Background Robotic therapy (RT) and augmented reality (AR) have each demonstrated benefits for stroke rehabilitation. Despite the potential priming effect of robotics, no study has investigated whether robotic priming of AR provides additive effects compared to AR or conventional therapy.Objective This study examined the effects of AR with and without robotic priming compared with dose-matched control.Methods In this exploratory trial (N = 33), participants were allocated to robotic-primed AR (RT + AR), AR, or conventional therapy (CT). Outcomes were the Fugl-Meyer Assessment-Upper Extremity (FMA-UE), Berg Balance Scale (BBS), Chedoke Arm and Hand Activity Inventory (CAHAI), and Stroke Impact Scale (SIS). Patient-reported pain and fatigue were recorded.Results All groups improved in motor recovery and balance immediately after therapy. RT + AR exceeded AR (p = 0.037, eta 2=0.19) and CT (p = 0.039, eta 2=0.19) on FMA-UE at post-test and remained superior to CT at follow-up (p = 0.03, eta 2=0.20). For the BBS, both RT + AR (p = 0.016, eta 2=0.18) and AR (p = 0.004, eta 2=0.24) outperformed CT at post-test, and AR retained superiority at follow-up (p = 0.02, eta 2=0.21). RT + AR surpassed CT on CAHAI (p = 0.046, eta 2=0.18) and SIS (p = 0.04, eta 2=0.19) at post-test, with a trend favoring RT + AR on SIS at follow-up (p = 0.06, eta 2=0.18). No severe adverse responses were observed.Conclusion Robotic priming of AR improved more than AR and CT in motor impairments. AR was beneficial for improving balance. Results of this study should be interpreted with caution and may not be generalized to stroke survivors with different characteristics. There was a lack of multiplicity adjustments in this small exploratory trial. Further research is needed to validate the findings based on larger multicenter trials.

Background Gait disorders in Parkinson’s disease (PD) are often characterized by reduced stride length, particularly under off-medication conditions. Inertial measurement units (IMUs) embedded in footwear provide a practical and environment-independent method for assessing stride length. Although deep learning approaches have recently shown promise for stride length estimation from inertial signals, most models have been trained on healthy participants, limiting their applicability to populations with gait impairments. Methods We developed a deep learning model to predict stride length in 10 individuals with PD using tri-axial accelerations and angular velocities recorded from footwear-mounted IMUs. The model incorporated an autoencoder for feature extraction, followed by a fully connected regression network for stride length prediction. Results Leave-one-out cross-validation against ground-truth stride lengths from a GAITRite walkway demonstrated strong agreement, with an R² of 0.8619 and limits of agreement of ±18.11 cm for 1-second windows preceding heel strike. To assess robustness against stride segmentation errors, simulated heel-strike timing offsets of up to ±0.5 s were introduced. Although performance declined with increasing offsets, the model maintained an R² of 0.8033 and limits of agreement of ±21.58 cm at ±0.5 s, indicating that explicit stride segmentation is not required.Significance: These findings demonstrate the feasibility of stride length estimation in PD without explicit stride identification, paving the way for unobtrusive gait monitoring and objective evaluation of disease progression and therapeutic interventions.

Mirror therapy (MT) and augmented reality (AR) are gaining popularity in stroke rehabilitation. MT uses mirror visual feedback to promote bilateral brain coupling and increase primary motor cortex excitability. AR offers an interactive context of practice for promoting motor and cognitive recovery. MT and AR may complement each other for hybrid interventions in stroke rehabilitation. This study investigated the benefits of MT-primed AR (MT + AR) versus AR group, relative to conventional therapy (CT) for individuals with stroke. The study randomly assigned 45 stroke survivors to the MT + AR group, the AR, or the CT group, and 44 of them completed the experiment and were included in the analysis. Each treatment session was 90 min, 3 times a week, for 6 weeks. All assessments were administered before, immediately after treatment, and at 3 months. Primary outcome measures were the Fugl-Meyer Assessment-Upper Extremity (FMA-UE) and the Berg Balance Scale (BBS). Secondary outcome measures were the revised Nottingham Sensory Assessment (rNSA), Chedoke Arm and Hand Activity Inventory (CAHAI), Motor Activity Log (MAL), and Stroke Impact Scale Version 3.0 (SIS). Adverse events were monitored before and after each session. After 6 weeks of treatment, the three groups demonstrated significant improvements in the FMA-UE, BBS, CAHAI, MAL, and SIS. In the between-group comparisons, MT + AR and AR groups demonstrated significant advantages in the BBS, proprioception scale of rNSA and SIS, compared with the CT group. Only the MT + AR group, not the AR group, showed significantly better improvements in the FMA-UE and tactile scale of rNSA than the CT group. The MT + AR and AR alone showed differential benefits in the FMA-UE, tactile scale of rNSA, and SIS; the MT + AR rendered significantly better benefits. There were no significant differences among the three groups in the stereognosis scale of rNSA and MAL. No adverse effects were observed. MT + AR and AR both effectively enhanced sensorimotor functions, balance and postural control, task performance, and life quality in patients with stroke with moderate-to-severe motor impairments. The results showed that MT + AR and AR were more beneficial for improving stroke survivors’ balance, functional mobility, proprioception recovery, and quality of life than the CT group. Furthermore, the MT + AR revealed better outcomes in the upper limb motor function and tactile sensory recovery. Between the MT + AR and AR comparisons, the MT + AR was more beneficial for improving upper limb motor function, tactile sensory recovery, and quality of life. Trial registration NCT05993091.

Investigating brain development during infancy and childhood is essential for identifying critical periods of cognitive growth. Brain connectivity networks constructed from electroencephalograms provide an effective method for examining cortical connections across various frequency bands. While current studies often focus on analyzing trends in functional connectivity or network dynamics over time, they offer limited insights into distinguishing specific differences. This study addresses this gap by examining variations in nodal strength, global efficiency, clustering coefficient, and betweenness centrality during the N1 sleep stage across infancy, toddlerhood, and the preschool stage.Clinical Relevance— This study revealed the lowest nodal strength, global efficiency, and clustering coefficient in the theta band during infancy, while these network indices were highest in the beta band during infancy. Additionally, these indices peaked in the alpha band in preschool children. These findings demonstrate the progressive development of brain connectivity, functional integration, and segregation from infancy to preschool age.

Estimating foot pressure distribution and the center of pressure (COP) using a sparse sensor topology offers cost-effective benefits. While deep learning neural networks improve the prediction of information in areas with incomplete sensing, there are still gaps in foot pressure recordings due to limited sensor coverage in certain plantar regions. To address this, we used eleven larger sensors to increase coverage across critical foot areas, including the big toe, little toe, medial, middle, and lateral metatarsus, as well as the medial and lateral arches, foreheels, and heels. These regions are commonly used to study the effects of muscle fatigue during walking and jogging, as well as to predict ground reaction forces during walking. We employed a conditional generative adversarial network (GAN) to reconstruct high-resolution foot pressure distributions from the data collected by these sensors. This method operates on individual samples, eliminating the need for gait cycle segmentation and normalization. Compared to ground truth data from a 99-sensor array, the GAN approach significantly improved COP estimation over direct computation from the eleven sensors. The highest accuracy was achieved during level walking, with reduced performance during jogging and stair walking. In conclusion, the conditional GAN effectively reconstructed foot pressure distributions, and future research should explore reallocating sensor topology to improve resolution and coverage while balancing simplified instrumentation with improved plantar pressure distribution reconstruction.

Background Spinocerebellar ataxia (SCA) is a neurodegenerative disease causing weakness and balance disorders that affected quality of life. Whole body vibration (WBV) had been reported to facilitate neuromuscular contraction in healthy people and athletes. Objective The purpose of this study was to investigate whether four weeks of WBV training can enhance central and peripheral muscle strength and balance performances in patients with SCA. Methods Thirteen individuals with diagnosed SCA were randomly assigned into WBV and control groups. Subjects in the training group received four weeks of WBV training at semi-squatting position for 3 sessions per week; whereas subjects in the control group performed semi-squatting position for the same duration. The maximum voluntary contraction (MVC), voluntary activation level (VA), twitch force, Berg balance scale (BBS), and one-leg standing time were evaluated before and after training. All subjects in the training group could tolerate the WBV training. Results The MVC of soleus, the VA of plantar flexors and knee extensors, the score of BBS (p < 0.05) and one-leg standing time improved (p < .05) only in the training group. Conclusions WBV training is a feasible rehabilitation strategy which can improve general and central origin force and balance performance in individuals with SCA.

Introduction. Gait initiation (GI) difficulties in Parkinson's disease (PD) are often attributed to impaired anticipatory postural adjustments (APAs), a key pathophysiological factor. The aim of the study is to explore the effects of visual cues on anticipatory postural adjustments (APAs) alterations during gait initiation (GI) in individuals with and without Parkinson's disease (PD) in 18 patients with PD and 18 age-matched healthy controls. Methods: Eighteen patients with PD (PD group) and 18 age-matched healthy controls (HC group) performed self-generated gait initiation with two experimental GI conditions comprising a transverse visual cue and no visual cue. Characteristics of APAs were derived from monitoring the trajectory of the center of pressure (COP) during GI. The measure outcomes included lateral/posterior APA size, APA duration, APA velocity, and the frequency of trials with either missing or multiple APAs. Results: Visual cues significantly increased (P <.0001) both the lateral APA size and APA velocity in the PD groups only. The frequency of missing APAs was higher in the PD group, whereas the incidence of multiple APAs was similar between the PD and HC groups. Conclusion: The findings suggest that the visual cue significantly enhances the preparation for gait initiation in individuals with Parkinson's disease. Further research and long-term studies are needed to fully explore the potential of visual cues as a therapeutic tool in managing postural instability in people with Parkinson's.

BackgroundStroke is a leading cause of long-term disability among stroke survivors. Despite the availability of numerous stroke rehabilitative therapies, such as mirror therapy, bilateral arm training, and robot-assisted therapy, the recovery of motor function after stroke remains incomplete. Bilateral arm function is a key component in stroke patients to perform activities of daily living and to reflect their functional autonomy.ObjectiveThis clinimetric study investigated and compared the construct validity and responsiveness of 2 bimanual activity outcome measures, the Chedoke Arm and Hand Activity Inventory (CAHAI) and the ABILHAND Questionnaire, in individuals receiving stroke rehabilitation.MethodsThe present study is a secondary analysis following the framework of the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN). Individuals with chronic stroke (N = 113) were recruited from outpatient rehabilitation settings. Participants received 18 to 20 sessions of robot-assisted therapy, mirror therapy, combined therapy, or conventional rehabilitation for 4 to 6 weeks. The CAHAI, ABILHAND Questionnaire, and a comparison instrument, the Motor Activity Log (MAL), were administered twice at a 4- to 6-week interval to all participants. ABILHAND scores, in logits, were converted from raw ordinal scores into a linear measure.ResultsThere was medium to large correlation of the CAHAI and the MAL (ρ = 0.60–0.62, p < 0.01) as well as the ABILHAND Questionnaire and the MAL (ρ = 0.44–0.51, p < 0.01). Change scores from the initial measurement to the post-intervention measurement demonstrated small to medium correlation of the CAHAI and the MAL (ρ = 0.27–0.31, p < 0.01) and medium to large correlation of the ABILHAND Questionnaire and the MAL (ρ = 0.37–0.41, p < 0.01). Overall, 7 of 8 hypotheses were supported. The hypothesis testing regarding the construct validity and responsiveness of the CAHAI and ABILHAND Questionnaire was confirmed.ConclusionThe CAHAI and ABILHAND Questionnaire are both responsive and suitable to detect changes in bilateral arm functional daily activities in individuals with chronic stroke. Patient-reported outcome measures are recommended to use along with therapist-rated outcome measures for upper limb capacity evaluation in stroke rehabilitation. Further study with a prospective study design to capture specific clinical features of participants and the use of body-worn sensors, such as the arm accelerometer, is suggested.

Gait disorders are a fundamental challenge in Parkinson’s disease (PD). The use of laser-light visual cues emitted from shoes has demonstrated effective in improving freezing of gait within less restrictive environments. However, the effectiveness of shoes-based laser-light cueing may vary among individuals with PD who have different types of impairments. We introduced an innovative laser-light visual shoes system capable of producing alternating visual cues for the left and right feet through one-side cueing at a time, while simultaneously recording foot inertial data and foot pressures. The effects of this visual cueing system on gait patterns were assessed in individuals with PD, both those with well-gait and those with worse-gait. Our device successfully quantified gait characteristics, including the asymmetry in the center of pressure trajectory, in individuals with PD. Furthermore, visual cueing prolonged stride times and increased the percentage of stance phase, while concurrently reducing stride length in PD individuals with well-gait. Conversely, in PD individuals with worse-gait, visual cueing resulted in a decreased freeze index and a reduction in the proportion of intervals prone to freezing episodes. The effects of visual cueing varied between PD individuals with well-gait and those with worse-gait. Visual cueing slowed down gait in the well-gait group while it appeared to mitigate freezing episodes in worse-gait group. Future researches, including enhancements to extend the projection distance of visual cues and clinical assessments conducted in real-world settings, will help establish the clinical utility of our proposed visual cueing system.

Dual cognitive-walking treadmill training (DTT), designed to replicate real-life walking conditions, has shown promise effect in individuals with Parkinson’s disease (PD). This study aims to compare the effects of DTT versus single treadmill training (STT) on cognitive and walking performance under both single and dual task conditions, as well as on fall, patients’ subjective feeling, and quality of life. Sixteen individuals with PD were randomly assigned to DTT or STT group and underwent 8 weeks of training. The DTT group received treadmill training with cognitive loads, while the STT group received treadmill training without cognitive load. Outcome measures included gait parameters (speed, step length) and cognitive performance (reaction time, accuracy, composite score) under both single and dual task conditions. Unified Parkinson’s Disease Rating Scale-part III (UPDRS-III), Falls Efficacy Scale (FES), Patient Global Impression of Change (PGIC), and Parkinson’s Disease Questionnaire (PDQ-39) were also measured. Both DTT and STT groups showed increased comfortable walking speed and step length. Only the DTT group demonstrated significant improvements in cognitive composite score under both single and dual task conditions, as well as UPDRS-III, FES, and PDQ-39(p < 0.05). DTT can enhance cognitive function without compromising walking ability and also have real-world transferability.

Objective. Start hesitation is a key issue for individuals with Parkinson's disease (PD) during gait initiation. Visual cues have proven effective in enhancing gait initiation. When applied to laser-light shoes, swing-limb detection efficiently activates the laser on the side of the stance limb, prompting the opposite swing limb to initiate stepping. Approach. This paper presents the development of two models for this purpose: a convolutional neural network that predicts the swing limb's side using center of pressure data, and a swing onset detection model based on sequential hypothesis test using foot pressure data. Main results. Our findings demonstrate an accuracy rate of 85.4% in predicting the swing limb's side, with 82.4% of swing onsets correctly detected within 0.05 s. Significance. This study demonstrates the efficiency of swing-limb detection based on foot pressures. Future research aims to comprehensively assess the impact of this method on improving gait initiation in individuals with PD.

Robot-assisted bilateral arm training has demonstrated its effectiveness in improving motor function in individuals post-stroke, showing significant enhancements with increased repetitions. However, prolonged training sessions may lead to both mental and muscle fatigue. We conducted two types of robot-assisted bimanual wrist exercises on 16 healthy adults, separated by one week: long-duration, low-resistance workouts and short-duration, high-resistance exercises. Various measures, including surface electromyograms, near-infrared spectroscopy, heart rate, and the Borg Rating of Perceived Exertion scale, were employed to assess fatigue levels and the impacts of exercise intensity. High-resistance exercise resulted in a more pronounced decline in electromyogram median frequency and recruited a greater amount of hemoglobin, indicating increased muscle fatigue and a higher metabolic demand to cope with the intensified workload. Additionally, high-resistance exercise led to increased sympathetic activation and a greater sense of exertion. Conversely, engaging in low-resistance exercises proved beneficial for reducing post-exercise muscle stiffness and enhancing muscle elasticity. Choosing a low-resistance setting for robot-assisted wrist movements offers advantages by alleviating mental and physiological loads. The reduced training intensity can be further optimized by enabling extended exercise periods while maintaining an approximate dosage compared to high-resistance exercises.

Abstract Background Parkinson’s disease (PD) is a neurogenerative disorder implicated in dysfunctions of motor functions, particularly gait and balance. Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation offered as a potential adjuvant therapy for PD. This systematic review and meta-analysis were conducted to identify whether tDCS alone and combined with additional rehabilitation therapies improve gait and balance among individuals with PD. Methods We searched PubMed, Embase, Web of Science, and relevant databases for eligible studies from inception to December 2022. Studies with a comparative design investigating the effects of tDCS on motor functions, including gait and balance among individuals with PD, were included. A meta-analysis was performed for each outcome using a random effects model for subgroup analysis and pooling of overall effect sizes. Results A total of 23 studies were included in the meta-analysis. The pooled results revealed that tDCS has moderate overall effects on gait, measured by gait speed (standardized mean deviation [SMD] = 0.238; 95% confidence interval [CI] − 0.026 to 0.502); stride length (SMD = 0.318; 95% CI − 0.015 to 0.652); cadence (SMD = − 0.632; 95% CI − 0.932 to − 0.333); freezing of gait questionnaire scores (SMD = − 0.360; 95% CI − 0.692 to − 0.027); step length (SMD = 0.459; 95% CI − 0.031 to 0.949); walking time (SMD = − 0.253; 95% CI − 0.758 to 0.252); stride time (SMD = − 0.785; 95% CI: − 1.680 to 0.111); double support time (SMD = 1.139; 95% CI − 0.244 to 0.523); and balance, measured by timed up and go (TUG) test (SMD = − 0.294; 95% CI − 0.516 to − 0.073), Berg balance scale (BBS) scores (SMD = 0.406; 95% CI − 0.059 to 0.87), and dynamic gait index (SMD = 0.275; 95% CI − 0.349 to 0.898). For the subgroup analysis, gait and balance demonstrated moderate effect sizes. However, only cadence, stride time, and TUG indicated a significant difference between real and sham tDCS (P = 0.027, P = 0.002, and P = 0.023, respectively), whereas cadence and BBS (P < 0.01 and P = 0.045, respectively) significantly differed after real tDCS plus other therapies rather than after sham tDCS plus other therapies. Conclusions Our results indicated that tDCS is significantly associated with gait and balance improvements among individuals with PD. The findings of this study provide more proof supporting the effectiveness of tDCS, encouraging tDCS to be utilized alone or in combination with other therapies in clinical practice for PD rehabilitation.

Background Various neurocognitive tests have shown that cycling enhances cognitive performance compared to resting. Event-related potentials (ERPs) elicited by an oddball or flanker task have clarified the impact of dual-task cycling on perception and attention. In this study, we investigate the effect of cycling on cognitive recruitment during tasks that involve not only stimulus identification but also semantic processing and memory retention.Methods We recruited 24 healthy young adults (12 males, 12 females; mean age = 22.71, SD = 1.97 years) to perform three neurocognitive tasks (namely color-word matching, arithmetic calculation, and spatial working memory) at rest and while cycling, employing a within-subject design with rest/cycling counterbalancing.Results The reaction time on the spatial working memory task was faster while cycling than at rest at a level approaching statistical significance. The commission error percentage on the color-word matching task was significantly lower at rest than while cycling. Dual-task cycling while responding to neurocognitive tests elicited the following results: (a) a greater ERP P1 amplitude, delayed P3a latency, less negative N4, and less positivity in the late slow wave (LSW) during color-word matching; (b) a greater P1 amplitude during memory encoding and smaller posterior negativity during memory retention on the spatial working memory task; and (c) a smaller P3 amplitude, followed by a more negative N4 and less LSW positivity during arithmetic calculation.Conclusion The encoding of color-word and spatial information while cycling may have resulted in compensatory visual processing and attention allocation to cope with the additional cycling task load. The dual-task cycling and cognitive performance reduced the demands of semantic processing for color-word matching and the cognitive load associated with temporarily suspending spatial information. While dual-tasking may have required enhanced semantic processing to initiate mental arithmetic, a compensatory decrement was noted during arithmetic calculation. These significant neurocognitive findings demonstrate the effect of cycling on semantic-demand and memory retention-demand tasks.

Fall detection and physical activity (PA) classification are important health maintenance issues for the elderly and people with mobility dysfunctions. The literature review showed that most studies concerning fall detection and PA classification addressed these issues individually, and many were based on inertial sensing from the trunk and upper extremities. While shoes are common footwear in daily off-bed activities, most of the aforementioned studies did not focus much on shoe-based measurements. In this paper, we propose a novel footwear approach to detect falls and classify various types of PAs based on a convolutional neural network and recurrent neural network hybrid. The footwear-based detections using deep-learning technology were demonstrated to be efficient based on the data collected from 32 participants, each performing simulated falls and various types of PAs: fall detection with inertial measures had a higher F1-score than detection using foot pressures; the detections of dynamic PAs (jump, jog, walks) had higher F1-scores while using inertial measures, whereas the detections of static PAs (sit, stand) had higher F1-scores while using foot pressures; the combination of foot pressures and inertial measures was most efficient in detecting fall, static, and dynamic PAs.

Abstract Introduction Stressful conditions can impact our judgement and increase the risk of adverse events such as workplace accidents, falls, and automobile collisions, among others. Sleep quality has also been shown to influence stress responses and heart rate variability (HRV) has proved to be a useful indicator of stress in a variety of scenarios. Therefore, wearable devices such as heart rate monitors may be able to reduce adverse events by measuring stress responses. Among subjects reporting different sleep quality, we measured heart rate variability (HRV) before and after different stressors to understand whether these stressful events could be detected by a wearable device. Methods Twenty-four subjects (male = 10; female = 14) with no known health conditions participated in this study. Subjects were divided into good sleep quality (N = 12) and bad sleep quality (N = 12) groups based on their Pittsburgh Sleep Quality Index (PSQI) score. Each subject engaged in a physical stress and mental stress on separate days and HRV was assessed before and after each stress intervention. T-tests were used to assess the change in HRV from pre- to post stress condition for each group. Results In the good sleep quality group we found several statistically significant differences across several HRV frequency-domains before and after physical stress (Low frequency: p = 0.0292; High frequency: p = 0.0287; Low frequency/ High frequency ratio: p = 0.0245) and mental stress (Low frequency: p = 0.0394; High frequency: p = 0.0387; Low frequency/ High frequency ratio: p = 0.0373). Conclusion Our findings indicate that sleep quality may influence the HRV response to different stressors. This suggests that HRV measured via wearable device may be used to provide warning under stressful conditions that could help prevent accidents and other adverse events. Support (if any)

To safely walk in a community environment requires dual cognitive-walking ambulation ability for people with Parkinson's disease (PD). A past study showed inconsistent results on cognitive-walking performance for PD patients, possibly due to the various cognitive tasks used and task priority assignment. This study designed cognitive-walking tests that used executive-related cognitive tasks to evaluate patients with early-stage Parkinson's disease who did not have obvious cognitive deficits. The effect of assigning task prioritization was also evaluated. Sixteen individuals with PD (PD group) and 16 individuals without PD (control group) underwent single cognitive tests, single walking tests, dual walking tests, and prioritizing task tests. Three types of cognitive, spatial memory, Stroops, and calculation tasks were employed. The cognitive performance was evaluated by response time, accuracy, and speed-accuracy trade off composite score. The walking performance was evaluated by the temporal spatial gait characteristics and variation in gait. The results showed that the walking performance of the PD group was significantly worse than the control group in both single and dual walking conditions. The group difference in cognitive performance was shown in composite score under the dual calculation walking task but not under the single task. While assigning priority to walking, no group difference in walking was observed but the response accuracy rate of PD groups declined. This study concluded that the dual task walking test could sharpen the cognitive deficits for early-stage PD patients. The task priority assignment might not be recommended while testing gait deficits since it decreased the ability to discriminate group differences.

Objective: To examine the effects of bilateral robotic priming combined with mirror therapy (R-mirr) vs bilateral robotic priming combined with bilateral arm training (R-bilat), relative to the control approach of bilateral robotic priming combined with movement-oriented training (R-mov) in patients with stroke.Design: A single-blind, preliminary, randomized controlled trial. Setting: Four outpatient rehabilitation settings.Participants: Outpatients with stroke and mild to moderate motor impairment (N=63).Interventions: Patients received 6 weeks of clinic-based R-mirr, R-bilat, or R-mov for 90 min/d, 3 d/wk, plus a transfer package at home for 5 d/wk.Main Outcome Measures: Fugl-Meyer Assessment Upper Extremity subscale (FMA-UE), ABILHAND, and Stroke Impact Scale v3.0 scores before, immediately after, and 3 months after treatment as well as lateral pinch strength and accelerometry before and immediately after treatment.Results: The posttest results favored R-mirr over R-bilat and R-mov on the FMA-UE score (P<.05). Follow-up analysis revealed that significant improvement in FMA-UE score was retained at the 3-month follow-up in the R-mirr over R-bilat or R-mov (P<.05). Significant improvements were not observed in the R-mirr over R-bilat and R-mov on other outcomes.Conclusions: Between-group differences were only detected for the primary outcome, FMA-UE. R-mirr was more effective at enhancing upper limb motor improvement, and the effect has the potential to be maintained at 3 months of follow-up. Archives of Physical Medicine and Rehabilitation 2023;104:1195-202 & COPY; 2023 by the American Congress of Rehabilitation Medicine.

An information compensation method to reduce motion sickness caused by reading information on the transparent window display has been studied and proposed. In this research, Visual Analogue Scale (VAS), Center of Pressure(CoP), Simulator sickness questionnaire (SSQ) and Heart Rate Variability (HRV) were conducted and the data analysis revealed that the information compensation based on the degree of vehicle vibration improved the comfort of reading the text information for passengers.

The fusion information on the side window of the car may cause the passenger's motion sickness as moving. This motion sickness mixed the visual‐induced and caused by riding a vehicle. In this research, we propose a method of the reference image to solve reduce motion sickness and used the MSSQ‐short to judge motion sickness degree.