Comparing the effects of treadmill training versus Baduanjin on prefrontal cortical activity during dual-task walking in Parkinson’s disease: Study protocol using a fNIRS device

Comparing the effects of treadmill training versus Baduanjin on prefrontal cortical activity during dual-task walking in Parkinson’s disease: Study protocol using a fNIRS device | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Study protocol Comparing the effects of treadmill training versus Baduanjin on prefrontal cortical activity during dual-task walking in Parkinson’s disease: Study protocol using a fNIRS device Juan Hui, Zhenlan Li, Shanshan Xu, Junwu Yu, Min Tang, Lifeng Zhou This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4976473/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Patients with Parkinson’s disease (PD) have shown impaired gait rhythmicity and increased prefrontal activation during complex tasks, presumably to compensate for decreased automaticity. Exercise can reduce cortical excitability and enhance automaticity, thereby improving walking function. However, the effectiveness of treadmill training and Baduanjin on prefrontal activity has received little attention when patients with PD walk under different dual-task conditions. This randomized control trial (RCT) will investigate the comparative effects of treadmill training and Baduanjin on prefrontal activation and gait function during both single and dual tasks in PD. Methods: This RCT will be designed as a single-center, three-arm, single-blind study. One hundred and forty-four participants will be allocated into treadmill training, Baduanjin, or waitlist control groups. Participants in both the treadmill training and Baduanjin groups will receive 45 min of specific exercise three times weekly for 12 weeks. Participants in the control groups will maintain routine care and lifestyle. The primary and secondary outcomes will be assessed at baseline, after a 12-week intervention, and at the end of a12-week follow-up. The primary outcomes will be prefrontal activation (oxygenated hemoglobin concentration, HbO 2 ) measured by functional near-infrared spectroscopy (fNIRS), and gait parameters (gait speed, stride length, double-phase time, stride variability, and step width) assessed by an electronic walkway with pressure sensors. The secondary outcomes will be motor function, balance, mobility, and quality of life. Discussion: This study will determine whether treadmill training or Baduanjin is more effective in reducing prefrontal activation and improving gait function. If the findings are consistent with our expectations, they may help clinicians and physical therapists to manage gait impairments in patients with PD and to select targeted interventions for them. Trial registration http//www.chictr.org.cn. Trial number ChiCTR2300075048. Registered on 23 Aug 2023. Treadmill Baduanjin prefrontal activity dual-task Parkinson’s disease Figures Figure 1 Introduction The simultaneous performance of motor and cognitive tasks is required for most daily activities and demands continuous integration of neural processes as well as the practice of so called “dual tasks” (DTs)[ 1 ]. Adding an attention-focused cognitive task to mobility tasks has been shown to amplify gait variability in individuals with neurologic disorders, such as stroke, Parkinson’s disease, and multiple sclerosis[ 2 ]. Compared to healthy elderly individuals, patients with PD present with deficits in the cognitive domain and sensory-motor processing, in particular when walking under challenging conditions (such as talking on the phone while walking), and they have significantly increased the swing and stride time variability [ 2 – 4 ]. Previous research has indicated that patients with PD apply higher-level cognitive resources to compensate for motor deficits, in particular in the prefrontal lobe [ 5 ]. The ability to walk while performing cognitive tasks depends on executive functions with projections derived from the prefrontal cortex (PFC)[ 6 , 7 ]. At present, the activation of the PFC can be detected by functional near-infrared spectroscopy (fNIRS). This non-invasive technique has become an important research tool to explore neural activity of locomotion in aging and special populations (patients with neurological or psychiatric conditions) or for a variety of motor tasks, such as walking under different conditions [ 8 , 9 ]. fNIRS mainly measures the concentrations of oxygenated (HbO 2 ) and deoxygenated (HHb) hemoglobin in the PFC to quantify task-related changes in brain activation[ 10 ]. Many studies found that the specific nature of complex walking plays a vital role in determining the frontal lobe involvement in gait. Further, higher PFC activation could be observed regardless of the type of accompanying task performed during ambulation. The mean HbO 2 concentrations of the PFC in PD during DT walking (walking while serially subtracting or reciting digit spans) were significantly higher than during rest [ 6 ]. There was also a significant increase in prefrontal activity when crossing an obstacle but only a slight increase in activation during DT walking in contrast to usual walking. The HbO 2 levels were higher in patients with PD than in healthy elderly people during usual walking [ 7 ]. The reason may be that patients with PD recruit more brain networks, in particular cognitive prefrontal areas, as a form of compensation due to decreased gait automaticity even while performing simple tasks [ 11 ]. Interventions that ameliorate components of frontal-striatal circuits may have a direct effect on a patient's ability to walk in complex situations and reduce the risk of falls [ 12 ]. Several studies showed that treadmill training can improve gait performance and lower prefrontal activation during a simple walking task [ 5 , 13 ]. Evidence for assessing the impact of DT training on prefrontal activation using fNIRS is growing in PD studies. When compared to over-ground walking, patients with PD showed a significant decrease in prefrontal activity and a walking pattern with increased stability during treadmill walking [ 5 ]. After a treadmill training program, patients with PD demonstrated significantly improved cognitive function and mobility as well as modified cerebellar activity [ 14 ]. Adding a cognitive training component to a treadmill exercise program obviously altered the effects of training on the magnitude and lateralization of prefrontal activation in patients with PD [ 12 ]. An intensive exercise-based training program might produce positive effects in patients with PD by decreasing prefrontal activity and improving gait performance during usual walking [ 15 ]. Qigong is traditional Chinese exercise, which is widely used to treat various chronic diseases and improve physical health [ 16 ]. Baduanjin is one type of Qigong, which likely originated in ancient China over a 1000 years ago; it is also known as the “eight section brocades”[ 17 ]. Baduanjin exercise emphasizes meditative movements, breathing patterns, and mental regulation. Previous studies proved that Baduanjin can improve balance and reduce the risk of falls among patients with PD [ 16 ]. Furthermore, Baduanjin can promote the recovery of walking and in particular improve the gait speed, stride length, and cadence of patients with PD [ 18 ]. However, currently, no study has explored the effects of Baduanjin on PFC activity in patients with PD. Further, few studies compared the effects of treadmill training and Baduanjin on changes in the activation of the PFC in patients with PD performing different types of dual-tasking. Thus, the changes in activity patterns of prefrontal neurons caused by both types of exercise remain to be further investigated. The aim of our study protocol is to assess (1) the effects of 12 weeks of treadmill training and Baduanjin exercise on the prefrontal activity and gait performance during single-task and three types of DT walking (obstacle negotiation, backward digital span, and serial-3 subtraction); (2) the relationship between prefrontal activation and gait performance; and (3) comparative effects of the two exercises on motor function, balance, mobility, and quality of life. We hypothesize that both exercises will reduce prefrontal activation during single-task and DT walking, and the better the gait performance, the lower the prefrontal activation of the prefrontal cortex, Baduanjin exercise may reduce activation more than treadmill training. Both types of exercise will be beneficial for motor function, balance, mobility, and quality of life of patients with PD. Methods Study design overview This study is designed as a randomized, single-blind, single-center trial and will be conducted at the local rehabilitation hospital. This clinical trial was approved by the Ethics Committee of Ningbo College of Health Sciences (LLSC2023017) and registered in the China Clinical Trial Registry (ChiCTR2300075048). The design of this interventional study follows the Standard Protocol Items: Recommended for Interventional Trials (SPIRIT) 2013 statement (see Additional file1) [ 19 ]. Participants will be randomly allocated into two intervention groups and one waitlist control group for 12 weeks. An informed consent will be signed prior to joining the study. Assessments will be conducted at baseline, after 12 weeks of intervention, and after a 12-week follow-up and will include gait parameters, changes in the HbO 2 concentration in the PFC, and other motor function parameters. The schedule of observations is illustrated in Table 1 . Participants Recruitment We will enroll participants from the Neurology Department of the local rehabilitation hospital and local communities by means of printed leaflets, online PD patient groups, and popular science lectures by the hospital. To minimize potential expectation bias and confirm eligibility, a research assistant will contact those referred by a clinician and follow up with interested participants by phone. Participants will be informed that they will be randomly allocated to two experimental groups (treadmill training and Baduanjin) and a waitlist control group. Figure 1 illustrates the recruitment strategy, intervention procedure, and time points of the three assessments. Inclusion criteria (1) Age 60–75 years old; (2) diagnosed with idiopathic PD according to the UK Brain Bank criteria[ 20 ]; (3) Hoehn and Yahr (H&Y) stage I–III; (4) Mini-Mental State Examination score ≥ 24; and (5) ability to walk at least 5 min independently (walking aids are permitted). Exclusion criteria (1) Unstable medical conditions, including cardiopulmonary disease, cancer, or orthopedic problems affecting performance; (2) severe cognitive, visual, or auditory impairment; (3) any co-morbidity of the motor system that may restrict the gait; and (4) other ongoing forms of intensive training. Sample size In the absence of preliminary data on a meaningful change in prefrontal activation for DT walking, the effect size will be calculated by the gait speed. A clinically important difference in the gait speed among people with PD under the on-medication condition ranged from 0.05 m/s to 0.22 m/s by a distribution-based analysis [ 21 ]. We set a statistical power of 0.8 and two-tailed α level of 0.05 in repeated-measures multivariate analysis of variance (MANOVA). Based on the data of a previous study, we assumed that there would be a difference of 15% between the Treadmill training group and Baduanjin group in favor of DT gait[ 22 ]. Considering a loss to follow-up, with an estimated drop-out rate of 5%, we will recruit 48 participants per group (a total of 144 patients). Randomization, allocation, and blinding Eligible participants will be randomized to one of the groups with an allocation of 1:1:1 ratio through an independent statistician-implemented, computerized block randomization. The treating physiotherapist will be notified of the results of the group allocation by e-mail to ensure concealed allocation. All study assessors who collect outcome measures will be blinded to the study hypotheses and group assignments. In addition, participants will be instructed not to reveal their training regime at any time to prevent unbinding. Both therapists and participants will be informed that both training methods may effectively improve DT gait performance to control for expectancy effects. Study interventions Participants in the two intervention groups will complete an exercise program during the “on” medication phase that will be supervised by a physiotherapist. The program will consist of a 5-min warm-up, 30-min treadmill training or Baduanjin, and 10-min cool-down. The training period will encompass 12 consecutive weeks with a total of 36 sessions, including three weekly sessions lasing 45 min each. The intensity will be monitored by measuring the heart rate (Polar Team2; Polar Electro Finland) and perceived exertion (PRE). The calculation of the heart rate will adopt 60–70% of the HR max , determined by the formula HR max = 208 − (0.7 × age) [ 23 ] or reaching a fatigue limit at the RPE of 12 [ 24 ]. Attendance will be recorded for each training session. An assistant will inquire about the reason of absence by telephone for those participants with low attendance, and encourage them to persist in exercising. Moreover, participants will write an exercise log throughout the study, the content will involve in the self-report training effects, training duration per session and fall events. a) Treadmill training Participants will perform gait training on a treadmill (GaitTrainer System 2-Biodex Medical Systems, NY, USA). A safety jacket will be attached to an overhead suspension system, without providing weight support. At the first training session, participants will be familiarized with the equipment and will receive a gait speed measurement over-ground by 10 m walking. With the progression of training, treadmill speed will be elevated, and the duration of intervals of training will be reduced. During the first 2 weeks of the program, the treadmill speed will be set at 80% of the usual gait speed. The 30-min training sessions will be conducted in three sessions with 5-min breaks at the intervals. During the third and fourth weeks, the treadmill speed will be increased to 90% of the usual speed, and the training session will be completed in two 15-min sessions with a 5-min break between the sessions. During the latter 8 weeks, the treadmill speed will be increased to its usual speed and the training will be continuous for 30 min. Participants will conduct 5-min active stretching exercises to warm up. Ten min of relaxation exercise will be performed on the ground at the end of treadmill training. Training scheme is shown in Additional file 1. The participants will be encouraged to maintain a postural alignment and use the frontal support of the treadmill to minimize physical exertion[ 25 ]. Cognitive components of the DT will be integrated into the gait training after 4 weeks of training, including 1) walking while phoning; 2) walking while performing a backward digit span; and 3) walking while carrying a bag filled with food. b) Baduanjin exercise Participants will be instructed to perform Baduanjin, whose characteristics include symmetrical physical postures and dynamic movements, postural control, meditation, and rhythmic breathing regulation [ 26 ]. It consists of eight different movements, and each movement is repeated six times. The Baduanjin training program is shown in Additional file 1. During the initial 2–4 weeks, participants will learn to adjust their breathing and coordinate it with the prescribed movements. The whole set of Baduanjin movements usually takes 12–15 min to complete at a regular pace[ 18 ]. During the later 5–12 weeks, a concurrent cognitive task will be added to the exercise. The purpose is to strengthen continuous attentional processing demands while performing another task under varying conditions. Participants will practice Baduanjin while performing the following tasks: 1) stating the form of each movement; 2) counting a 4-digit number backwards; and 3) reciting Chinese poems. c) The waitlist control group will continue to maintain routine care and lifestyle and will not perform any form of intensive training. A research assistant will follow up their health status twice a month by phone or WeChat. They will participate in either the treadmill training or Baduanjin exercise after the 12-week follow-up assessment. Outcome measures The participants’ demographic characteristics will be collected before the study, including age, gender, duration of disease, weight, height, educational level, health status, medication dosage, exercise habits, and the numbers of falls within 6 months. All assessments will be performed in the practical, self-reported on-medication status, at about the same time of day. Participants will be required to walk under four conditions on a 4.6 m electronic walkway, while wearing a portable fNIRS device. The walking conditions will be: 1) walking at a usual speed; 2) walking while conducting a backward digital span; 3) walking while performing a serial-3 subtraction; and 4) walking while negotiating two obstacles positioned on the walkway at specific locations. The obstacles will be set up at a half knee height🞨60 cm and width 🞨3 cm depth [ 27 ]. To avoid a learning effect, the order of each task will be changed randomly. Participants will walk three consecutive loops on the walkway to obtain valid trials and to minimize within-individual variability, and the interval of each task will include 1-min rest [ 28 ]. All experimental data will be collected by the same trained assessor to ensure reproducibility. Primary Outcomes measures Change of prefrontal activity Prefrontal activity will be measured by monitoring the change in HbO 2 concentration of the anterior PFC using a multi-channel, continuous wave, fNIRS instrument (NIRScout; NIRx Medical Technologies LLC; Minneapolis, MN, USA) during task performance. The space between the emitter and detector will be maintained at 3 cm. HbO 2 concentration is sensitive to walking-related changes in cortical activity and has been used as a primary outcome to measure prefrontal activity [ 29 ]. The concentration of HbO 2 will be exported to MATLAB (MathWorks; Natick, MA, United States) for further data analysis. A bandpass filter with a cutoff frequency of 0.01 Hz will be used to remove low-frequency noise, such as head movements, and a low-pass filter with a cutoff frequency of 0.15 Hz will be utilized to reduce high-frequency noise and cardiovascular artifacts [ 30 ]. The concentration changes of HbO 2 in the targeted PFC will be calculated from the changes in detected light intensity according to the modified Beer-Lambert Law [ 31 ]. For each experimental condition, the average concentration of HbO 2 during task performance and 10 s baseline (i.e., the value during the 10 s quiet standing prior to the task) will be used to determine relative changes in HbO 2 concentration. We will analyze the average of the left and right PFC HbO 2 concentrations [ 4 , 5 ]. Gait parameters We will select the gait speed (m/s), stride length (m), double-phase time (%), stride variability (%), and step width (cm). The gait parameters will be measured using an electronic walkway with pressure sensors embedded in a 4.6 m carpet. Data processing and storing will be performed using the PKMAS software (PKMAS walkway, ProtoKinetics, Havertown, PA, USA) connected to a personal computer. Prior to performing each task, the participants will be required to stand quietly for 20 s and refrain from talking or moving their heads. The instruction “start” will be given after these 20 s. Secondary outcome measures Disease severity Disease severity will be determined using the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS). The MDS-UPDRS is structured in four parts, namely, Non-motor Experiences of Daily Living (I); Motor Experiences of Daily Living (II); Motor Examination (III); and Motor Complications (IV). Each item is scored on a 5-point scale (0–4 points), with a minimum score of 0 indicating normal and a maximum score of 4 indicating a severe impairment in performing activities. Thus, higher scores reflect worse functioning. The H&Y stage in the MDS-UPDRS includes 5 stages, with the early, middle, and late stages of PD corresponding to stage I-II, stage III-IV, and stage V, respectively [ 32 ]. Balance function Balance function will be measured by the Mini-Balance Evaluation Systems Test (Mini-BESTest). The scale consists of 14 items from four different balance control systems, including anticipatory postural adjustments, reactive postural control, sensory orientation, and dynamic gait. Each item is assessed from 0 to 2 points, and the total score ranges from 0 to 28, with a higher score representing better balance function [ 33 ]. The Time-Up and Go Test (TUG) TUG is widely used in clinical research to test balance, mobility, and fall risk. It is quick and easy to conduct and requires a participant to stand up from a chair, walk 3 m, turn 180 ° , walk back to the chair, and sit down. The outcome is the total duration, which is usually recorded with a stopwatch [ 34 ]. Health related quality of life (HRQoL) HROoL will be used to reflect the progression of PD and will be assessed using the 39-item Parkinson’s Disease Questionnaire (PDQ-39). It has eight domains: mobility, activities of daily living, emotional well-being, stigma, social support, cognition, communication, and bodily discomfort. A summary index of the eight domain scores ranges from 0 to 100, with higher scores indicating more frequent self-perceived difficulties in HRQoL [ 35 ]. Data management and monitoring To ensure the integrity and security of data, the project and data management and monitoring will be supervised by the independent Scientific Research Management Platform of the Ningbo Rehabilitation Center. The paper-based personal details and data involved will be confidential and stored in locked file cabinets in restricted-access areas. Output files from computer-based tasks will be encrypted and stored on research computers, and accessible only to authorized staff involved in the project. Statistical analysis Statistical analysis will be carried out using IBM SPSS Statistics 24.0. Group comparisons on baseline demographic descriptors and primary and secondary outcome measures will be performed utilizing analysis of variance (ANOVA) for continuous variables and the chi-square independent test for categorical variables. Primary and secondary intervention effects for between/within-group differences will be analyzed by mixed repeated-measures ANOVA. The H&Y stage and MMSE score will be included as covariates since these variables will probably differ significantly among the groups. Bonferroni’s post hoc test will be used to compare results when the main effects are significant. Paired t -test will be adopted to test within-group changes from baseline to post 12-week follow-up. HbO 2 differences among the groups and tasks will be measured using a linear regression, including the interactions between groups and tasks. Pearson correlation coefficients will be adopted to analyze the association between gait performance and PFC activation with tasks in the three groups [ 7 ]. We will employ repeated measures ANOVA to analyze differences among conditions with regards to HbO 2 levels and gait parameters. Post-hoc analysis will be used to assess for differences between the tasks in both gait and HbO 2 . Data normality will be tested utilizing the Kolmogorov–Smirnov test. If the data are not normally distributed, the Mann-Whitney U test will be applied to analyze between-group differences under different tasks following training (baseline minus post-intervention), and the Wilcoxon signed-ranks test will be utilized to analyze within-group differences. Significant differences will be set at P values less than 0.05. Missing data and lost to follow-up data will be analyzed based on the intention-to-treat (ITT) principle, and all data obtained from the participants will be included in the analysis. Discussion Dual-task theories have indicated that deficits in motor performance result from spatial and temporal interferences in information processing, contributing to a compromised selection and execution of the motor response [ 36 ]. The loss of automaticity in PD causes difficulties in gait control and might augment the reliance on cognitive resources to optimize motor control. This restricts the utilization of cognitive resources in PD to perform another task while walking [ 37 ]. Recent studies have indicated that adding aerobic exercise to non-motor cognitive training could enhance the cognitive capacity in frontal regions and thereby release more capacity to support motor control [ 38 , 39 ]. In addition, cortical activation of the PFC or dorsolateral PFC decreased after an exercise intervention, and the step speed and length significantly improved [ 12 , 15 ]. However, most studies have not explicitly investigated the differential effect of PFC activation on various DT gaits and have not elucidated which exercise mode is conducive to reduce cortical activation and facilitate the recovery of walking ability in patients with PD[ 12 – 14 ]. Therefore, we have designed a comparative randomized controlled trial to assess the impact of two training methods on PFC activity, particularly the effect of PFC activation on gait improvement among DT in patients with PD. In this study, we have selected treadmill training, because an instrumented training approach has been shown to significantly improve single task gait performance and gait pattern in patients with PD [ 40 ]. Baduanjin qigong has become a popular exercise program among the elderly in China and plays an important role in promoting health and improving the quality of life. In Baduanjin, the forms and movements are slow and rhythmic, and there is a focus on posture, breathing, and inner balance. This strengthens the function of the vegetative nervous system and intensifies the whole body state [ 41 ]. Baduanjin benefits patients with PD by improving their gait, balance, concentration, and coordination [ 42 ]. In the two experiment groups, we will integrate a cognitive component into training in order to increase the cognitive reaction speed when walking under DT conditions. We will add cognitive components to the Baduanjin exercise, such as participants needing to memorize and retell the name of each pattern when practicing. This may improve individuals’ ability to process cognitive resources concurrently with conducting another motor task. Participants in the treadmill training group will walk while talking on the phone, counting down numbers, and carrying a bag full of food. Perhaps the ability to speed up one’s cognitive response will promote a walking speed improvement in more challenging DTs, enabling their better performance. Some research has shown that exercise may influence PFC recruitment simultaneously or separately in two ways: (1) In order to produce the same (or higher) level of usual walking performance, the efficiency of neural control can increase to reduce activation, and (2) the PFC generates the highest activation capacity, that is, extends capacity[ 12 , 43 , 44 ]. Moreover, exercise can facilitate neuroplasticity in aging healthy individuals and might benefit the recovery of motor automaticity in individuals with PD. This improvement of the automaticity of motion could free cognitive resources and perhaps contribute to improved walking performance [ 45 , 46 ]. This protocol still has some limitations. First, it is difficult to achieve a double-blind status for participants and investigators to achieve a doubled-blind status because exercise intervention is extensively to the participants. Second, participants are limited to those with mild to moderate PD, whether the results are generalizable to advanced PD remains unclear. Third, intervention duration and follow-up are relatively short, so long-term training effects on PFC activity and various functions in PD may not be observed. Future investigations will focus on the long-term therapeutic effects of treadmill training and Baduanjin. We will try to modify the existing protocol so that it can be used in advanced PD. The findings will help clinicians and physical therapists to manage gait disorders and to select exercise interventions that are beneficial to the recovery of walking function in individuals with PD by observing the magnitude of PFC activation. We hope the evidence generated from the study will be comprehensively applicable for assisting gait improvement and quality of life for PD in clinical and community settings. Abbreviations DT dual-task fNIRS Functional near-infrared spectroscopy HbO 2 oxygenated hemoglobin concentration H&Y Hoehn-Yahr stage HRQoL Health related quality of life ITT intention-to-treat PFC prefrontal cortex MDS-UPDRS Movement Disorder Society-Unified Parkinson’s Disease Rating Scale Mini-BESTest Mini-Balance Evaluation Systems Test MMSE Mini-Mental Screening Examination PD Parkinson’s disease; PDQ-39 39-item Parkinson’s Disease Questionnaire TT treadmill training TUG Time-Up and Go Test. Declarations Acknowledgements The authors would like to thank the doctors and physiotherapists from the Neurological rehabilitation Department of Ningbo Rehabilitation Hospital for their support for this study. Availability of data and materials Not applicable. Authors’ contributions ZLL and LFZ conceived the design of the trial; JH and ZLL drafted the manuscript; SSX and JWY planned the study implementation and data collection; and MT and JWY carried out statistical calculations and analyzed the results. All authors have read and approved the final version of the manuscript. Funding This study was supported by Ningbo Natural Science Foundation Program (Key Program) (No.2019A610285), General Educational Planning Project of Zhejiang Province (No.2021SCG100), program of Collaboration and Innovation Center for Application Technology and Standards of Health Aged-care (No.JKYL202201)，and Project of Collaborative Innovation Center for Infant Development and Rehabilitation (No.YYE202204). Ethics approval and consent to participate This study protocol has been approved by the Ethical Review committee of Ningbo College of Health Sciences (LLSC2023017). All participants will voluntarily sign an informed consent before the study implementation, random assignment, and data analysis. All participants will fully understand the content of the study and potential risks. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Author details 1 Ningbo College of Health Sciences, Specialty of Rehabilitation Technique, Ningbo, China 2 Ningbo Rehabilitation Hospital, Neurological rehabilitation Department, Ningbo, China Supplementary Information The online version contains supplementary material available References Silva AZD, Israel V. Effects of dual-task aquatic exercises on functional mobility, balance and gait of individuals with Parkinson's disease: A randomized clinical trial with a 3-month follow-up. Complementary Therapies in Medicine. 2019; 42:119-24. Fritz NE, Cheek FM, Nichols-Larsen D S. 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Comparison of strength training, aerobic training, and additional physical therapy as supplementary treatments for Parkinson's disease: pilot study. Clin Interv Aging. 2015; 10: 183-91. Borg, G. Borg’s Perceived Exertion and Pain Scales. Human Kinetics, USA; 1998; 87-88. Trigueiro LC, Gama GL, Ribeiro TS, Ferreira LG, Galvão ÉR, Silva EM, Júnior CO, Lindquist AR. Influence of treadmill gait training with additional load on motor function, postural instability and history of falls for individuals with Parkinson's disease: A randomized clinical trial. J Bodyw Mov Ther. 2017; 21(1): 93-100. Song R, Grabowska W, Park M, Osypiuk K, Vergara-Diaz GP, Bonato P, Hausdorff JM, Fox M, Sudarsky LR, Macklin E, Wayne PM. The impact of Tai Chi and Qigong mind-body exercises on motor and non-motor function and quality of life in Parkinson's disease: A systematic review and meta-analysis. Parkinsonism Relat Disord. 2017; 41: 3-13. Vitório R, Lirani-Silva E, Baptista AM, Barbieri FA, dos Santos PC, Teixeira-Arroyo C, Gobbi LT. Disease severity affects obstacle crossing in people with Parkinson's disease. Gait Posture. 2014; 40(1): 266-9. Fernandes Â, Sousa AS, Rocha N, Tavares JM. Parkinson's Disease and Cognitive-Motor Dual-Task: Is Motor Prioritization Possible in the Early Stages of the Disease? J Mot Behav. 2016; 48(4): 377-83. Hawkins KA, Fox EJ, Daly JJ, Rose DK, Christou EA, McGuirk TE, Otzel DM, Butera KA, Chatterjee SA, Clark DJ. Prefrontal over-activation during walking in people with mobility deficits: Interpretation and functional implications. Hum Mov Sci. 2018; 59: 46-55. Niu R, Yu Y, Li Y, Liu Y. Use of fNIRS to Characterize the Neural Mechanism of Inter-Individual Rhythmic Movement Coordination. Front Physiol. 2019; 10: 781. Sakatani K, Yamashita D, Yamanaka T, Oda M, Yamashita Y, Hoshino T, Fujiwara N, Murata Y, Katayama Y. Changes of cerebral blood oxygenation and optical pathlength during activation and deactivation in the prefrontal cortex measured by time-resolved near infrared spectroscopy. Life Sci. 2006; 78(23): 2734-41. Goetz CG, Stebbins GT, Tilley BC. Calibration of unified Parkinson's disease rating scale scores to Movement Disorder Society-unified Parkinson's disease rating scale scores. Mov Disord. 2012; 27(10): 1239-42. Benka Wallén M, Sorjonen K, Löfgren N, Franzén E. Structural Validity of the Mini-Balance Evaluation Systems Test (Mini-BESTest) in People With Mild to Moderate Parkinson Disease. Phys Ther. 2016; 96(11): 1799-1806. Dibilio V, Nicoletti A, Mostile G, Toscano S, Luca A, Raciti L, Sciacca G, Vasta R, Cicero CE, Contrafatto D, Zappia M. Dopaminergic and non-dopaminergic gait components assessed by instrumented timed up and go test in Parkinson's disease. J Neural Transm (Vienna). 2017; 124(12): 1539-1546. Tu XJ, Hwang WJ, Hsu SP, Ma HI. Responsiveness of the short-form health survey and the Parkinson's disease questionnaire in patients with Parkinson's disease. Health Qual Life Outcomes. 2017, 15(1): 75. Schumacher EH, Elston PA, D'Esposito M. Neural evidence for representation-specific response selection. J Cogn Neurosci. 2003; 15(8): 1111-21. Micó-Amigo ME, Kingma I, Heinzel S, Nussbaum S, Heger T, van Lummel RC, Berg D, Maetzler W, van Dieën JH, Dual vs. Single Tasking During Circular Walking: What Better Reflects Progression in Parkinson's Disease? Front Neurol. 2019; 10: 372. Desjardins-Crépeau L, Berryman N, Fraser SA, Vu TT, Kergoat MJ, Li KZ, Bosquet L, Bherer L. Effects of combined physical and cognitive training on fitness and neuropsychological outcomes in healthy older adults. Clin Interv Aging. 2016; 11: 1287-1299. Fraser SA, Li KZ, Berryman N, Desjardins-Crépeau L, Lussier M, Vadaga K, Lehr L, Minh Vu TT, Bosquet L, Bherer L. Does Combined Physical and Cognitive Training Improve Dual-Task Balance and Gait Outcomes in Sedentary Older Adults? Front Hum Neurosci. 2016; 10: 688. Paz TSR, Guimarães F, Britto VLS, Correa CL. Treadmill training and kinesiotherapy versus conventional physiotherapy in Parkinson's disease: a pragmatic study. Fisioterapia Em Movimento. 2019; 32: e003201. Matos LC, Sousa CM, Gonçalves M, Gabriel J, Machado J, Greten HJ, Qigong as a Traditional Vegetative Biofeedback Therapy: Long-Term Conditioning of Physiological Mind-Body Effects. Biomed Res Int. 2015; 2015: 531789. Yang Y, Qiu W Q, Hao Y L, Yun Z L, Jiao J S, Teng FJ. The Efficacy of Traditional Chinese Medical Exercise for Parkinson's Disease: A Systematic Review and Meta-analysis. PLOS One. 2015; 10(4): e0122469. Stern Y. An approach to studying the neural correlates of reserve. Brain Imaging Behav. 2017; 11: 410-416. Fisher BE, Wu AD, Salem GJ, Song J, Lin CH, Yip J, Cen S, Gordon J, Jakowec M, Petzinger G. The effect of exercise training in improving motor performance and corticomotor excitability in people with early Parkinson's disease. Arch Phys Med Rehabil. 2008; 89(7): 1221-9. Petzinger GM, Fisher BE, McEwen S, Beeler JA, Walsh JP, Jakowec MW. Exercise-enhanced neuroplasticity targeting motor and cognitive circuitry in Parkinson's disease. Lancet Neurol. 2013, 12(7): 716-26. Mirelman A, Maidan I, Bernad-Elazari H, Shustack S, Giladi N, Hausdorff JM. Effects of aging on prefrontal brain activation during challenging walking conditions. Brain Cogn. 2017; 115: 41-46. Table 1 Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.docx Additionalfile1.doc Additional file 1. SPIRIT Checklist for Trials &Training Scheme Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4976473","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Study protocol","associatedPublications":[],"authors":[{"id":351922347,"identity":"cda08447-074c-4b2e-a492-408b2ef7f24b","order_by":0,"name":"Juan Hui","email":"","orcid":"","institution":"Ningbo College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Juan","middleName":"","lastName":"Hui","suffix":""},{"id":351922351,"identity":"c50f466a-5f90-44d1-9519-6e194a7d4a83","order_by":1,"name":"Zhenlan Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxElEQVRIiWNgGAWjYLCCDxVscvwMjA3E62CccYbPWLKBFC3MvC1yiRsOEKucv733mARvg1ni5vOH2x78YLCT0yVkmcSZc2kSkjvSjLfdSGw37GFINjYjZJ2BRI6ZhOGZY7LbbjC2SfAwHEjcRpSWxLb/jJv7D7ZJ/iFay8E2NsUNDIlt0kTZInHmjLFlwxk2Y4kbQC0yBkT4hb+9x/D2H1BU9h9/Jvmmwk6OoBYgYJFAcidh5SDA/IE4daNgFIyCUTBiAQA4XkGpc5HkSwAAAABJRU5ErkJggg==","orcid":"","institution":"Ningbo College of Health Sciences","correspondingAuthor":true,"prefix":"","firstName":"Zhenlan","middleName":"","lastName":"Li","suffix":""},{"id":351922353,"identity":"5681ce35-a883-4f7f-bd86-69a94e7e9d76","order_by":2,"name":"Shanshan Xu","email":"","orcid":"","institution":"Ningbo College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Shanshan","middleName":"","lastName":"Xu","suffix":""},{"id":351922356,"identity":"8c3c1d84-dc58-4872-aab1-4652d83683db","order_by":3,"name":"Junwu Yu","email":"","orcid":"","institution":"Ningbo College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Junwu","middleName":"","lastName":"Yu","suffix":""},{"id":351922358,"identity":"0260e642-ef2e-486f-888c-74c496553c3a","order_by":4,"name":"Min Tang","email":"","orcid":"","institution":"Ningbo Rehabilitation hospital","correspondingAuthor":false,"prefix":"","firstName":"Min","middleName":"","lastName":"Tang","suffix":""},{"id":351922360,"identity":"c0b797e2-0fb8-4c1e-a9b1-2042b723c1a0","order_by":5,"name":"Lifeng Zhou","email":"","orcid":"","institution":"Ningbo College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Lifeng","middleName":"","lastName":"Zhou","suffix":""}],"badges":[],"createdAt":"2024-08-26 08:40:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4976473/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4976473/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66938252,"identity":"444c61d7-8051-4c7f-ae5d-7a6a7813ddc7","added_by":"auto","created_at":"2024-10-18 08:36:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":344331,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of the study design\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4976473/v1/b45d35fb6d589598d702557a.png"},{"id":102058622,"identity":"dd70c50d-9d54-40cb-a2bf-6da67eaf5e68","added_by":"auto","created_at":"2026-02-06 16:25:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1064822,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4976473/v1/c64f85d1-3325-4d78-9c05-ab35d17b2f4b.pdf"},{"id":66938251,"identity":"1bd23be7-966a-408b-82c0-3b0525487b4b","added_by":"auto","created_at":"2024-10-18 08:36:57","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":45191,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4976473/v1/a6302b34239bbf9d0514b183.docx"},{"id":66938253,"identity":"7a92d89b-b248-4393-8245-8d3864a78086","added_by":"auto","created_at":"2024-10-18 08:36:57","extension":"doc","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":139776,"visible":true,"origin":"","legend":"\u003cp\u003eAdditional file 1. SPIRIT Checklist for Trials \u0026amp;Training Scheme\u003c/p\u003e","description":"","filename":"Additionalfile1.doc","url":"https://assets-eu.researchsquare.com/files/rs-4976473/v1/bbf2fe45a8b0b8020e93987f.doc"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparing the effects of treadmill training versus Baduanjin on prefrontal cortical activity during dual-task walking in Parkinson’s disease: Study protocol using a fNIRS device","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe simultaneous performance of motor and cognitive tasks is required for most daily activities and demands continuous integration of neural processes as well as the practice of so called \u0026ldquo;dual tasks\u0026rdquo; (DTs)[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Adding an attention-focused cognitive task to mobility tasks has been shown to amplify gait variability in individuals with neurologic disorders, such as stroke, Parkinson\u0026rsquo;s disease, and multiple sclerosis[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Compared to healthy elderly individuals, patients with PD present with deficits in the cognitive domain and sensory-motor processing, in particular when walking under challenging conditions (such as talking on the phone while walking), and they have significantly increased the swing and stride time variability [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Previous research has indicated that patients with PD apply higher-level cognitive resources to compensate for motor deficits, in particular in the prefrontal lobe [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The ability to walk while performing cognitive tasks depends on executive functions with projections derived from the prefrontal cortex (PFC)[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAt present, the activation of the PFC can be detected by functional near-infrared spectroscopy (fNIRS). This non-invasive technique has become an important research tool to explore neural activity of locomotion in aging and special populations (patients with neurological or psychiatric conditions) or for a variety of motor tasks, such as walking under different conditions [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. fNIRS mainly measures the concentrations of oxygenated (HbO\u003csub\u003e2\u003c/sub\u003e) and deoxygenated (HHb) hemoglobin in the PFC to quantify task-related changes in brain activation[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Many studies found that the specific nature of complex walking plays a vital role in determining the frontal lobe involvement in gait. Further, higher PFC activation could be observed regardless of the type of accompanying task performed during ambulation. The mean HbO\u003csub\u003e2\u003c/sub\u003e concentrations of the PFC in PD during DT walking (walking while serially subtracting or reciting digit spans) were significantly higher than during rest [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. There was also a significant increase in prefrontal activity when crossing an obstacle but only a slight increase in activation during DT walking in contrast to usual walking. The HbO\u003csub\u003e2\u003c/sub\u003e levels were higher in patients with PD than in healthy elderly people during usual walking [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The reason may be that patients with PD recruit more brain networks, in particular cognitive prefrontal areas, as a form of compensation due to decreased gait automaticity even while performing simple tasks [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInterventions that ameliorate components of frontal-striatal circuits may have a direct effect on a patient's ability to walk in complex situations and reduce the risk of falls [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Several studies showed that treadmill training can improve gait performance and lower prefrontal activation during a simple walking task [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Evidence for assessing the impact of DT training on prefrontal activation using fNIRS is growing in PD studies. When compared to over-ground walking, patients with PD showed a significant decrease in prefrontal activity and a walking pattern with increased stability during treadmill walking [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. After a treadmill training program, patients with PD demonstrated significantly improved cognitive function and mobility as well as modified cerebellar activity [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Adding a cognitive training component to a treadmill exercise program obviously altered the effects of training on the magnitude and lateralization of prefrontal activation in patients with PD [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. An intensive exercise-based training program might produce positive effects in patients with PD by decreasing prefrontal activity and improving gait performance during usual walking [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eQigong is traditional Chinese exercise, which is widely used to treat various chronic diseases and improve physical health [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Baduanjin is one type of Qigong, which likely originated in ancient China over a 1000 years ago; it is also known as the \u0026ldquo;eight section brocades\u0026rdquo;[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Baduanjin exercise emphasizes meditative movements, breathing patterns, and mental regulation. Previous studies proved that Baduanjin can improve balance and reduce the risk of falls among patients with PD [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Furthermore, Baduanjin can promote the recovery of walking and in particular improve the gait speed, stride length, and cadence of patients with PD [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, currently, no study has explored the effects of Baduanjin on PFC activity in patients with PD. Further, few studies compared the effects of treadmill training and Baduanjin on changes in the activation of the PFC in patients with PD performing different types of dual-tasking. Thus, the changes in activity patterns of prefrontal neurons caused by both types of exercise remain to be further investigated.\u003c/p\u003e \u003cp\u003eThe aim of our study protocol is to assess (1) the effects of 12 weeks of treadmill training and Baduanjin exercise on the prefrontal activity and gait performance during single-task and three types of DT walking (obstacle negotiation, backward digital span, and serial-3 subtraction); (2) the relationship between prefrontal activation and gait performance; and (3) comparative effects of the two exercises on motor function, balance, mobility, and quality of life. We hypothesize that both exercises will reduce prefrontal activation during single-task and DT walking, and the better the gait performance, the lower the prefrontal activation of the prefrontal cortex, Baduanjin exercise may reduce activation more than treadmill training. Both types of exercise will be beneficial for motor function, balance, mobility, and quality of life of patients with PD.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy design overview\u003c/h2\u003e\n \u003cp\u003eThis study is designed as a randomized, single-blind, single-center trial and will be conducted at the local rehabilitation hospital. This clinical trial was approved by the Ethics Committee of Ningbo College of Health Sciences (LLSC2023017) and registered in the China Clinical Trial Registry (ChiCTR2300075048). The design of this interventional study follows the Standard Protocol Items: Recommended for Interventional Trials (SPIRIT) 2013 statement (see Additional file1) [\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e]. Participants will be randomly allocated into two intervention groups and one waitlist control group for 12 weeks. An informed consent will be signed prior to joining the study. Assessments will be conducted at baseline, after 12 weeks of intervention, and after a 12-week follow-up and will include gait parameters, changes in the HbO\u003csub\u003e2\u003c/sub\u003e concentration in the PFC, and other motor function parameters. The schedule of observations is illustrated in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003eParticipants\u003c/h2\u003e\n \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\n \u003ch2\u003eRecruitment\u003c/h2\u003e\n \u003cp\u003eWe will enroll participants from the Neurology Department of the local rehabilitation hospital and local communities by means of printed leaflets, online PD patient groups, and popular science lectures by the hospital. To minimize potential expectation bias and confirm eligibility, a research assistant will contact those referred by a clinician and follow up with interested participants by phone. Participants will be informed that they will be randomly allocated to two experimental groups (treadmill training and Baduanjin) and a waitlist control group. Figure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the recruitment strategy, intervention procedure, and time points of the three assessments.\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\n \u003ch2\u003eInclusion criteria\u003c/h2\u003e\n \u003cp\u003e(1) Age 60\u0026ndash;75 years old; (2) diagnosed with idiopathic PD according to the UK Brain Bank criteria[\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e]; (3) Hoehn and Yahr (H\u0026amp;Y) stage I\u0026ndash;III; (4) Mini-Mental State Examination score\u0026thinsp;\u0026ge;\u0026thinsp;24; and (5) ability to walk at least 5 min independently (walking aids are permitted).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\n \u003ch2\u003eExclusion criteria\u003c/h2\u003e\n \u003cp\u003e(1) Unstable medical conditions, including cardiopulmonary disease, cancer, or orthopedic problems affecting performance; (2) severe cognitive, visual, or auditory impairment; (3) any co-morbidity of the motor system that may restrict the gait; and (4) other ongoing forms of intensive training.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\n \u003ch2\u003eSample size\u003c/h2\u003e\n \u003cp\u003eIn the absence of preliminary data on a meaningful change in prefrontal activation for DT walking, the effect size will be calculated by the gait speed. A clinically important difference in the gait speed among people with PD under the on-medication condition ranged from 0.05 m/s to 0.22 m/s by a distribution-based analysis [\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e]. We set a statistical power of 0.8 and two-tailed \u0026alpha; level of 0.05 in repeated-measures multivariate analysis of variance (MANOVA). Based on the data of a previous study, we assumed that there would be a difference of 15% between the Treadmill training group and Baduanjin group in favor of DT gait[\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e]. Considering a loss to follow-up, with an estimated drop-out rate of 5%, we will recruit 48 participants per group (a total of 144 patients).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\n \u003ch2\u003eRandomization, allocation, and blinding\u003c/h2\u003e\n \u003cp\u003eEligible participants will be randomized to one of the groups with an allocation of 1:1:1 ratio through an independent statistician-implemented, computerized block randomization. The treating physiotherapist will be notified of the results of the group allocation by e-mail to ensure concealed allocation. All study assessors who collect outcome measures will be blinded to the study hypotheses and group assignments. In addition, participants will be instructed not to reveal their training regime at any time to prevent unbinding. Both therapists and participants will be informed that both training methods may effectively improve DT gait performance to control for expectancy effects.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\n \u003ch2\u003eStudy interventions\u003c/h2\u003e\n \u003cp\u003eParticipants in the two intervention groups will complete an exercise program during the \u0026ldquo;on\u0026rdquo; medication phase that will be supervised by a physiotherapist. The program will consist of a 5-min warm-up, 30-min treadmill training or Baduanjin, and 10-min cool-down. The training period will encompass 12 consecutive weeks with a total of 36 sessions, including three weekly sessions lasing 45 min each. The intensity will be monitored by measuring the heart rate (Polar Team2; Polar Electro Finland) and perceived exertion (PRE). The calculation of the heart rate will adopt 60\u0026ndash;70% of the HR\u003csub\u003emax\u003c/sub\u003e, determined by the formula HR\u003csub\u003emax\u003c/sub\u003e = 208 \u0026minus; (0.7 \u0026times; age) [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e] or reaching a fatigue limit at the RPE of 12 [\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]. Attendance will be recorded for each training session. An assistant will inquire about the reason of absence by telephone for those participants with low attendance, and encourage them to persist in exercising. Moreover, participants will write an exercise log throughout the study, the content will involve in the self-report training effects, training duration per session and fall events.\u003c/p\u003e\n \u003cp\u003ea) Treadmill training\u003c/p\u003e\n \u003cp\u003eParticipants will perform gait training on a treadmill (GaitTrainer System 2-Biodex Medical Systems, NY, USA). A safety jacket will be attached to an overhead suspension system, without providing weight support.\u003c/p\u003e\n \u003cp\u003eAt the first training session, participants will be familiarized with the equipment and will receive a gait speed measurement over-ground by 10 m walking. With the progression of training, treadmill speed will be elevated, and the duration of intervals of training will be reduced. During the first 2 weeks of the program, the treadmill speed will be set at 80% of the usual gait speed. The 30-min training sessions will be conducted in three sessions with 5-min breaks at the intervals. During the third and fourth weeks, the treadmill speed will be increased to 90% of the usual speed, and the training session will be completed in two 15-min sessions with a 5-min break between the sessions. During the latter 8 weeks, the treadmill speed will be increased to its usual speed and the training will be continuous for 30 min. Participants will conduct 5-min active stretching exercises to warm up. Ten min of relaxation exercise will be performed on the ground at the end of treadmill training. Training scheme is shown in Additional file 1.\u003c/p\u003e\n \u003cp\u003eThe participants will be encouraged to maintain a postural alignment and use the frontal support of the treadmill to minimize physical exertion[\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e]. Cognitive components of the DT will be integrated into the gait training after 4 weeks of training, including 1) walking while phoning; 2) walking while performing a backward digit span; and 3) walking while carrying a bag filled with food.\u003c/p\u003e\n \u003cp\u003eb) Baduanjin exercise\u003c/p\u003e\n \u003cp\u003eParticipants will be instructed to perform Baduanjin, whose characteristics include symmetrical physical postures and dynamic movements, postural control, meditation, and rhythmic breathing regulation [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e]. It consists of eight different movements, and each movement is repeated six times. The Baduanjin training program is shown in Additional file 1. During the initial 2\u0026ndash;4 weeks, participants will learn to adjust their breathing and coordinate it with the prescribed movements. The whole set of Baduanjin movements usually takes 12\u0026ndash;15 min to complete at a regular pace[\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e]. During the later 5\u0026ndash;12 weeks, a concurrent cognitive task will be added to the exercise. The purpose is to strengthen continuous attentional processing demands while performing another task under varying conditions. Participants will practice Baduanjin while performing the following tasks: 1) stating the form of each movement; 2) counting a 4-digit number backwards; and 3) reciting Chinese poems.\u003c/p\u003e\n \u003cp\u003ec) The waitlist control group will continue to maintain routine care and lifestyle and will not perform any form of intensive training. A research assistant will follow up their health status twice a month by phone or WeChat. They will participate in either the treadmill training or Baduanjin exercise after the 12-week follow-up assessment.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eOutcome measures\u003c/h2\u003e\n \u003cp\u003eThe participants\u0026rsquo; demographic characteristics will be collected before the study, including age, gender, duration of disease, weight, height, educational level, health status, medication dosage, exercise habits, and the numbers of falls within 6 months.\u003c/p\u003e\n \u003cp\u003eAll assessments will be performed in the practical, self-reported on-medication status, at about the same time of day. Participants will be required to walk under four conditions on a 4.6 m electronic walkway, while wearing a portable fNIRS device. The walking conditions will be: 1) walking at a usual speed; 2) walking while conducting a backward digital span; 3) walking while performing a serial-3 subtraction; and 4) walking while negotiating two obstacles positioned on the walkway at specific locations. The obstacles will be set up at a half knee height🞨60 cm and width 🞨3 cm depth [\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eTo avoid a learning effect, the order of each task will be changed randomly. Participants will walk three consecutive loops on the walkway to obtain valid trials and to minimize within-individual variability, and the interval of each task will include 1-min rest [\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e]. All experimental data will be collected by the same trained assessor to ensure reproducibility.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003ePrimary Outcomes measures\u003c/h2\u003e\n \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\n \u003ch2\u003eChange of prefrontal activity\u003c/h2\u003e\n \u003cp\u003ePrefrontal activity will be measured by monitoring the change in HbO\u003csub\u003e2\u003c/sub\u003e concentration of the anterior PFC using a multi-channel, continuous wave, fNIRS instrument (NIRScout; NIRx Medical Technologies LLC; Minneapolis, MN, USA) during task performance. The space between the emitter and detector will be maintained at 3 cm. HbO\u003csub\u003e2\u003c/sub\u003e concentration is sensitive to walking-related changes in cortical activity and has been used as a primary outcome to measure prefrontal activity [\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eThe concentration of HbO\u003csub\u003e2\u003c/sub\u003e will be exported to MATLAB (MathWorks; Natick, MA, United States) for further data analysis. A bandpass filter with a cutoff frequency of 0.01 Hz will be used to remove low-frequency noise, such as head movements, and a low-pass filter with a cutoff frequency of 0.15 Hz will be utilized to reduce high-frequency noise and cardiovascular artifacts [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e]. The concentration changes of HbO\u003csub\u003e2\u003c/sub\u003e in the targeted PFC will be calculated from the changes in detected light intensity according to the modified Beer-Lambert Law [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e]. For each experimental condition, the average concentration of HbO\u003csub\u003e2\u003c/sub\u003e during task performance and 10 s baseline (i.e., the value during the 10 s quiet standing prior to the task) will be used to determine relative changes in HbO\u003csub\u003e2\u003c/sub\u003e concentration. We will analyze the average of the left and right PFC HbO\u003csub\u003e2\u003c/sub\u003e concentrations [\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eGait parameters\u003c/h2\u003e\n \u003cp\u003eWe will select the gait speed (m/s), stride length (m), double-phase time (%), stride variability (%), and step width (cm). The gait parameters will be measured using an electronic walkway with pressure sensors embedded in a 4.6 m carpet. Data processing and storing will be performed using the PKMAS software (PKMAS walkway, ProtoKinetics, Havertown, PA, USA) connected to a personal computer. Prior to performing each task, the participants will be required to stand quietly for 20 s and refrain from talking or moving their heads. The instruction \u0026ldquo;start\u0026rdquo; will be given after these 20 s.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eSecondary outcome measures\u003c/h2\u003e\n \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\n \u003ch2\u003eDisease severity\u003c/h2\u003e\n \u003cp\u003eDisease severity will be determined using the Movement Disorder Society-Unified Parkinson\u0026rsquo;s Disease Rating Scale (MDS-UPDRS). The MDS-UPDRS is structured in four parts, namely, Non-motor Experiences of Daily Living (I); Motor Experiences of Daily Living (II); Motor Examination (III); and Motor Complications (IV). Each item is scored on a 5-point scale (0\u0026ndash;4 points), with a minimum score of 0 indicating normal and a maximum score of 4 indicating a severe impairment in performing activities. Thus, higher scores reflect worse functioning. The H\u0026amp;Y stage in the MDS-UPDRS includes 5 stages, with the early, middle, and late stages of PD corresponding to stage I-II, stage III-IV, and stage V, respectively [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003eBalance function\u003c/h2\u003e\n \u003cp\u003eBalance function will be measured by the Mini-Balance Evaluation Systems Test (Mini-BESTest). The scale consists of 14 items from four different balance control systems, including anticipatory postural adjustments, reactive postural control, sensory orientation, and dynamic gait. Each item is assessed from 0 to 2 points, and the total score ranges from 0 to 28, with a higher score representing better balance function [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003eThe Time-Up and Go Test (TUG)\u003c/h2\u003e\n \u003cp\u003eTUG is widely used in clinical research to test balance, mobility, and fall risk. It is quick and easy to conduct and requires a participant to stand up from a chair, walk 3 m, turn 180\u003csup\u003e\u0026deg;\u003c/sup\u003e, walk back to the chair, and sit down. The outcome is the total duration, which is usually recorded with a stopwatch [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n \u003ch2\u003eHealth related quality of life (HRQoL)\u003c/h2\u003e\n \u003cp\u003eHROoL will be used to reflect the progression of PD and will be assessed using the 39-item Parkinson\u0026rsquo;s Disease Questionnaire (PDQ-39). It has eight domains: mobility, activities of daily living, emotional well-being, stigma, social support, cognition, communication, and bodily discomfort. A summary index of the eight domain scores ranges from 0 to 100, with higher scores indicating more frequent self-perceived difficulties in HRQoL [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n \u003ch2\u003eData management and monitoring\u003c/h2\u003e\n \u003cp\u003eTo ensure the integrity and security of data, the project and data management and monitoring will be supervised by the independent Scientific Research Management Platform of the Ningbo Rehabilitation Center. The paper-based personal details and data involved will be confidential and stored in locked file cabinets in restricted-access areas. Output files from computer-based tasks will be encrypted and stored on research computers, and accessible only to authorized staff involved in the project.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eStatistical analysis will be carried out using IBM SPSS Statistics 24.0. Group comparisons on baseline demographic descriptors and primary and secondary outcome measures will be performed utilizing analysis of variance (ANOVA) for continuous variables and the chi-square independent test for categorical variables. Primary and secondary intervention effects for between/within-group differences will be analyzed by mixed repeated-measures ANOVA. The H\u0026amp;Y stage and MMSE score will be included as covariates since these variables will probably differ significantly among the groups. Bonferroni\u0026rsquo;s post hoc test will be used to compare results when the main effects are significant. Paired \u003cem\u003et\u003c/em\u003e-test will be adopted to test within-group changes from baseline to post 12-week follow-up.\u003c/p\u003e\n \u003cp\u003eHbO\u003csub\u003e2\u003c/sub\u003e differences among the groups and tasks will be measured using a linear regression, including the interactions between groups and tasks. Pearson correlation coefficients will be adopted to analyze the association between gait performance and PFC activation with tasks in the three groups [\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e]. We will employ repeated measures ANOVA to analyze differences among conditions with regards to HbO\u003csub\u003e2\u003c/sub\u003e levels and gait parameters. Post-hoc analysis will be used to assess for differences between the tasks in both gait and HbO\u003csub\u003e2\u003c/sub\u003e. Data normality will be tested utilizing the Kolmogorov\u0026ndash;Smirnov test. If the data are not normally distributed, the Mann-Whitney U test will be applied to analyze between-group differences under different tasks following training (baseline minus post-intervention), and the Wilcoxon signed-ranks test will be utilized to analyze within-group differences. Significant differences will be set at P values less than 0.05. Missing data and lost to follow-up data will be analyzed based on the intention-to-treat (ITT) principle, and all data obtained from the participants will be included in the analysis.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eDual-task theories have indicated that deficits in motor performance result from spatial and temporal interferences in information processing, contributing to a compromised selection and execution of the motor response [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The loss of automaticity in PD causes difficulties in gait control and might augment the reliance on cognitive resources to optimize motor control. This restricts the utilization of cognitive resources in PD to perform another task while walking [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Recent studies have indicated that adding aerobic exercise to non-motor cognitive training could enhance the cognitive capacity in frontal regions and thereby release more capacity to support motor control [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. In addition, cortical activation of the PFC or dorsolateral PFC decreased after an exercise intervention, and the step speed and length significantly improved [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, most studies have not explicitly investigated the differential effect of PFC activation on various DT gaits and have not elucidated which exercise mode is conducive to reduce cortical activation and facilitate the recovery of walking ability in patients with PD[\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Therefore, we have designed a comparative randomized controlled trial to assess the impact of two training methods on PFC activity, particularly the effect of PFC activation on gait improvement among DT in patients with PD. In this study, we have selected treadmill training, because an instrumented training approach has been shown to significantly improve single task gait performance and gait pattern in patients with PD [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Baduanjin qigong has become a popular exercise program among the elderly in China and plays an important role in promoting health and improving the quality of life. In Baduanjin, the forms and movements are slow and rhythmic, and there is a focus on posture, breathing, and inner balance. This strengthens the function of the vegetative nervous system and intensifies the whole body state [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Baduanjin benefits patients with PD by improving their gait, balance, concentration, and coordination [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the two experiment groups, we will integrate a cognitive component into training in order to increase the cognitive reaction speed when walking under DT conditions. We will add cognitive components to the Baduanjin exercise, such as participants needing to memorize and retell the name of each pattern when practicing. This may improve individuals\u0026rsquo; ability to process cognitive resources concurrently with conducting another motor task. Participants in the treadmill training group will walk while talking on the phone, counting down numbers, and carrying a bag full of food. Perhaps the ability to speed up one\u0026rsquo;s cognitive response will promote a walking speed improvement in more challenging DTs, enabling their better performance. Some research has shown that exercise may influence PFC recruitment simultaneously or separately in two ways: (1) In order to produce the same (or higher) level of usual walking performance, the efficiency of neural control can increase to reduce activation, and (2) the PFC generates the highest activation capacity, that is, extends capacity[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Moreover, exercise can facilitate neuroplasticity in aging healthy individuals and might benefit the recovery of motor automaticity in individuals with PD. This improvement of the automaticity of motion could free cognitive resources and perhaps contribute to improved walking performance [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis protocol still has some limitations. First, it is difficult to achieve a double-blind status for participants and investigators to achieve a doubled-blind status because exercise intervention is extensively to the participants. Second, participants are limited to those with mild to moderate PD, whether the results are generalizable to advanced PD remains unclear. Third, intervention duration and follow-up are relatively short, so long-term training effects on PFC activity and various functions in PD may not be observed. Future investigations will focus on the long-term therapeutic effects of treadmill training and Baduanjin. We will try to modify the existing protocol so that it can be used in advanced PD. The findings will help clinicians and physical therapists to manage gait disorders and to select exercise interventions that are beneficial to the recovery of walking function in individuals with PD by observing the magnitude of PFC activation. We hope the evidence generated from the study will be comprehensively applicable for assisting gait improvement and quality of life for PD in clinical and community settings.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eDT \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; dual-task\u003c/p\u003e\n\u003cp\u003efNIRS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Functional near-infrared spectroscopy\u003c/p\u003e\n\u003cp\u003eHbO\u003csub\u003e2\u003c/sub\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;oxygenated hemoglobin concentration\u003c/p\u003e\n\u003cp\u003eH\u0026amp;Y \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Hoehn-Yahr stage \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHRQoL \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Health related quality of life\u003c/p\u003e\n\u003cp\u003eITT \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;intention-to-treat\u003c/p\u003e\n\u003cp\u003ePFC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;prefrontal cortex\u003c/p\u003e\n\u003cp\u003eMDS-UPDRS \u0026nbsp; \u0026nbsp; \u0026nbsp; Movement Disorder Society-Unified Parkinson\u0026rsquo;s Disease Rating Scale\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMini-BESTest \u0026nbsp; \u0026nbsp; Mini-Balance Evaluation Systems Test\u003c/p\u003e\n\u003cp\u003eMMSE \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Mini-Mental Screening Examination\u003c/p\u003e\n\u003cp\u003ePD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Parkinson\u0026rsquo;s disease;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePDQ-39 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;39-item Parkinson\u0026rsquo;s Disease Questionnaire\u003c/p\u003e\n\u003cp\u003eTT \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; treadmill training\u003c/p\u003e\n\u003cp\u003eTUG \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Time-Up and Go Test.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the doctors and physiotherapists from the\u0026nbsp;Neurological rehabilitation Department of Ningbo Rehabilitation Hospital for their support for this study.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZLL and LFZ conceived the design of the trial; JH and ZLL drafted the manuscript; SSX and JWY planned the study implementation and data collection; and MT and JWY carried out statistical calculations and analyzed the results. All authors have read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by\u0026nbsp;Ningbo Natural Science Foundation Program (Key Program) (No.2019A610285), General Educational Planning Project of Zhejiang Province (No.2021SCG100), program of Collaboration and Innovation Center for Application Technology and Standards of Health Aged-care (No.JKYL202201)，and Project of Collaborative Innovation Center for Infant Development and Rehabilitation (No.YYE202204).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study protocol has been approved by the Ethical Review committee of Ningbo College of Health Sciences (LLSC2023017). All participants will voluntarily sign an informed consent before the study implementation, random assignment, and data analysis. All participants will fully understand the content of the study and potential risks.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eNingbo College of Health Sciences, Specialty of Rehabilitation Technique, Ningbo, China\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eNingbo Rehabilitation Hospital, Neurological rehabilitation Department, Ningbo, China\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eSupplementary Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe online version contains supplementary material available\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSilva AZD, Israel V. 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Clin Interv Aging. 2016; 11: 1287-1299.\u003c/li\u003e\n\u003cli\u003eFraser SA, Li KZ, Berryman N, Desjardins-Cr\u0026eacute;peau L, Lussier M, Vadaga K, Lehr L, Minh Vu TT, Bosquet L, Bherer L. Does Combined Physical and Cognitive Training Improve Dual-Task Balance and Gait Outcomes in Sedentary Older Adults? Front Hum Neurosci. 2016; 10: 688.\u003c/li\u003e\n\u003cli\u003ePaz TSR, Guimar\u0026atilde;es F, Britto VLS, Correa CL. Treadmill training and kinesiotherapy versus conventional physiotherapy in Parkinson\u0026apos;s disease: a pragmatic study. Fisioterapia Em Movimento. 2019; 32: e003201.\u003c/li\u003e\n\u003cli\u003eMatos LC, Sousa CM, Gon\u0026ccedil;alves M, Gabriel J, Machado J, Greten HJ, Qigong as a Traditional Vegetative Biofeedback Therapy: Long-Term Conditioning of Physiological Mind-Body Effects. Biomed Res Int. 2015; 2015: 531789.\u003c/li\u003e\n\u003cli\u003eYang Y, Qiu W Q, Hao Y L, Yun Z L, Jiao J S, Teng FJ. The Efficacy of Traditional Chinese Medical Exercise for Parkinson\u0026apos;s Disease: A Systematic Review and Meta-analysis. PLOS One. 2015; 10(4): e0122469.\u003c/li\u003e\n\u003cli\u003eStern Y. An approach to studying the neural correlates of reserve. Brain Imaging Behav. 2017; 11: 410-416.\u003c/li\u003e\n\u003cli\u003eFisher BE, Wu AD, Salem GJ, Song J, Lin CH, Yip J, Cen S, Gordon J, Jakowec M, Petzinger G. The effect of exercise training in improving motor performance and corticomotor excitability in people with early Parkinson\u0026apos;s disease. Arch Phys Med Rehabil. 2008; 89(7): 1221-9.\u003c/li\u003e\n\u003cli\u003ePetzinger GM, Fisher BE, McEwen S, Beeler JA, Walsh JP, Jakowec MW. Exercise-enhanced neuroplasticity targeting motor and cognitive circuitry in Parkinson\u0026apos;s disease. Lancet Neurol. 2013, 12(7): 716-26.\u003c/li\u003e\n\u003cli\u003eMirelman A, Maidan I, Bernad-Elazari H, Shustack S, Giladi N, Hausdorff JM. Effects of aging on prefrontal brain activation during challenging walking conditions. Brain Cogn. 2017; 115: 41-46. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Treadmill, Baduanjin, prefrontal activity, dual-task, Parkinson’s disease","lastPublishedDoi":"10.21203/rs.3.rs-4976473/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4976473/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e \u003cp\u003ePatients with Parkinson\u0026rsquo;s disease (PD) have shown impaired gait rhythmicity and increased prefrontal activation during complex tasks, presumably to compensate for decreased automaticity. Exercise can reduce cortical excitability and enhance automaticity, thereby improving walking function. However, the effectiveness of treadmill training and Baduanjin on prefrontal activity has received little attention when patients with PD walk under different dual-task conditions. This randomized control trial (RCT) will investigate the comparative effects of treadmill training and Baduanjin on prefrontal activation and gait function during both single and dual tasks in PD.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eThis RCT will be designed as a single-center, three-arm, single-blind study. One hundred and forty-four participants will be allocated into treadmill training, Baduanjin, or waitlist control groups. Participants in both the treadmill training and Baduanjin groups will receive 45 min of specific exercise three times weekly for 12 weeks. Participants in the control groups will maintain routine care and lifestyle. The primary and secondary outcomes will be assessed at baseline, after a 12-week intervention, and at the end of a12-week follow-up. The primary outcomes will be prefrontal activation (oxygenated hemoglobin concentration, HbO\u003csub\u003e2\u003c/sub\u003e) measured by functional near-infrared spectroscopy (fNIRS), and gait parameters (gait speed, stride length, double-phase time, stride variability, and step width) assessed by an electronic walkway with pressure sensors. The secondary outcomes will be motor function, balance, mobility, and quality of life.\u003c/p\u003e\u003ch2\u003eDiscussion:\u003c/h2\u003e \u003cp\u003eThis study will determine whether treadmill training or Baduanjin is more effective in reducing prefrontal activation and improving gait function. If the findings are consistent with our expectations, they may help clinicians and physical therapists to manage gait impairments in patients with PD and to select targeted interventions for them.\u003c/p\u003e\u003ch2\u003eTrial registration\u003c/h2\u003e \u003cp\u003ehttp//www.chictr.org.cn. Trial number ChiCTR2300075048. Registered on 23 Aug 2023.\u003c/p\u003e","manuscriptTitle":"Comparing the effects of treadmill training versus Baduanjin on prefrontal cortical activity during dual-task walking in Parkinson’s disease: Study protocol using a fNIRS device","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-18 08:36:53","doi":"10.21203/rs.3.rs-4976473/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e1ca3e46-77f5-4061-b881-9af64abb2b0b","owner":[],"postedDate":"October 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-06T16:24:59+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-18 08:36:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4976473","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4976473","identity":"rs-4976473","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}