Sirinun Boripuntakul

Background/Objectives: Markerless video-based gait assessment has emerged as a promising alternative to laboratory motion capture systems because it enables objective, low-cost, and accessible mobility assessment. However, evidence supporting the validity of deep learning (DL)-based markerless video systems for gait speed assessment during the 10-meter walk test (10-MWT) in real-world clinical environments remains limited. This study evaluated the concurrent validity of a DL-based markerless video system for estimating gait speed during the 10-MWT under outdoor clinical conditions. Methods: Thirty-two healthy participants from three age groups completed the 10-MWT under comfortable, slow, and fast walking conditions. Gait speed was simultaneously measured using the proposed DL-based markerless video system with the YOLOv11x model and Tracker video analysis software (version 6.3.2). Gait speed was calculated across six consecutive 1 m walking segments. Concurrent validity was evaluated using Pearson’s correlation coefficients and Bland-Altman analysis. Results: Pearson’s correlation coefficients ranged from 0.92 to 0.98 across all six walking segments and walking-speed conditions, indicating very high concurrent validity. Bland-Altman analysis demonstrated good agreement between the proposed system and the reference method, with mean differences close to zero and most observations falling within the 95% limits of agreement. The proposed system maintained high agreement across comfortable, slow, and fast walking conditions while enabling segment-specific gait speed analysis throughout the 10-MWT. Conclusions: The proposed DL-based markerless video system demonstrated high agreement with Tracker for gait speed assessment during the 10-MWT under outdoor non-laboratory conditions, supporting its potential as an accessible approach for gait speed assessment.

As stroke survivors often manifest not only physical dysfunction but also cognitive impairment, interventions that address both physical and cognitive aspects may be beneficial for individuals with chronic stroke. However, a randomized clinical trial (RCT) examining the effects of physical–cognitive telerehabilitation exergaming across physical and cognitive domains in chronic stroke survivors remains scarce. Therefore, this study aims to investigate the effectiveness of the web-based physical–cognitive telerehabilitation exergaming on the physical and cognitive performance of chronic stroke survivors as compared to control. A two-arm RCT with a blinded assessor will be conducted. Fifty-two participants will be randomly assigned to either the intervention or the control group. Participants in the intervention group will receive a 12-week training program, whereas those in the control group will continue with usual care. Motor function, gait speed, balance, fall risk, muscle power, weight distribution, body composition, global cognition, executive function, attention, memory, as well as enjoyment will be assessed. Existing evidence has established the health benefits of physical–cognitive exergaming. It is expected that a physical–cognitive exergaming program may further exhibit positive effects on both physical function and cognition beyond the results of usual care. In addition, incorporating physical–cognitive training into a web-based telerehabilitation program may improve adherence and provide a feasible and enjoyable rehabilitation option for individuals with chronic stroke.

Background: Trunk impairment is an important clinical feature in children with cerebral palsy (CP), therefore assessment of trunk control is a crucial part of functional assessment in children with CP. Objectives: The study aimed to translate the Trunk Control Measurement Scale (TCMS) from the original English into a Thai version and demonstrate the reliability and validity of the TCMS-TH among children with spastic CP. Materials and methods: The TCMS was translated using standard cross-cultural adaptation guidelines. The final TCMS-TH was tested on 29 children with spastic CP aged 5-15 years. For inter-rater reliability, two assessors independently scored the children from the video recording using the TCMS-TH. One month after the first assessment, a second assessment was performed to determine intra-rater reliability. The convergent validity of the TCMS-TH was assessed by comparison to the Gross Motor Function Measure (GMFM-88). The intraclass correlation coefficient (ICC) and Pearson’s correlation coefficient were used to analyze reliability and validity. Results: The TCMS-TH had good internal consistency, with Cronbach’s alpha = 0.916 for the total TCMS-TH. Inter-rater reliability was good to excellent, ICC = 0.837-0.955, whereas intra-rater reliability was excellent, ICC =0.918-0.995. The TCMS-TH and the GMFM has moderate to high correlation (r=0.631-0.810). Conclusion: The TCMS-TH is a reliable and valid tool for assessing trunk control in children with spastic CP. However, its outcomes are primarily generalizable to observations obtained from video recordings rather than direct in-person assessments. Despite this limitation, the TCMS-TH remains a valuable tool for both clinical practice and research settings.

Background: Combined physical–cognitive training has shown beneficial effects on cognition in older adults with mild cognitive impairment (MCI). However, most interventions employ moderate-to-high intensity, which may limit accessibility for individuals with health concerns. Whether low-intensity exercise provides similar cognitive benefits remains inconclusive. Delivering such training through home-based exergame may improve adherence. This study evaluated the feasibility of a home-based, low-intensity exergame for older adults with MCI. Methods: Older adults with MCI completed 50-min exergaming sessions, triweekly, for 4 weeks. Feasibility outcomes, including recruitment, adherence, adverse events, enjoyment, and cognitive and physical performance, were evaluated at baseline and post-intervention. Cognitive performance was assessed using the Montreal Cognitive Assessment (MoCA), 10-word recall test, digit span, and verbal fluency tests. Physical performance was assessed with the four-square step and five-times sit-to-stand tests. Results: Fifteen older adults with MCI (mean age 66.07 ± 4.36 years; 75% recruitment rate) participated. The average adherence rate was 93.33% (11.2 sessions), with no adverse events or attrition reported. Enjoyment significantly increased from week 1 to week 4 ( p = 0.001). Significant cognitive improvements were demonstrated for the 10-word immediate and delayed recall ( p = 0.03, p = 0.002), MoCA total scores ( p = 0.002), and MoCA sub-domains: executive function ( p = 0.007), language ( p = 0.034), and delayed recall ( p = 0.001). No significant changes were observed in physical performance. Conclusion: Home-based, low-intensity exergaming is a safe, feasible, and enjoyable approach for older adults with MCI. Preliminary findings suggest potential cognitive benefits of low-intensity exergaming in improving cognitive function, which warrant confirmation in a large-scale, rigorous randomized controlled trial.

Background: The 10-meter walk test (10MWT) is a useful field test for gait speed assessment in older adults. However, the conventional 10MWT only provides an overall average gait speed and does not monitor changes in gait speed at specific times. A computer vision-based system is a markerless motion-tracking technology that detects an individual’s instantaneous gait speed, providing valuable insights into gait control. Objective: This cross-sectional study aimed to investigate: 1) the concurrent validity of a computer vision-based system against a motion analysis system for capturing instantaneous gait speed in the 10MWT; 2) the test-retest reliability of gait speed measures obtained from a computer vision-based system in the 10MWT; and 3) the usability of a computer vision-based system for gait speed assessment during the 10MWT in free-living environments. Methods: In the validity and reliability testing phase, ten older adults (mean age = 67.50 (6.36) years) participated. Participants performed the 10MWT under two walking conditions: walking at a comfortable speed and walking at maximum speed. For the validity testing, the instantaneous gait speed obtained from a computer vision-based system was compared against that from a motion analysis system. After 30 minutes, the same protocol was repeated to assess the test-retest reliability of a computer vision-based system. The outcome measures were the average instantaneous gait speed for each meter (i.e., meters 0-1, 1-2, 2-3, 3-4, 4-5, and 5-6). In the usability testing phase, six physical therapists (mean age = 26.83 (0.98) years) were asked to test a computer vision-based system for 10MWT assessment in a free-living environment. After completing the test, they were asked to rate the perceived usability of a computer vision-based system using the System Usability Scale (SUS). A Spearman's rank correlation was used to determine a correlation between a computer vision-based system and a motion analysis system, with significance set at P-value < 0.05. An intraclass correlation coefficient (ICCs (3,2)) was used to test the agreement between two repeated sessions of a computer vision-based system. Descriptive statistics were employed to analyze the SUS score. Results: The average gait speed obtained from a computer vision-based system and a motion analysis system showed high to very high agreement in all meters across two walking conditions, with correlations ranging from 0.70 to 1.00 (P-value < 0.05). The average walking speed measured by a computer vision-based system demonstrated very high repeatability across two sessions for all walking conditions, with ICCs falling between 0.940 and 0.986. The total SUS score for all participants was 75.83 (7.36), suggesting a good perception of the system's usability. Conclusion: A computer vision-based system is accurate, consistent, and acceptably user-friendly, making it a promising approach for measuring instantaneous gait speed of the 10MWT. However, the proposed system would need to be improved in terms of feasibility for use in community-based settings.

Background: Declines in physical and cognitive function are natural biological processes, leading to an increased risk of falls. Promising evidence suggests that combined physical-cognitive exercise has beneficial effects in improving both physical and cognitive health. Although moderate-to-high exercise intensity is commonly recommended, it might be impractical for older adults facing physical limitations or contraindications. Thus, low-intensity exercise is a viable option. The main barriers to engaging in exercise in older adults include transportation, time, motivation, and enjoyment. To overcome these challenges, a home-based, gamification-based training system may provide an effective approach to enhance exercise adherence. Objective: This study aimed to develop and evaluate the usability of a low-intensity, gamification-based, interactive physical-cognitive exercise for older adults in a home-based setting. Methods: The prototype of a game-based physical-cognitive exercise was created following the ADDIE model (analysis, design, development, implementation, and evaluation) and assessed for user experience in older adults. A total of 15 older adults engaged in the game-based physical-cognitive exercise at home for 60 minutes per day, 3 days per week, for 4 weeks. The usability of the game-based training system was evaluated using the system usability scale (SUS) after completion of a 4-week training program. As for satisfaction, the 8-item Physical Activity Enjoyment Scale (PACES) questionnaire was used to assess participants’ enjoyment level after 1 week and 4 weeks of training. Descriptive statistics were used to illustrate the SUS score. A Wilcoxon signed-rank test was used to compare the PACES scores between the first week and the end of the 4-week period, with significance set at P<.05. Results: As for experts’ consensus, the game-based training consisted of 3 games: Ocean Diver, Road Runner, and Moving and Memorizing. The games had 3 levels of difficulty: beginner, intermediate, and advanced. A computer vision–based system was selected as the delivery platform for a home setting. The total SUS score for all participants was mean 87.22 (SD 5.76), indicating the user’s perception of the usability of a system ranging from good to excellent. At the end of the 4-week training, the total PACES score was significantly greater than the first week, suggesting an improvement in enjoyment (first week: mean 44.93, SD 3.99 vs fourth week: mean 50.53, SD 4.70; P=.001). Conclusions: The prototype of low-intensity, gamification-based, interactive physical-cognitive training was designed and developed using the ADDIE model, which included both experts and end users in the process. The findings showed that the exergame prototype was a usable and practical approach for a home-based setting, enhancing older adults’ enjoyment and motivation. Further research is warranted to determine the effectiveness of such gamification-based training in promoting physical and cognitive functions.

Early signs of Mild Cognitive Impairment (MCI)-related gait deficits may be detected through the performance of complex walking tasks that require high gait control. Gait smoothness is a robust metric of overall body stability during walking. This study aimed to explore gait smoothness during complex walking tasks in older adults with and without MCI. Participants were 18 older adults with MCI (mean age = 67.89 ± 4.64 years) and 18 cognitively intact controls (mean age = 67.72 ± 4.63 years). Gait assessment was conducted under four complex walking tasks: walking a narrow path, walking around an obstacle, horizontal head turns while walking, and vertical head turns while walking. The index of harmonicity (IH), representing gait smoothness associated with overall body stability, was measured in anteroposterior, mediolateral, and vertical directions. A multivariate analysis was employed to compare the differences in IH between groups for each complex walking task. The MCI group demonstrated a reduction of IH in the mediolateral direction during the horizontal head turns than the control group (MCI group = 0.64 ± 0.16, Control group = 0.74 ± 0.12, p = 0.04). No significant differences between groups were found for the IH in other directions or walking conditions. These preliminary findings indicate that older adults with MCI have a decline in step regularity in the mediolateral direction during walking with horizontal head turns. Assessment of the smoothness of walking during head turns may be a useful approach to identifying subtle gait alterations in older adults with MCI, which may facilitate timely gait intervention.

The Timed Up and Go Test (TUG) is a simple fall risk screening test that covers basic functional movement; thus, quantifying the subtask movement ability may provide a clinical utility. The video-based system allows individual’s movement characteristics assessment. This study aimed to investigate the concurrent validity and test-retest reliability of the video-based system for assessing the movement speed of TUG subtasks among older adults. Twenty older adults participated in the validity study, whilst ten older adults participated in the reliability study. Participant’s movement speed in each subtask of the TUG under comfortable and fast speed conditions over two sessions was measured. Pearson correlation coefficient was used to identify the validity of the video-based system compared to the motion analysis system. Intraclass correlation coefficient (ICC3,2) was used to determine the reliability of the video-based system. The Bland-Altman plots were used to quantify the agreement between the two measurement systems and two repeatable sessions. The validity analysis demonstrated a moderate to very high relationship in all TUG subtask movement speeds between the two systems under the comfortable speed (r = 0.672–0.906, p < 0.05) and a moderate to high relationship under the fast speed (r = 0.681–0.876, p < 0.05). The reliability of the video-based system was good to excellent for all subtask movement speeds in both the comfortable speed (ICCs = 0.851–0.967, p < 0.05) and fast speed (ICCs = 0.720–0.979, p < 0.05). The Bland-Altman analyses showed that almost all mean differences of the subtask speed of the TUG were close to zero, within 95% limits of agreement, and symmetrical distribution of scatter plots. The video-based system was a valid and reliable tool that may be useful in measuring the subtask movement speed of TUG among healthy older adults.

Introduction: Obesity in middle-aged women markedly increases the risk for non-communicable diseases, neurodegenerative diseases, and physical and cognitive problems. Exercise, particularly combined physical-cognitive exercise, has been demonstrated to have beneficial effects on both physical and cognitive health. However, middle-aged women often face barriers to engaging in exercise, which include time constraints, lack of motivation, and enjoyment. Incorporating an exercise program into a technology-based intervention in the home environment may help overcome these barriers and promote health benefits. Therefore, this study aimed to assess the feasibility of home-based, physical-cognitive internet-based exercise for middle-aged obese women. Methods: A total of 33 middle-aged obese women were enrolled in the study. Participants performed an intervention for 60 min/day, 3 days/week for 3 months. Feasibility outcomes (adherence, adverse events, physical performances, obesity parameters, and enjoyment of the program) were measured. Results: Average exercise adherence was 91.67%, and no adverse events were reported in this feasibility study. At the end of the training period, body weight and BMI were significantly decreased compared to baseline. As for physical performances, both cardiorespiratory fitness and lower limb muscle power were significantly improved at post-training when compared to baseline. Furthermore, the participants experienced a high level of exercise enjoyment, and it was maintained over the 3-month training period. Conclusion: These findings suggest that home-based, internet-based physical-cognitive exercise was safe and feasible for reducing obesity parameters, improving physical function, maintaining enjoyment over the course of training, and facilitating adherence to exercise in middle-aged obese women.