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Stroke can impair mobility, with deficits more pronounced while simultaneously performing multiple activities. In this study, common clinical tests were instrumented with wearable motion sensors to study motor-cognitive interference effects in stroke survivors (SS). A total of 21 SS and 20 healthy controls performed the Timed Up and Go (TUG), Sit-to-Stand (STS), balance, and 10-Meter Walk (10MWT) tests under single and dual-task (counting backward) conditions. Calculated measures included total time and gait measures for TUG, STS, and 10MWT. Balance tests for both open and closed eyes conditions were assessed using sway, measured using the linear acceleration of the thorax, pelvis, and thighs. SS exhibited poorer performance with slower TUG (16.15 s vs. 13.34 s, single-task p < 0.001), greater sway in the eyes open balance test (0.1 m/s 2 vs. 0.08 m/s 2 , p = 0.035), and slower 10MWT (12.94 s vs. 10.98 s p = 0.01) compared to the controls. Dual tasking increased the TUG time (~14%, p < 0.001), balance thorax sway (~64%, p < 0.001), and 10MWT time (~17%, p < 0.001) in the SS group. Interaction effects were minimal, suggesting similar dual-task costs. The findings demonstrate exaggerated mobility deficits in SS during dual-task clinical testing. Dual-task assessments may be more effective in revealing impairments. Integrating cognitive challenges into evaluation can optimize the identification of fall risks and personalize interventions targeting identified cognitive-motor limitations post stroke.

Clinical tests like Timed Up and Go (TUG) facilitate the assessment of post-stroke mobility, but they lack detailed measures. In this study, 21 stroke survivors and 20 control participants underwent TUG, sit-to-stand (STS), and the 10 Meter Walk Test (10MWT). Tests incorporated single tasks (STs) and motor-cognitive dual-task (DTs) involving reverse counting from 200 in decrements of 10. Eight wearable motion sensors were placed on feet, shanks, thighs, sacrum, and sternum to record kinematic data. These data were analyzed to investigate the effects of stroke and DT conditions on the extracted features across segmented portions of the tests. The findings showed that stroke survivors (SS) took 23% longer for total TUG ( p < 0.001), with 31% longer turn time ( p = 0.035). TUG time increased by 20% ( p < 0.001) from STs to DTs. In DTs, turning time increased by 31% ( p = 0.005). Specifically, SS showed 20% lower trunk angular velocity in sit-to-stand ( p = 0.003), 21% longer 10-Meter Walk time ( p = 0.010), and 18% slower gait speed ( p = 0.012). As expected, turning was especially challenging and worsened with divided attention. The outcomes of our study demonstrate the benefits of instrumented clinical tests and DTs in effectively identifying motor deficits post-stroke across sitting, standing, walking, and turning activities, thereby indicating that quantitative motion analysis can optimize rehabilitation procedures.

Background: Falls are common and dangerous for stroke survivors. Current fall risk assessment methods rely on subjective scales. Objective sensor-based methods could improve prediction accuracy., Objective: Develop machine learning models using inertial sensors to objectively classify fall risk in stroke survivors. Determine optimal sensor configurations and clinical test protocols., Methods: 21 stroke survivors performed balance, Timed Up and Go, 10 Meter Walk, and Sit-to-Stand tests with and without dual-tasking. A total of 8 motion sensors captured lower limb and trunk kinematics, and 92 spatiotemporal gait and clinical features were extracted. Supervised models-Support Vector Machine, Logistic Regression, and Random Forest-were implemented to classify high vs. low fall risk. Sensor setups and test combinations were evaluated., Results: The Random Forest model achieved 91% accuracy using dual-task balance sway and Timed Up and Go walk time features. Single thorax sensor models performed similarly to multi-sensor models. Balance and Timed Up and Go best-predicted fall risk., Conclusion: Machine learning models using minimal inertial sensors during clinical assessments can accurately quantify fall risk in stroke survivors. Single thorax sensor setups are effective. Findings demonstrate a feasible objective fall screening approach to assist rehabilitation.

The digital world has recently experienced a swift rise in worldwide popularity due to Virtual (VR) and Augmented Reality (AR) devices. However, concrete evidence about the effects of VR/AR devices on the physical workload imposed on the human body is lacking. We reviewed 27 articles that evaluated the physical impact of VR/AR-based tasks on the users using biomechanical sensing equipment and subjective tools. Findings revealed that movement and muscle demands (neck and shoulder) varied in seven and five studies while using VR, while in four and three studies during AR use, respectively, compared to traditional methods. User discomfort was also found in seven VR and three AR studies. Outcomes indicate that interface and interaction design, precisely target locations (gestures, viewing), design of virtual elements, and device type (location of CG as in Head-Mounted Displays) influence these alterations in neck and shoulder regions. Recommendations based on the review include developing comfortable reach envelopes for gestures, improving wearability, and studying temporal effects of repetitive movements (such as effects on fatigue and stability). Finally, a guideline is provided to assist researchers in conducting effective evaluations. The presented findings from this review could benefit designers/evaluations working towards developing more effective VR/AR products., (© 2023. The Author(s) under exclusive licence to Biomedical Engineering Society.)

Industrial tasks that involve frequent sitting/standing transitions and squatting activities can benefit from lower-limb industrial exoskeletons; however, their use is not as widespread as their upper-body counterparts. In this review, we examined 23 articles that evaluated the effects of using Wearable Chair (WC) and Squat-assist (SA) exoskeletons. Evaluations mainly included assessment of muscular demands in the thigh, shank, and upper/lower back regions. Both types of devices were found to lessen muscular demands in the lower body by 30-90%. WCs also reduced low-back demands (~ 37%) and plantar pressure (54-80%) but caused discomfort/unsafe feeling in participants. To generalize outcomes, we suggest standardizing approaches used for evaluating the devices. Along with addressing low adoption through design upgrades (e.g., ground and body supports/attachments), we recommend that researchers thoroughly evaluate temporal effects on muscle fatigue, metabolic rate, and stability of wearers. Although lower-limb exoskeletons were found to be beneficial, discrepancies in experimental protocols (posture/task/measures) were discovered. We also suggest simulating more realistic conditions, such as walking/sitting interchangeability for WCs and lifting loads for SA devices. The presented outcomes could help improve the design/evaluation approaches, and implementation of lower limb wearable devices across industries., (© 2023. The Author(s) under exclusive licence to Biomedical Engineering Society.)

With rising manual work demands, physical assistance at the workplace is crucial, wherein the use of industrial exoskeletons (i-EXOs) could be advantageous. However, outcomes of numerous laboratory studies may not be directly translated to field environments. To explore this discrepancy, we conducted a systematic review including 31 studies to identify and compare the approaches, techniques, and outcomes within field assessments of shoulder and back support i-EXOs. Findings revealed that the subjective approaches [i.e., discomfort (23), usability (22), acceptance/perspectives (21), risk of injury (8), posture (3), perceived workload (2)] were reported more common (27) compared to objective (15) approaches [muscular demand (14), kinematics (8), metabolic costs (5)]. High variability was also observed in the experimental methodologies, including control over activity, task physics/duration, sample size, and reported metrics/measures. In the current study, the detailed approaches, their subject-related factors, and observed trends have been discussed. In sum, a new guideline, including tools/technologies has been proposed that could be utilized for field evaluation of i-EXOs. Lastly, we discussed some of the common technical challenges experimenters face in evaluating i-EXOs in field environments. Efforts presented in this study seek to improve the generalizability in testing and implementing i-EXOs., (© 2022. The Author(s) under exclusive licence to Biomedical Engineering Society.)

Background: A stroke often bequeaths surviving patients with impaired neuromusculoskeletal systems subjecting them to increased risk of injury (e.g., due to falls) even during activities of daily living. The risk of injuries to such individuals can be related to alterations in their movement. Using inertial sensors to record the digital biomarkers during turning could reveal the relevant turning alterations., Objectives: In this study, movement alterations in stroke survivors (SS) were studied and compared to healthy individuals (HI) in the entire turning task due to its requirement of synergistic application of multiple bodily systems., Methods: The motion of 28 participants (14 SS, 14 HI) during turning was captured using a set of four Inertial Measurement Units, placed on their sternum, sacrum, and both shanks. The motion signals were segmented using the temporal and spatial segmentation of the data from the leading and trailing shanks. Several kinematic parameters, including the range of motion and angular velocity of the four body segments, turning time, the number of cycles involved in the turning task, and portion of the stance phase while turning, were extracted for each participant., Results: The results of temporal processing of the data and comparison between the SS and HI showed that SS had more cycles involved in turning, turn duration, stance phase, range of motion in flexion-extension, and lateral bending for sternum and sacrum ( p -value < 0.035). However, HI exhibited larger angular velocity in flexion-extension for all four segments. The results of the spatial processing, in agreement with the prior method, showed no difference between the range of motion in flexion-extension of both shanks ( p -value > 0.08). However, it revealed that the angular velocity of the shanks of leading and trailing legs in the direction of turn was more extensive in the HI ( p -value < 0.01)., Conclusions: The changes in upper/lower body segments of SS could be adequately identified and quantified by IMU sensors. The identified kinematic changes in SS, such as the lower flexion-extension angular velocity of the four body segments and larger lateral bending range of motion in sternum and sacrum compared to HI in turning, could be due to the lack of proper core stability and effect of turning on vestibular system of the participants. This research could facilitate the development of a targeted and efficient rehabilitation program focusing on the affected aspects of turning movement for the stroke community.

Stroke survivors often experience reduced movement capabilities due to alterations in their neuromusculoskeletal systems. Modern sensor technologies and motion analyses can facilitate the determination of these changes. Our work aims to assess the potential of using wearable motion sensors to analyze the movement of stroke survivors and identifying the affected functions. We recruited 10 participants (5 stroke survivors, 5 healthy individuals) and conducted a controlled laboratory evaluation for two of the most common daily activities: turning and walking. Among the extracted kinematic parameters, range of trunk and sacrum lateral bending in turning were significantly larger in stroke survivors (p-value<0.02). However, no statistical difference in mean angular velocity and range of motion for trunk/sacrum/shank flexion-extension were obtained in the turning task. Our results also indicated that during walking, while there was no difference in swing time, double support portion of gait among the stroke group was significantly larger (p-value = 0.001). Outcomes of this investigation may help in designing new rehabilitation programs for stroke and other neurological disorders and/or in improving the efficacy of such programs.Clinical Relevance- This study may provide a better insight on the detailed functional differences between stroke survivors and healthy individuals which in turn could be used to develop a more efficient rehabilitation program for stroke community.