of Time nor interaction between factors of Time and Test type (Table 2 ). To estimate the co-variance level between two measurement diagnostic methods (CFA and CRS-R) used in the study, Passing-Bablok regression was used, which, without taking into account the causal relationship between them, compares the slope of the linear regression with a value of 1 and the intersection of the linear regression with a value of 0. The results of the statistical method used for each time point are shown in Table 3 . Table 3 Results of Passing-Bablok regressions between the CFA and the CRS-R at each time point and for the sum T1-T3. Time-point β 0 ± 95% CI for β 0 β 1 ± 95% CI for β 1 T1 4.77 -14.66–16.67 0.68 0.38–0.96 T2 12.50 -4.17–45.88 0.48 -0.37–0.85 T3 21.49 3.33–52.10 0.44 -0.32–0.800 Sum T1-T3 16.22 -6.03–27.23 0.47 0.14–0.92 β 0 – regression coefficient (intercept), β 1 – regression coefficient (slope), CI – confidence interval For measurement points T1 and T2, there was a significant bias between both tests, increasing with increasing test values (β1 = 0.68 and β1 = 0.48, respectively). In addition, for the sum T1-T3, there was a significant bias between both tests, increasing with increasing test values (β1 = 0.47) (Fig. 2 - Fig. 5 ). This means that patients scoring higher on the CRS-R scale receive progressively lower values on the CFA scale. Statistically significant and moderate correlations were found between the CFA scale and the CRS-R scale at time point T1 and for the sum from time point T1 to time point T3. Discussion The dynamic development of modern technologies, including those used in the medical field, creates entirely new opportunities for diagnosing and collaborating with patients. This is especially important in emergency medicine and those areas where previously used methods of diagnosis and therapy of patients, especially those who until recently were not given a chance to survive and live, are slowly becoming irreplaceable because they accelerate the establishment of accurate diagnosis and decision-making [ 37 , 38 ]. The prerequisite for proper therapeutic management is the establishment of an accurate diagnosis, which for the personnel caring for the patient then becomes the basis for treatment plan, including further therapeutic program [ 39 ]. Making an accurate diagnosis assumes particular importance in the case of patients (regardless of their age) with whom there is no verbal contact, whether they are children, patients of various ages who remain in a DOC state, or those who have suffered permanent brain damage that prevents them from verbal contact. Hence, among other things, comes the constant search for such methods of diagnosis that will be as objective as possible, but will also make the diagnosis independent of the examiner. Procedures used in this way significantly increase the chances of the accuracy of the decisions made, which are influenced, among other things, by such factors as the appropriate high level of staff training and minimizing subjectivity in the assessment of the patient's condition [ 40 ]. Problems with measurement accuracy include the traditionally used GCS scale, which is being replaced in an increasing number of countries around the world by the much more accurate CRS-R. This offers opportunities to reduce misdiagnosisis rate, the percentage of which for brain-injured patients who do not communicate verbally reaches 40% [ 41 ]. However, it should be noted that both the GCS and CRS-R are performed by medical personnel, so it is up to the experience of these personnel to determine whether the limitations of the GCS and CRS-R, which are known from the literature [ 42 – 45 ], will affect the finalscore that the patient as a result of the diagnostic process. The solution proposed in this paper is to assess the patient's cognitive function status with the CFA scale using eye tracking. The results of assessing these functions in patients who do not communicate verbally were compared with another scale that has a similar purpose, but different diagnostic sensitivity and measurement technique, the CRS-R tool. The first point to note is that a comparison of the two methods of assessing CF (cognitive functions) indicates that the differences between them are not significant. This is important information from the point of view of further inference, however, a deeper analysis of the obtained results provides cognitively interesting information. Outliers are more common; this may suggest either the greater sensitivity of the CFA scale, or that a certain level of cognitive function (as indicated by total CRS-R % scores at level 50%) is required to obtain a meaningful CFA result. Below it, the CFA appears to manifest a floor effect. However, there may be another reason, and it may be related to the level of training of the testing staff. When the same patient is evaluated by the same examiner several times, there may be a routine in evaluating the patient with the CRS-R. Assuming, however, that the examiners made every effort to make the results of both tests as accurate as possible, it should be assumed that the assessment of CF with the CFA seems to be more reliable, also taking into account the fact that it is an assessment independent of the examiner. In the case of patients with severe brain damage who do not communicate verbally, for whom vision is the only channel of communication, the high variability of CF scores has already been shown in earlier studies. Some authors suggested that it could be related to both the emotional state of the patient and, for example, meteorological factors [ 28 , 46 ]. In addition, it is evident that the level of consciousness in DOC patients is not constant but may fluctuate, thus affecting the results of a CF test on a given day of diagnosis, or therapy [ 47 ]. In comparing the two methods used, it can also be noted that only at T1 are the results quite similar, while at subsequent iterations of the CF diagnosis (time points T2 and T3), the regression equation curves show that the two methods differ to a greater extent, with the level of CF determined using CFA being at a lower level compared to CRS-R as the results obtained at this diagnosis increase, yet the linear relationship between both tools remains significant. The variability in the slope of the regression curves is also an important issue, this may be an effect of measurement instability; on the one hand, the CRS-R results are more variable (higher SD T1, T2 and T3), but on the other hand, there may be a floor effect in the CFA, as the test was more difficult to perform correctly for a large group of patients (especially those who obtained scores below 50%). This gives rise to the assumption that CFA is a method that more cautiously assesses the level of CF. This is especially true when considering it as a “mechanical” and therefore somewhat depersonalized way of assessing a patient's condition. Shifting the focus from the examiner to the mechanical device poses some challenges, not least in terms of the accuracy of the diagnosis for further use. Evaluating the above-described fact from this perspective, it is possible to take the diagnosis made with the eye tracker as safe from the point of view of patient care, especially in such a severe condition. Until recently, patients with severe brain damage were treated as individuals for whom no specific diagnostic and therapeutic measures were taken. However, successive scientific reports, gradually revealing the world of their inner experience, even despite a low or very low assessment of the state of consciousness made with the GCS or other behavioral scales, show that this is a group of patients to whom much more attention should be paid in clinical measures. Such an approach also meets the expectations directed by medical personnel and patients' caregivers to include the widest possible variety of methods of assessing the patient's clinical condition, which will allow the most objective assessment of the patient's state of health [ 48 , 49 ]. It is worth mentioning here that a separate challenge is to implement into clinical practice an objective method of diagnosing the state of consciousness and cognitive profile of a non-verbal patient in the shortest possible time. This is particularly important in the work of medical personnel in intensive care units (ICUs). The use of high-tech tools based on, among other things, eye tracking, such as the C-EYE X system used in this study, is a good predictor in this context. A particularly important issue, both from the perspective of the patient himself, as well as from the perspective of relatives and staff who care for him, is also the contact that is established with the patient using the eye tracker. This contact facilitates not only communication and diagnosis of the patient's state of consciousness [ 50 ], but also, as it turns out, diagnosis of the patient's level of cognitive functioning. This opens up a whole new field of discussion about the patient, who ceases to be an object of action and becomes a subject for those who deal with him. Thus, he significantly enters the role of a full participant in the treatment/clinical procedure, which is enshrined in the patient's Bill of Rights. Limitations The comparison of methods for diagnosing cognitive function made in this study, in addition to promising predictions for further diagnostic development, however, carries certain limitations. We realize that the size of the study group, although collected in a multicenter study, dictates caution in interpreting the results obtained. We therefore view the present study as a significant starting point for further clinical research in this area. The question of the patients' ability to work with the eye tracker, which may have been relevant to the results obtained in the study, also remains open. To this end, in future studies, the patient will be familiarized with the eye tracker beforehand, which will help in adapting the muscles of his eyeballs to work with the device, and thus may help in a more adequate assessment of the CF condition. Conclusions 1. The eye tracking technology used for the study is an objective method of CF diagnosis, and its results are comparable to the methods used so far, despite being based only on visual interaction it seems to be a suitable screening tool giving an overall picture of the cognitive functioning of a patient who does not communicate verbally. 2. The diagnosis of CF by means of CFA seems to take more account of the variation of these functions in different patients, as well as to a much greater extent than previously used methods, making their assessment independent of the experience of the examiner and the cooperation of the patient. 3. The use of eye movement tracking technology for CF assessment reduces the cost of working with patients by reducing the workload of skilled personnel while maintaining the high accuracy of this assessment. 4. Accurate diagnosis of CF patients who do not communicate verbally, for whom the only channel of communication is eye-gaze interaction, leads to a change in the understanding of their role in the process of diagnosis and therapy. In this approach, the patient ceases to be only an object of the measures taken and becomes a full participant in clinical practice. 5. CFA tool seems to work better for patients with higher CRS-R scores, for those who obtain lower results, the floor effect was observed. Declarations Ethics approval and consent to participate: Approval for the research was granted by the Senate Committee on Research Ethics at the Wroclaw University of Health and Sport Sciences (Decision 11/2022). The study was registered on the ClinicalTrials.gov clinical trials platform ID NCT05536921. Informed consent was obtained from the legal guardians of all subjects involved in the study. Consent for publication: All the authors have approved the manuscript and agree to submit it to a scientific journal. Availability of data and materials: The datasets used and/or analysed during the current study available to qualified researchers from the corresponding author on reasonable request. Competing interests: There are no conflicts of interest to declare. All authors received the compensation provided by the NCBiR grant according to their involvement in the implementation of this study. Each author exercised the utmost care and diligence to ensure that the course of the study was of the highest scientific value. Funding: The research was co-funded by the Polish National Center for Research and Development, grant number POIR.01.01.01-00-2125/20. Authors' contributions: Conception and design of the study (GZ, KKN, BK, MB), acquisition and analysis of data (GZ, KKN, BK, MB), drafting of the manuscript or figures (GZ, KKN, BK, MB), study supervision (GZ, BK, MB) Acknowledgements: We sincerely thank all the physicians, physiotherapists, and nurses for their hard work to achieve our goal and conduct this multicenter study. We thank all caregivers who agreed to allow their dependents to participate in the project and motivated us to work assiduously in improving the quality of life of their dependents and their loved ones. References Diamond A. Executive functions. Annu Rev Psychol. 2013;64:135–68. Anderson JR. Cognitive psychology and its implications. New York: Worth Publishers; 2005. Baddeley A. The episodic buffer: A new component of working memory? Trends Cogn Sci. 2000;4(11):417–23. Mayer RE. Learning and instruction. Upper Saddle River: Pearson Merrill Prentice Hall; 2008. Kahneman D. Thinking, fast and slow. 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Storage of features, conjunctions and objects in visual working memory. J Exp Psychol Hum Percept Perform. 2001;27(1):92–104. Caplan D, Waters GS. Verbal working memory and sentence comprehension. Behav Brain Sci. 1999;22(1):77–126. Baddeley A, Della Sala S. Working memory and executive control. Philos Trans R Soc Lond B Biol Sci. 1996;351(1346):1397–1404. Teasdale G, Jennett B. Assessment of coma and impaired consciousness. A practical scale. Lancet. 1974;2(7872):81–84. Giacino JT, Kalmar K, Whyte J. The JFK Coma Recovery Scale-Revised: measurement characteristics and diagnostic utility. Arch Phys Med Rehabil. 2004;85(12):2020–29. Binder M, Górska U, Wójcik-Krzemień A, Gociewicz K. A validation of the Polish version of the Coma Recovery Scale-Revised (CRSR). Brain Inj. 2017;32(2):242–46. R Core Team. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2013. Bruno RR, Wolff G, Wernly B, Masyuk M, Piayda K, Leaver S, et al. Virtual and augmented reality in critical care medicine: the patient's, clinician's, and researcher's perspective. Crit Care. 2022;26(1):326. O'Grady NP, Alexander E, Alhazzani W, Alshamsi F, Cuellar-Rodriguez J, Jefferson BK, et al. Guidelines for evaluating new fever in adult ICU patients. Crit Care Med. 2023;51(11):1570–86. Stocchetti N, Carbonara M, Citerio G, Ercole A, Skrifvars MB, Smielewski P, et al. Severe traumatic brain injury: targeted management in the ICU. Lancet Neurol. 2017;16(6):452–64. Rajagopalan S, Sarwal A. Neuromonitoring in critically ill patients. Crit Care Med. 2023;51(4):525–42. Monti MM, Laureys S, Owen AM. The vegetative state. BMJ. 2010;341:c3765. Haydel MJ, Preston CA, Mills TJ, Luber S, Blaudeau E, DeBlieux PM. Indications for computed tomography in patients with minor head injury. N Engl J Med. 2000;343(2):100–5. Li Q, Deng L, Huang C, Zhang WY, Zou N, Cao D, et al. A novel scale for assessment of stroke severity at symptom onset. Front Neurol. 2021;11:602839. Forgacs PB, Conte MM, Fridman EA, Voss HU, Victor JD, Schiff ND. A proposed role for routine EEGs in patients with consciousness disorders. Ann Neurol. 2015;77(1):185–86. Andrews K, Murphy L, Munday R, Littlewood C. Misdiagnosis of the vegetative state: retrospective study in a rehabilitation unit. BMJ. 1996;313(7048):13–16. Pundole A, Crawford S. The assessment of language and the emergence from disorders of consciousness. Neuropsychol Rehabil. 2018;28(8):1285–94. Giacino JT, Fins JJ, Laureys S, Schiff ND. Disorders of consciousness after acquired brain injury: the state of the science. Nat Rev Neurol. 2014;10(2):99–114. Seel RT, Sherer M, Whyte J, Katz DI, Giacino JT, Rosenbaum AM, et al. Assessment scales for disorders of consciousness: evidence-based recommendations. Arch Phys Med Rehabil. 2010;91(12):1795–813. Mikkelsen ME, Still M, Anderson BJ, Bienvenu OJ, Brodsky MB, Brummel N, et al. International consensus on long-term impairments after critical illness. Crit Care Med. 2020;48(11):1670–79. Zurek G, Binder M, Kunka B, Kosikowski R, Rodzeń M, Karaś D, et al. Can eye tracking help assess the state of consciousness in non-verbal brain injury patients? J Clin Med. 2024;13(20):6227. Additional Declarations No competing interests reported. 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Grzegorz","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDklEQVRIie2QsWrDMBCGTwjOi8Brgkv1CjKGhkJrP0gXFUFfIItHh4Kz+AGatygUslZgcBeRrimBFr+BAx1c2qGiBLpYTcZA9U06nT793AF4PMePvgCgelcEhyk3ACh3BT1Mqfcr/Oqpbd/z1wxCc9Z15pmLBjDK8xQmDiVeSZWcmKltm2Rxt97E91YZG6Pg/NahVNBE41IikCqhrNuQ5VuBL7NSg6hdCpl/WoUBZQn96lbZ0qb8qXBGkWxLOQK0Cqz19V5FMKQRGCmQ4ZRURqnHhsw/CqOYaxZeBe22z2UWhvUD9E16uShpHRd5ejoJiuEUbffP7AF/78jPUyaGQ4DbNumHf3MoHo/H8+/4Bt8vV6Q5v0GwAAAAAElFTkSuQmCC","orcid":"","institution":"Wroclaw University of Health and Sport Sciences","correspondingAuthor":true,"prefix":"","firstName":"Żurek","middleName":"","lastName":"Grzegorz","suffix":""},{"id":464674213,"identity":"100c951d-5686-4827-81ee-8ee79eb3d23e","order_by":1,"name":"Kryś-Noszczyk Karolina","email":"","orcid":"","institution":"Centrum Opieki i Rehabilitacji","correspondingAuthor":false,"prefix":"","firstName":"Kryś-Noszczyk","middleName":"","lastName":"Karolina","suffix":""},{"id":464674214,"identity":"4a796424-c474-4f81-b6dd-4060a23dd9cb","order_by":2,"name":"Kunka Bartosz","email":"","orcid":"","institution":"AssisTech","correspondingAuthor":false,"prefix":"","firstName":"Kunka","middleName":"","lastName":"Bartosz","suffix":""},{"id":464674215,"identity":"63eb9df8-f58d-4c2f-a9a4-0621df09bdd6","order_by":3,"name":"Binder Marek","email":"","orcid":"","institution":"Jagiellonian University","correspondingAuthor":false,"prefix":"","firstName":"Binder","middleName":"","lastName":"Marek","suffix":""}],"badges":[],"createdAt":"2025-05-02 20:38:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6580794/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6580794/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-27996-6","type":"published","date":"2025-12-19T15:57:43+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":83814558,"identity":"7df16445-889e-4d97-8721-f34f893ace6c","added_by":"auto","created_at":"2025-06-03 07:29:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":121336,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of study enrolment, allocation, and analysis.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6580794/v1/e4ba3ff67d873cae1b8771f4.png"},{"id":83814563,"identity":"0bd9b02f-242f-4a13-b62a-6b80bd773330","added_by":"auto","created_at":"2025-06-03 07:29:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":178414,"visible":true,"origin":"","legend":"\u003cp\u003eThe Passing-Bablok regression between the CFA and the CRS-R scores at the T1 time point (pcorr\u0026lt;0.05).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6580794/v1/e3935accae19af26063a1ab8.png"},{"id":83814562,"identity":"b0f4404b-add2-4178-a654-4c45967896b1","added_by":"auto","created_at":"2025-06-03 07:29:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":168573,"visible":true,"origin":"","legend":"\u003cp\u003eThe Passing-Bablok regression between the CFA and the CRS-R at the T2 time point (pcorr=0.09).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6580794/v1/2b1ae7801bbcf9872b8b787d.png"},{"id":83814565,"identity":"77a146aa-2bb4-4379-979d-9b22b6c84a72","added_by":"auto","created_at":"2025-06-03 07:29:06","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":166779,"visible":true,"origin":"","legend":"\u003cp\u003eThe Passing-Bablok regression between the CFA and the CRS-R at the T3 time point (pcorr=0.09).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6580794/v1/667b0e9ebb4ecada5e68aec4.png"},{"id":83814566,"identity":"36d717b3-88c0-4696-af67-e18682adab40","added_by":"auto","created_at":"2025-06-03 07:29:07","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":174964,"visible":true,"origin":"","legend":"\u003cp\u003eThe Passing-Bablok regression between the CFA and the CRS-R for the sum from T1 – T3 (pcorr\u0026lt;0.05).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6580794/v1/6b2fd88eec3302c69bcc8fb3.png"},{"id":98814056,"identity":"4901ee57-bc6f-40df-93b6-a38778ffd0d8","added_by":"auto","created_at":"2025-12-22 16:10:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1275126,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6580794/v1/fba5ce01-290c-461c-8741-d88a0290647a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Eye-Tracking Technology: A Promising Tool for Assessing Cognitive Functions in DOC Patients. Results from a Multicenter Clinical Trial","fulltext":[{"header":"Background","content":"\u003cp\u003eA reliable and detailed neuropsychological diagnosis is of vital importance in the process of patient recovery [1]. At the core of the diagnostic assessment are preserved cognitive functions (CF), because they are essential for information processing. They include ability to recognize people and situations and assign the correct meaning to them [2]. Another key role plays memory, which is important for learning, performing daily tasks, and maintaining social relationships [3]. In turn, learning is the basis of adaptation to changing conditions and situations [4]. A proper adaptation requires the correct assessment and analysis of the information gathered, and applying to both simple and highly complex situations [5,6]. The appropriate level of spared CF is also important for maintaining mental health, due to its support for coping with stress, anxiety, and depression [7].\u003c/p\u003e\n\u003cp\u003eThe assessment of CF is particularly challenging when it must be done for patients with disorders of consciousness (DOC) who are unable to communicate verbally. Due to the high level of misdiagnosis of DOC patients, CF assessment should not be limited to observations of the overt spontaneous behaviors and responses to environmental stimuli [8]. There is no doubt that assessing CF can serve as an indicator of the degree of brain dysfunction and it can predict possible recovery of consciousness [9]. Utilization of the preserved CF offers a basis for cooperation in the rehabilitation process, while at the same time, they are also a conduit for the use of assistive communication technologies (e.g. eye-tracking technique) [10].\u003c/p\u003e\n\u003cp\u003eFor DOC patients, even a basic ability to process information is important both for the quality of the health care and for the assessment of their clinical condition [11], and may affect decisions regarding care and therapy [12,13]. Diagnosing the CF of DOC patients poses special challenges, as it requires going beyond the current pattern of thinking. Many solutions have been proposed so far, including fMRI, PET, and EEG [14], interviews with family and caregivers [15], the therapist\u0026apos;s subjective assessment [16], as well as consultations with specialists (i.a. neurologists, psychologists) [17]. A significant segment of assessment is the observation of responses to sensory stimulation [18], that can be effective in assessing baseline CF [19]. Another useful indicator is the assessment of procedural memory [20], spatial working memory [21], motor abilities and visual perception [22], as well as observational scales for DOC patients [23].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRecently eye-trackers have been also used to successfully \u0026nbsp;assess functions such as attention [24], visuospatial function [25,26], language function [27], and memory [28]. Results indicate that the way images are visually processed, as well as discernible gaze patterns, can provide information on working memory processes [29-30], as well as for assessing working memory in patients with aphasia and other communication problems [31,32].\u003c/p\u003e\n\u003cp\u003eThe purpose of this study was to assess the validity of the tool based on eye-tracking technology in the assessment of the profile of CF of DOC patients for whom vision is the only channel of communication. Upon positive validation, this tool can be implemented in clinical practice.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003e2.1 Participants and Study Design\u003c/p\u003e \u003cp\u003e Approval for the research was granted by the Senate Committee on Research Ethics at the Wroclaw University of Health and Sport Sciences (Decision 11/2022), as well as being aligned with the regulations of the 1975 Declaration of Helsinki. The study was registered on the ClinicalTrials.gov clinical trials platform ID NCT05536921.\u003c/p\u003e \u003cp\u003eThis multicenter study was conducted between July 2022 and February 2023 across five Polish centers (located in Krakow, Sawice, Częstochowa, Wrocław, and Zawiercie) and one German clinical center (University Clinical Hospital Oldenburg). The study enrolled patients with severe brain injury who were undergoing neurorehabilitation. A positive medical qualification, based on meeting the inclusion criteria, was a prerequisite for participation: 1) age\u0026thinsp;\u0026ge;\u0026thinsp;18 years, 2) legal guardian's consent to participate in the study and access to medical records, 3) a medical diagnosis indicating damage to the central nervous system (CNS), 4) possession of and access to an imaging examination reports (MR or CT) and, as an alternative, of the oculometric test, ophthalmic examination, and hearing assessment, 5) providing a list of medications used by the patient that may affect the results obtained in tests of cognitive function, 6) physician\u0026rsquo;s approval (e.g., neurologist, neurosurgeon, internist) for participation in the clinical trial, following the review of the study protocol, including the ability to communicate solely thorough eye-gaze interaction (no verbal, sign language, or other forms of communication possible), the absence of dementia and aphasic disorders prior to the event that caused the CNS damage and the patient's current condition, preservation of at least one functioning eyeball (ability to establish cooperation with an eye tracker).\u003c/p\u003e \u003cp\u003eThe exclusion criteria were: 1) a vision impairment (refractive error) diagnosed before the injury, requiring the use of glasses with lenses of more than \u0026plusmn;\u0026thinsp;3 diopters, 2) the inclusion of pharmacological treatment during the study (observation), which may affect the patient's cognitive functioning \u0026ndash; both in terms of an increase in cognitive abilities, as well as their impairment/dementia.\u003c/p\u003e \u003cp\u003eA total of 68 patients were recruited for the study (66 in Poland and 2 in Germany). Due to the small number of patients, Oldenburg Hospital / Germany was excluded from the study. The remaining patients underwent medical screening, and 19 were excluded either for not meeting the inclusion criteria or for meeting the exclusion criteria (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Of the 47 patients who qualified for further procedure, 31 (66,0%) underwent successful calibration to assess their cognitive function. Time since injury is presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe aetiology of brain damage in the patients whose results were analyzed varied; the most common causes were stroke (31,4%) and craniocerebral trauma (28,6%). Details of aetiology and demographics are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic demographics and clinical data patients qualified for the clinical study.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e51,6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e48,4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eNature of the brain injury\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eCraniocerebral trauma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e28,6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eStroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e31,4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eHypoxia due to cardiovascular causes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e17,1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eHypoxia due to respiratory causes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e11,4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eStatus epilepticus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e5,7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eMetabolic disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e2,9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e2,9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVariable\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8,0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11,0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime since injury [months]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e150.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo better illustrate the state of consciousness of the patients included in the study, the GCS scale score was included in the description of their clinical condition. It is used in clinical centers in Poland and other European countries to diagnose patients with chronic DOC and those in the acute phase of the disease. The range of variability in the score that a patient can obtain ranges from 3\u0026ndash;15 points; the lower the values, the more severe the disturbance of consciousness [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e2.2 Study procedure and data collection methods\u003c/p\u003e \u003cp\u003eThe level of cognitive functioning of participating patients was assessed using the proprietary Cognitive Functions Assessment (CFA) scale, installed on the C-EYE X device. This scale was created by a team that included i.a. the authors of this paper, consisting of researchers and practitioners in neuropsychology, medicine, nursing, neurorehabilitation, and computer science to assess selected cognitive functions: attention, language functions, visual-spatial functions, personal orientation, memory, and abstract thinking.\u003c/p\u003e \u003cp\u003eThe CFA scale consists of a set of clinical tests designed touse the meaningful eye movement responses to assess the level of cognitive function. Once it was developed, it was adapted into an eye tracker for patients who do not communicate verbally.\u003c/p\u003e \u003cp\u003eThe C-Eye X consists of a 19-inch moving screen mounted on a tripod, so it is possible to rotate the screen to place it 60 cm in front of the subject's face. The device does not require the subject's head to be stabilized, as it can compensate for small head movements. The infrared-emitting iluminators are located below the monitor screen and do not interfere with the patient's use of the device. The technical parameters of the C-Eye X are as follows: sampling rate of 33 Hz, accuracy of 0.5 degrees of visual angle, speed threshold of 40 cm/s. Because the C-Eye X is tailored to patients who have one or both eyeballs functioning, either monocular or binocular eye-tracking mode can be used. Each test was preceded by a single-point calibration to determine the location of the subject's eye fixation point (the 2D image from the IR camera is processed on the device's screen). The eye tracker determined the direction of the user's gaze - i.e., the eye fixation point the user was looking at based on the location of the center of the pupil and two infrared reflections (corneal reflections, called \u0026ldquo;glints\u0026rdquo;) on the cornea of the eye. Calibration consisted of the patient looking at and keeping his or her gaze on a flashing red dot, surrounded by a white border, which was presented in the center of the screen. The fixation of the patient's gaze lasted no more than 10 seconds and was considered complete by the device when the system detected the correct fixation of the patient's gaze on the calibration dot. If proper gaze fixation did not occur during this time, the system aborted the calibration process, informing the patient and the examiner that the calibration had failed and should be repeated.\u003c/p\u003e \u003cp\u003eThe system recorded the patient's response if the dwell time on the target area exceeded 1.2 seconds.\u003c/p\u003e \u003cp\u003eTheinitial visit (visit 1) was aimed at collecting basic sociodemographic and clinical information about the patient, including establishing information on the results of the state of consciousness upon admission to the rehabilitation centers and the diagnosis made. Visits 2\u0026ndash;4 (designated hereafter as measurement points T1, T2, T3) were devoted to assessing the studypatients cognitive functions using CFA; each visit was preceded by the administration of CRS-R. The cognitive function testing protocol consisted of administering CFA three times over 14 days, with intervals of at least 1 day. The examinations at each center were conducted by the neurorehabilitation specialists trained in working withan eye tracker and certified in the administration of CRS-R. The duration of one patient testing session did not exceed 60 minutes and depended on the level of cooperation between the patient and examiner.\u003c/p\u003e \u003cp\u003eEach CFA administration was preceded by an assessment of the patient's level of neurocognitive functioning done with CRS-R [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], now considered an accurate tool for evaluating patients with chronic DOC. CRS-R enables differential diagnosis, prognostic evaluation, and treatment planning based on the assessment of selected perceptual, motor, and cognitive abilities, consisting of six subscales: auditory, visual, motor, and oral-motor/verbal, as well as communication and arousal abilities [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe last visit (no 5) was dedicated to clinical diagnosis performed by the attending physician.\u003c/p\u003e \u003cp\u003eThe collected patient data was processed using the GoInsights\u0026trade; platform, which meets all FDA 21 CFR Part 11 and GCP 5.5.3 requirements for electronic data. The safeguards used in GoInsights\u0026trade; as well as the quality procedures for data collection minimize the risk of incomplete data entry. All data has been recorded in the electronic patient record (eCRF).\u003c/p\u003e \u003cp\u003e2.3 Data analysis\u003c/p\u003e \u003cp\u003eThe actual study was preceded by the preparation of a Statistical Analysis Plan. The distribution of variables was evaluated using a quantile-quantile (Q-Q) chart and the results of the Shapiro-Wilk test. Depending on the distribution of the data, the mean and standard deviation, median and lower and upper quartiles, as well as maximum and minimum values were calculated. Homogeneity of variance was assessed using Levene's test, assuming a statistical significance level of α\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eThe raw CFA and CRS-R scores were normalized to the percentage of the maximum possible total score for each tool (denoted as total CFA score % and total CRS-R score %, respectively).\u003c/p\u003e \u003cp\u003eFor each subsequent visit (T1-T3), the percentage changes in total and subscale scores compared to T1 are presented. Measurement equivalence of the methods used was assessed using Passing-Bablok regression. All analyses were performed using the R statistical package, ver. 3.6.3 [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. shows the sums of the patients' scores at each time point, the raw change between T3 and T1, and the sums of the totals for all tests. There were no statistically significant differences in mean values between different time points (T1 vs T2 vs T3) for each test. There was no difference between CFA and CRS-R in the raw change between time points T3 and T1, or in the summary percentage points from all time points (2.42% \u0026plusmn; 10.08% vs 0.28% \u0026plusmn; 5.38%; p\u0026thinsp;=\u0026thinsp;0.27), or in the summary percentage points from all time points (T1 - T3; 41.67% \u0026plusmn; 22.03% vs 54.32% \u0026plusmn; 29.77%; p\u0026thinsp;=\u0026thinsp;0.18).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of the CFA with the CRS-R and the ANOVA-type results of repeated measurements comparison between the CFA and the CRS-R.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTime\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCFA Total % points\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCRS-R Total % points\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMedian (Q1 \u0026ndash; Q3)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.86% \u0026plusmn; 23.56%\u003c/p\u003e \u003cp\u003e37.50% (25.00% \u0026minus;\u0026thinsp;47.92%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.14% \u0026plusmn; 29.82%\u003c/p\u003e \u003cp\u003e52.17% (26.09% \u0026minus;\u0026thinsp;78.26%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.86% \u0026plusmn; 23.11%\u003c/p\u003e \u003cp\u003e33.33% (25.00% \u0026minus;\u0026thinsp;45.83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.42% \u0026plusmn; 30.72%\u003c/p\u003e \u003cp\u003e56.52% (23.91% \u0026minus;\u0026thinsp;80.43%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.28% \u0026plusmn; 21.29%\u003c/p\u003e \u003cp\u003e37.50% (31.25% \u0026minus;\u0026thinsp;47.92%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.42% \u0026plusmn; 29.68%\u003c/p\u003e \u003cp\u003e52.17% (21.74% \u0026minus;\u0026thinsp;80.43%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRelative % change T3 vs T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.42% \u0026plusmn; 10.08%\u003c/p\u003e \u003cp\u003e4.17% (-4.17% \u0026minus;\u0026thinsp;12.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.28% \u0026plusmn; 5.38%\u003c/p\u003e \u003cp\u003e0.00% (-4.35% \u0026minus;\u0026thinsp;0.00%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSum (T1-T3) of total % points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.67% \u0026plusmn; 22.03% \u003c/p\u003e \u003cp\u003e31.94% (30.56% \u0026minus;\u0026thinsp;45.83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.32% \u0026plusmn; 29.77%\u003c/p\u003e \u003cp\u003e52.17% (22.46% \u0026minus;\u0026thinsp;79.71%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFactor\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eF ratio\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ep\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTest type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.576\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0640\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2793\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInteraction Test x Time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3535\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe next step in the analysis was a two-way ANOVA to see if there were statistical differences between the CRS-R total % results and theCFA Total % score (Test type factor) concerning time points (Time factor). We observed a tendency to statistically significant difference between CFA and CRS-R independently of time (p\u0026thinsp;=\u0026thinsp;0.06) - main effect of Test type, but no statistically significant effects of Time nor interaction between factors of Time and Test type (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo estimate the co-variance level between two measurement diagnostic methods (CFA and CRS-R) used in the study, Passing-Bablok regression was used, which, without taking into account the causal relationship between them, compares the slope of the linear regression with a value of 1 and the intersection of the linear regression with a value of 0. The results of the statistical method used for each time point are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of Passing-Bablok regressions between the CFA and the CRS-R at each time point and for the sum T1-T3.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime-point\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eβ\u003csub\u003e0\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;95% CI for β\u003csub\u003e0\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eβ\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026plusmn;\u0026thinsp;95% CI for β\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-14.66\u0026ndash;16.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.38\u0026ndash;0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-4.17\u0026ndash;45.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.37\u0026ndash;0.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.33\u0026ndash;52.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.32\u0026ndash;0.800\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSum T1-T3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.03\u0026ndash;27.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.14\u0026ndash;0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eβ\u003csub\u003e0\u003c/sub\u003e \u0026ndash; regression coefficient (intercept), β\u003csub\u003e1\u003c/sub\u003e \u0026ndash; regression coefficient (slope), CI \u0026ndash; confidence interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFor measurement points T1 and T2, there was a significant bias between both tests, increasing with increasing test values (β1\u0026thinsp;=\u0026thinsp;0.68 and β1\u0026thinsp;=\u0026thinsp;0.48, respectively). In addition, for the sum T1-T3, there was a significant bias between both tests, increasing with increasing test values (β1\u0026thinsp;=\u0026thinsp;0.47) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e - Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This means that patients scoring higher on the CRS-R scale receive progressively lower values on the CFA scale. Statistically significant and moderate correlations were found between the CFA scale and the CRS-R scale at time point T1 and for the sum from time point T1 to time point T3.\u003c/p\u003e "},{"header":"Discussion","content":"\u003cp\u003eThe dynamic development of modern technologies, including those used in the medical field, creates entirely new opportunities for diagnosing and collaborating with patients. This is especially important in emergency medicine and those areas where previously used methods of diagnosis and therapy of patients, especially those who until recently were not given a chance to survive and live, are slowly becoming irreplaceable because they accelerate the establishment of accurate diagnosis and decision-making [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The prerequisite for proper therapeutic management is the establishment of an accurate diagnosis, which for the personnel caring for the patient then becomes the basis for treatment plan, including further therapeutic program [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Making an accurate diagnosis assumes particular importance in the case of patients (regardless of their age) with whom there is no verbal contact, whether they are children, patients of various ages who remain in a DOC state, or those who have suffered permanent brain damage that prevents them from verbal contact. Hence, among other things, comes the constant search for such methods of diagnosis that will be as objective as possible, but will also make the diagnosis independent of the examiner. Procedures used in this way significantly increase the chances of the accuracy of the decisions made, which are influenced, among other things, by such factors as the appropriate high level of staff training and minimizing subjectivity in the assessment of the patient's condition [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eProblems with measurement accuracy include the traditionally used GCS scale, which is being replaced in an increasing number of countries around the world by the much more accurate CRS-R. This offers opportunities to reduce misdiagnosisis rate, the percentage of which for brain-injured patients who do not communicate verbally reaches 40% [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. However, it should be noted that both the GCS and CRS-R are performed by medical personnel, so it is up to the experience of these personnel to determine whether the limitations of the GCS and CRS-R, which are known from the literature [\u003cspan additionalcitationids=\"CR43 CR44\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], will affect the finalscore that the patient as a result of the diagnostic process.\u003c/p\u003e \u003cp\u003eThe solution proposed in this paper is to assess the patient's cognitive function status with the CFA scale using eye tracking. The results of assessing these functions in patients who do not communicate verbally were compared with another scale that has a similar purpose, but different diagnostic sensitivity and measurement technique, the CRS-R tool.\u003c/p\u003e \u003cp\u003eThe first point to note is that a comparison of the two methods of assessing CF (cognitive functions) indicates that the differences between them are not significant. This is important information from the point of view of further inference, however, a deeper analysis of the obtained results provides cognitively interesting information. Outliers are more common; this may suggest either the greater sensitivity of the CFA scale, or that a certain level of cognitive function (as indicated by total CRS-R % scores at level 50%) is required to obtain a meaningful CFA result. Below it, the CFA appears to manifest a floor effect. However, there may be another reason, and it may be related to the level of training of the testing staff. When the same patient is evaluated by the same examiner several times, there may be a routine in evaluating the patient with the CRS-R. Assuming, however, that the examiners made every effort to make the results of both tests as accurate as possible, it should be assumed that the assessment of CF with the CFA seems to be more reliable, also taking into account the fact that it is an assessment independent of the examiner. In the case of patients with severe brain damage who do not communicate verbally, for whom vision is the only channel of communication, the high variability of CF scores has already been shown in earlier studies. Some authors suggested that it could be related to both the emotional state of the patient and, for example, meteorological factors [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. In addition, it is evident that the level of consciousness in DOC patients is not constant but may fluctuate, thus affecting the results of a CF test on a given day of diagnosis, or therapy [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn comparing the two methods used, it can also be noted that only at T1 are the results quite similar, while at subsequent iterations of the CF diagnosis (time points T2 and T3), the regression equation curves show that the two methods differ to a greater extent, with the level of CF determined using CFA being at a lower level compared to CRS-R as the results obtained at this diagnosis increase, yet the linear relationship between both tools remains significant. The variability in the slope of the regression curves is also an important issue, this may be an effect of measurement instability; on the one hand, the CRS-R results are more variable (higher SD T1, T2 and T3), but on the other hand, there may be a floor effect in the CFA, as the test was more difficult to perform correctly for a large group of patients (especially those who obtained scores below 50%). This gives rise to the assumption that CFA is a method that more cautiously assesses the level of CF. This is especially true when considering it as a \u0026ldquo;mechanical\u0026rdquo; and therefore somewhat depersonalized way of assessing a patient's condition. Shifting the focus from the examiner to the mechanical device poses some challenges, not least in terms of the accuracy of the diagnosis for further use. Evaluating the above-described fact from this perspective, it is possible to take the diagnosis made with the eye tracker as safe from the point of view of patient care, especially in such a severe condition. Until recently, patients with severe brain damage were treated as individuals for whom no specific diagnostic and therapeutic measures were taken. However, successive scientific reports, gradually revealing the world of their inner experience, even despite a low or very low assessment of the state of consciousness made with the GCS or other behavioral scales, show that this is a group of patients to whom much more attention should be paid in clinical measures. Such an approach also meets the expectations directed by medical personnel and patients' caregivers to include the widest possible variety of methods of assessing the patient's clinical condition, which will allow the most objective assessment of the patient's state of health [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. It is worth mentioning here that a separate challenge is to implement into clinical practice an objective method of diagnosing the state of consciousness and cognitive profile of a non-verbal patient in the shortest possible time. This is particularly important in the work of medical personnel in intensive care units (ICUs). The use of high-tech tools based on, among other things, eye tracking, such as the C-EYE X system used in this study, is a good predictor in this context.\u003c/p\u003e \u003cp\u003eA particularly important issue, both from the perspective of the patient himself, as well as from the perspective of relatives and staff who care for him, is also the contact that is established with the patient using the eye tracker. This contact facilitates not only communication and diagnosis of the patient's state of consciousness [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], but also, as it turns out, diagnosis of the patient's level of cognitive functioning. This opens up a whole new field of discussion about the patient, who ceases to be an object of action and becomes a subject for those who deal with him. Thus, he significantly enters the role of a full participant in the treatment/clinical procedure, which is enshrined in the patient's Bill of Rights.\u003c/p\u003e \u003cp\u003eLimitations\u003c/p\u003e \u003cp\u003eThe comparison of methods for diagnosing cognitive function made in this study, in addition to promising predictions for further diagnostic development, however, carries certain limitations. We realize that the size of the study group, although collected in a multicenter study, dictates caution in interpreting the results obtained. We therefore view the present study as a significant starting point for further clinical research in this area. The question of the patients' ability to work with the eye tracker, which may have been relevant to the results obtained in the study, also remains open. To this end, in future studies, the patient will be familiarized with the eye tracker beforehand, which will help in adapting the muscles of his eyeballs to work with the device, and thus may help in a more adequate assessment of the CF condition.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003e1. The eye tracking technology used for the study is an objective method of CF diagnosis, and its results are comparable to the methods used so far, despite being based only on visual interaction it seems to be a suitable screening tool giving an overall picture of the cognitive functioning of a patient who does not communicate verbally.\u003c/p\u003e\n\u003cp\u003e2. The diagnosis of CF by means of CFA seems to take more account of the variation of these functions in different patients, as well as to a much greater extent than previously used methods, making their assessment independent of the experience of the examiner and the cooperation of the patient.\u003cspan\u003e3. The use of eye movement tracking technology for CF assessment reduces the cost of working with patients by reducing the workload of skilled personnel while maintaining the high accuracy of this assessment.\u003cbr\u003e\u003c/span\u003e\u003cspan\u003e4. Accurate diagnosis of CF patients who do not communicate verbally, for whom the only channel of communication is eye-gaze interaction, leads to a change in the understanding of their role in the process of diagnosis and therapy. In this approach, the patient ceases to be only an object of the measures taken and becomes a full participant in clinical practice.\u003cbr\u003e\u003c/span\u003e\u003cspan\u003e5. CFA tool seems to work better for patients with higher CRS-R scores, for those who obtain lower results, the floor effect was observed.\u003cbr\u003e\u003c/span\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate: Approval for the research was granted by the Senate Committee on Research Ethics at the Wroclaw University of Health and Sport Sciences (Decision 11/2022). The study was registered on the ClinicalTrials.gov clinical trials platform ID NCT05536921. Informed consent was obtained from the legal guardians of all subjects involved in the study.\u003c/p\u003e\n\u003cp\u003eConsent for publication: All the authors have approved the manuscript and agree to submit it to a scientific journal.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials: \u0026nbsp;The datasets used and/or analysed during the current study available to qualified researchers from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting interests: There are no conflicts of interest to declare. All authors received the compensation provided by the NCBiR grant according to their involvement in the implementation of this study. Each author exercised the utmost care and diligence to ensure that the course of the study was of the highest scientific value.\u003c/p\u003e\n\u003cp\u003eFunding: The research was co-funded by the Polish National Center for Research and Development, grant number POIR.01.01.01-00-2125/20.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions: Conception and design of the study (GZ, KKN, BK, MB), \u0026nbsp;acquisition and analysis of data (GZ, KKN, BK, MB), drafting of the manuscript or figures (GZ, KKN, BK, MB), study supervision (GZ, BK, MB)\u003c/p\u003e\n\u003cp\u003eAcknowledgements: We sincerely thank all the physicians, physiotherapists, and nurses for their hard work to achieve our goal and conduct this multicenter study. We thank all caregivers who agreed to allow their dependents to participate in the project and motivated us to work assiduously in improving the quality of life of their dependents and their loved ones.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDiamond A. Executive functions. Annu Rev Psychol. 2013;64:135\u0026ndash;68.\u003c/li\u003e\n\u003cli\u003eAnderson JR. Cognitive psychology and its implications. New York: Worth Publishers; 2005.\u003c/li\u003e\n\u003cli\u003eBaddeley A. The episodic buffer: A new component of working memory? Trends Cogn Sci. 2000;4(11):417\u0026ndash;23.\u003c/li\u003e\n\u003cli\u003eMayer RE. Learning and instruction. Upper Saddle River: Pearson Merrill Prentice Hall; 2008.\u003c/li\u003e\n\u003cli\u003eKahneman D. Thinking, fast and slow. London: Penguin Books; 2019.\u003c/li\u003e\n\u003cli\u003ePinker S. The language instinct: How the mind creates language. New York: Harper Perennial; 2007.\u003c/li\u003e\n\u003cli\u003eBeck AT. The past and future of cognitive therapy. J Psychother Pract Res. 1997;6(4):276\u0026ndash;84.\u003c/li\u003e\n\u003cli\u003eSchnakers C, Vanhaudenhuyse A, Giacino J, Ventura M, Boly M, Majerus S, et al. Diagnostic accuracy of the vegetative and minimally conscious state: clinical consensus versus standardized neurobehavioral assessment. BMC Neurol. 2009;9:1\u0026ndash;5.\u003c/li\u003e\n\u003cli\u003eGiacino JT, Ashwal S, Childs N, Cranford R, Jennett B, Katz DI, et al. The minimally conscious state: definition and diagnostic criteria. Neurology. 2002;58(3):349\u0026ndash;53.\u003c/li\u003e\n\u003cli\u003eOwen AM, Coleman MR, Boly M, Davis MH, Laureys S, Pickard JD. Detecting awareness in the vegetative state. Science. 2006;313(5792):1402.\u003c/li\u003e\n\u003cli\u003eLaureys S, Owen AM, Schiff ND. Brain function in coma, vegetative state, and related disorders. 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Science. 2003;302(5646):830\u0026ndash;34.\u003c/li\u003e\n\u003cli\u003eKarlawish JH, Clark CM. Diagnostic evaluation of elderly patients with mild memory problems. Ann Intern Med. 2003;138(5):411\u0026ndash;19.\u003c/li\u003e\n\u003cli\u003eRaglio A, Bellandi D, Baiardi P, Gianotti M, Ubezio MC, Zanacchi E, et al. Effect of active music therapy and individualized listening to music on dementia: a multicenter randomized controlled trial. J Am Geriatr Soc. 2015;63(8):1534\u0026ndash;39.\u003c/li\u003e\n\u003cli\u003eJohnson JK, Gross AL, Pa J, McLaren DG, Park LQ, Manly JJ. Longitudinal change in neuropsychological performance using latent growth models: a study of mild cognitive impairment. Brain Imaging Behav. 2012;6(4):540\u0026ndash;50.\u003c/li\u003e\n\u003cli\u003eVerghese J, Lipton RB, Katz MJ, Hall CB, Derby CA, Kuslansky G, et al. Leisure activities and the risk of dementia in the elderly. N Engl J Med. 2003;348(25):2508\u0026ndash;16.\u003c/li\u003e\n\u003cli\u003eKessels RP, van Zandvoort MJ, Postma A, Kappelle LJ, de Haan EH. The Corsi Block-Tapping Task: standardization and normative data. Appl Neuropsychol. 2000;7(4):252\u0026ndash;58.\u003c/li\u003e\n\u003cli\u003eArnau RC, Green BA, Rosen DH, Gleaves DH, Melancon SM. Are Jungian preferences really categorical? An empirical investigation using taxometric analysis. Pers Individ Dif. 2003;26(2):269\u0026ndash;76.\u003c/li\u003e\n\u003cli\u003eHughes CP, Berg L, Danziger WL, Coben LA, Martin RL. A new clinical scale for the staging of dementia. Br J Psychiatry. 1982;140:566\u0026ndash;72.\u003c/li\u003e\n\u003cli\u003eDuchowski AT. Eye tracking methodology: Theory and practice. Berlin: Springer-Verlag; 2007.\u003c/li\u003e\n\u003cli\u003eKujawa K, Żurek A, Gorączko A, Olejniczak R, Zurek G. Implementing new technologies to improve visual-spatial functions in patients with impaired consciousness. Int J Environ Res Public Health. 2022;19(5).\u003c/li\u003e\n\u003cli\u003eDella Sala S, Gray C, Baddeley A, Allamano N, Wilson L. Pattern span: a tool for unwelding visuo-spatial memory. Neuropsychologia. 1999;37(10):1189\u0026ndash;99.\u003c/li\u003e\n\u003cli\u003eKujawa K, Zurek G, Kwiatkowska A, Olejniczak R, Zurek A. Assessment of language functions in patients with disorders of consciousness using an alternative communication tool. Front Neurol. 2021 Jul 20;12:684362.\u003c/li\u003e\n\u003cli\u003eKujawa K, Zurek A, Goraczko A, Zurek G. Application of high-tech solution for memory assessment in patients with disorders of consciousness. Front Neurol. 2022 Mar 31;13:841095.\u003c/li\u003e\n\u003cli\u003eAivar MP, Hayhoe MM, Chizk CL, Mruczek RE. Spatial memory and saccadic targeting in a natural task. J Vis. 2005;5(3):177\u0026ndash;93.\u003c/li\u003e\n\u003cli\u003eVogel EK, Woodman GF, Luck SJ. Storage of features, conjunctions and objects in visual working memory. 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Brain Inj. 2017;32(2):242\u0026ndash;46.\u003c/li\u003e\n\u003cli\u003eR Core Team. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2013.\u003c/li\u003e\n\u003cli\u003eBruno RR, Wolff G, Wernly B, Masyuk M, Piayda K, Leaver S, et al. Virtual and augmented reality in critical care medicine: the patient\u0026apos;s, clinician\u0026apos;s, and researcher\u0026apos;s perspective. Crit Care. 2022;26(1):326.\u003c/li\u003e\n\u003cli\u003eO\u0026apos;Grady NP, Alexander E, Alhazzani W, Alshamsi F, Cuellar-Rodriguez J, Jefferson BK, et al. Guidelines for evaluating new fever in adult ICU patients. Crit Care Med. 2023;51(11):1570\u0026ndash;86.\u003c/li\u003e\n\u003cli\u003eStocchetti N, Carbonara M, Citerio G, Ercole A, Skrifvars MB, Smielewski P, et al. Severe traumatic brain injury: targeted management in the ICU. Lancet Neurol. 2017;16(6):452\u0026ndash;64.\u003c/li\u003e\n\u003cli\u003eRajagopalan S, Sarwal A. Neuromonitoring in critically ill patients. Crit Care Med. 2023;51(4):525\u0026ndash;42.\u003c/li\u003e\n\u003cli\u003eMonti MM, Laureys S, Owen AM. The vegetative state. BMJ. 2010;341:c3765.\u003c/li\u003e\n\u003cli\u003eHaydel MJ, Preston CA, Mills TJ, Luber S, Blaudeau E, DeBlieux PM. Indications for computed tomography in patients with minor head injury. N Engl J Med. 2000;343(2):100\u0026ndash;5.\u003c/li\u003e\n\u003cli\u003eLi Q, Deng L, Huang C, Zhang WY, Zou N, Cao D, et al. A novel scale for assessment of stroke severity at symptom onset. Front Neurol. 2021;11:602839.\u003c/li\u003e\n\u003cli\u003eForgacs PB, Conte MM, Fridman EA, Voss HU, Victor JD, Schiff ND. A proposed role for routine EEGs in patients with consciousness disorders. Ann Neurol. 2015;77(1):185\u0026ndash;86.\u003c/li\u003e\n\u003cli\u003eAndrews K, Murphy L, Munday R, Littlewood C. Misdiagnosis of the vegetative state: retrospective study in a rehabilitation unit. BMJ. 1996;313(7048):13\u0026ndash;16.\u003c/li\u003e\n\u003cli\u003ePundole A, Crawford S. The assessment of language and the emergence from disorders of consciousness. Neuropsychol Rehabil. 2018;28(8):1285\u0026ndash;94.\u003c/li\u003e\n\u003cli\u003eGiacino JT, Fins JJ, Laureys S, Schiff ND. Disorders of consciousness after acquired brain injury: the state of the science. Nat Rev Neurol. 2014;10(2):99\u0026ndash;114.\u003c/li\u003e\n\u003cli\u003eSeel RT, Sherer M, Whyte J, Katz DI, Giacino JT, Rosenbaum AM, et al. Assessment scales for disorders of consciousness: evidence-based recommendations. Arch Phys Med Rehabil. 2010;91(12):1795\u0026ndash;813.\u003c/li\u003e\n\u003cli\u003eMikkelsen ME, Still M, Anderson BJ, Bienvenu OJ, Brodsky MB, Brummel N, et al. International consensus on long-term impairments after critical illness. Crit Care Med. 2020;48(11):1670\u0026ndash;79.\u003c/li\u003e\n\u003cli\u003eZurek G, Binder M, Kunka B, Kosikowski R, Rodzeń M, Karaś D, et al. Can eye tracking help assess the state of consciousness in non-verbal brain injury patients? J Clin Med. 2024;13(20):6227.\u003c/li\u003e\n\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":"DOC, cognitive functions, eye movements, eye tracking in neurological diagnosis, cognitive profile of non-verbal patients","lastPublishedDoi":"10.21203/rs.3.rs-6580794/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6580794/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground. The proper assessment of cognitive functioning is the subject of numerous scientific studies. Current behavioral methods essentially preclude this assessment in patients with disorders of consciousness (DOC). However, the development of eye-tracking technology and the establishment of contact via this channel have created an opportunity to diagnose the cognitive function (CF) of DOC patients. The purpose of this study was to assess the level of CF of DOC patients for whom vision is the only channel of communication, conducted using eye tracking technology.\u003c/p\u003e \u003cp\u003eMethods. The clinical multicenter study involved 31 DOC patients, whose attention, language functions, visual-spatial functions, personal orientation, memory, and abstract thinking were assessed three times (T1-T3) using the Cognitive Functions Assessment (CFA) scale, installed on the C-EYE X system. The data obtained were compared with the CF assessment results obtained with the CRS-R, and then statistically analyzed.\u003c/p\u003e \u003cp\u003eResults. There were no statistically significant differences between different time points. Patients scoring higher on the CRS-R receive progressively lower values on the CFA. Statistically significant and moderate correlations were found between the CFA and CRS-R.\u003c/p\u003e \u003cp\u003eConclusions. The results of the study indicate that the diagnosis of CF made with the use of the CFA takes greater account of the diversity of CFs as well as makes their assessment independent of the experience of the examiner and the cooperation of the patient. The use of eye tracking technology, without reducing the quality of the examination, reduces the cost of working with patients by reducing the workload of qualified personnel.\u003c/p\u003e \u003cp\u003eThe study was registered on the ClinicalTrials.gov clinical trials platform ID NCT05536921.\u003c/p\u003e","manuscriptTitle":"Eye-Tracking Technology: A Promising Tool for Assessing Cognitive Functions in DOC Patients. 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