IEEE ... International Conference on Rehabilitation Robotics : [proceedings]最新文献_第9页

Strategic User Identification Increases the Impact of Wearable Airbags in High-Fall Risk Populations with Neurological Disease. 战略性用户识别增加可穿戴安全气囊对患有神经系统疾病的高危人群的影响

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2025-05-01 DOI: 10.1109/ICORR66766.2025.11063031

Kyle R Embry, Sajjad Daneshgar, Katelyn Aragon, Arun Jayaraman

{"title":"Strategic User Identification Increases the Impact of Wearable Airbags in High-Fall Risk Populations with Neurological Disease.","authors":"Kyle R Embry, Sajjad Daneshgar, Katelyn Aragon, Arun Jayaraman","doi":"10.1109/ICORR66766.2025.11063031","DOIUrl":"https://doi.org/10.1109/ICORR66766.2025.11063031","url":null,"abstract":"Falls are a major health concern among older adults, particularly those with neurological conditions such as Parkinson's disease or stroke. Wearable airbags are a promising new technology that may help mitigate fall-related injuries. These devices use motion sensors, pre-impact fall detection algorithms, and CO2-powered airbags to cushion the impact of a fall. However, this technology is only needed for people with a high risk of falls, and it is only useful if the pre-impact fall detection algorithm successfully detects the fall. Our prior work showed that some individuals benefit more from one pre-impact fall detection algorithm than another due to their unique movement characteristics and biomechanics. This study aims to determine who may be suitable users for this technology by predicting future fall risk and categorizing users as 'responders' or 'non-responders' based on their predicted algorithm performance. We recruited 22 participants with neurological conditions in a six-month study design. Using baseline physical assessments, survey scores, and principal component analysis, we trained a logistic regression model that distinguished high-risk 'fallers' from 'non-fallers' with an average F1 score of 0.76. The model also identified 'responder' individuals, whose fall patterns were accurately detected, achieving an F1 score of 0.75. These findings suggest that identifying high fall risk users whose falls are best identified by a fall detection algorithm can enhance device effectiveness and maximize benefits for users.","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2025 ","pages":"121-127"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144612723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of Multimodal EEG-EMG Human Machine Interface for Hand-Wrist Rehabilitation: A Preliminary Study. 多模态脑电图-肌电图人机界面开发的初步研究。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2025-05-01 DOI: 10.1109/ICORR66766.2025.11063079

Minki Kim, SeongHyeon Jo, Hyeonseung Cho, Seungmin Ye, Yeongtae Kim, Hyung-Soon Park

{"title":"Development of Multimodal EEG-EMG Human Machine Interface for Hand-Wrist Rehabilitation: A Preliminary Study.","authors":"Minki Kim, SeongHyeon Jo, Hyeonseung Cho, Seungmin Ye, Yeongtae Kim, Hyung-Soon Park","doi":"10.1109/ICORR66766.2025.11063079","DOIUrl":"https://doi.org/10.1109/ICORR66766.2025.11063079","url":null,"abstract":"Patients with neurological disorders, such as stroke, often undergo upper limb motor impairments, severely limiting their ability to perform activities of daily living (ADL). Wearable robots have been developed to provide intensive and precise repetitive training for upper limb rehabilitation. Effective rehabilitation requires aligning robotic assistance with patient movement intention to promote brain plasticity. Additionally, robotic assistance must accommodate the complex, coordinated upper limb motions required for ADL tasks, including not only isolated hand movements but also integrated hand and wrist actions. This paper presents a multimodal human-machine interface (HMI) for integrated hand-wrist rehabilitation using both EEG and EMG signals. A three-degrees-of-freedom (3-DOF) soft wearable robot, combining a robotic hand glove and forearm skin brace, was designed to assist coordinated hand and wrist movements during reaching and grasping. EEG signals classified rest and grasp states using a Riemannian geometry approach, while EMG signals from three forearm muscles detected reaching onset to trigger the wrist adjustment. Preliminary tests with four healthy participants demonstrated 85% accuracy in EEG-based classification and sufficient EMG amplitude for motion onset detection. Future studies will expand participant testing to improve system robustness and evaluate its effectiveness for stroke rehabilitation.","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2025 ","pages":"1564-1569"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144612483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparative Analysis of Temporal Difference Learning Methods to Learn General Value Functions of Lower-Limb Signals. 学习下肢信号一般值函数的时间差分学习方法的比较分析。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2025-05-01 DOI: 10.1109/ICORR66766.2025.11063114

Sonny T Jones, Grange M Simpson, Wyatt M J Young, Kylee North, Patrick M Pilarski, Ashley N Dalrymple

{"title":"Comparative Analysis of Temporal Difference Learning Methods to Learn General Value Functions of Lower-Limb Signals.","authors":"Sonny T Jones, Grange M Simpson, Wyatt M J Young, Kylee North, Patrick M Pilarski, Ashley N Dalrymple","doi":"10.1109/ICORR66766.2025.11063114","DOIUrl":"https://doi.org/10.1109/ICORR66766.2025.11063114","url":null,"abstract":"Millions of people in the United States suffer from paralysis, resulting in significant deficits in motor function. Restricted mobility due to these deficits and the lack of adaptive rehabilitative solutions make traversing complex and challenging terrains unsafe. Exoskeletons offer a promising solution, but their effectiveness could be greatly enhanced by incorporating reinforcement learning algorithms for real-time adaptation to changing environments and the user's unique gait biomechanics. This study explored different temporal difference learning methods for predicting signals recorded from sensors on the lower-limbs, including muscle activation from electromyography, underfoot pressure, and joint angles from goniometers. Specifically, the performance of the temporal difference learning methods TD $(lambda)$, TOTD, and SwiftTD to quickly and accurately predict these signals was examined. From initial findings, SwiftTD generally converged faster, while TOTD typically achieved lower convergence errors. These outcomes varied depending on the specific signal that was being predicted, highlighting the need for careful consideration of algorithm choice depending on the signal, accuracy, and speed. The results, therefore, support the informed selection of specific algorithms for providing predictive knowledge to adaptive, machine learning-controlled assistive rehabilitative technologies. These findings will enable the selection of appropriate predictive algorithms, leading to the development of better exoskeletons and other assistive devices to enhance the mobility and quality of life of individuals with motor paralysis.","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2025 ","pages":"1209-1214"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144612527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Myoassist 0.1: Myosuite for Dexterity and Agility in Bionic Humans. Myoassist 0.1：用于仿生人的灵活性和敏捷性的Myosuite。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2025-05-01 DOI: 10.1109/ICORR66766.2025.11063089

Chun Kwang Tan, Cheryl Wang, Shirui Lyu, Balint K Hodossy, Pierre Schumacher, Elizabeth B Wilson, Vittorio Caggiano, Vikash Kumar, Dario Farina, Letizia Gionfrida, Elliott J Rouse, Guillaume Durandau, Seungmoon Song

{"title":"Myoassist 0.1: Myosuite for Dexterity and Agility in Bionic Humans.","authors":"Chun Kwang Tan, Cheryl Wang, Shirui Lyu, Balint K Hodossy, Pierre Schumacher, Elizabeth B Wilson, Vittorio Caggiano, Vikash Kumar, Dario Farina, Letizia Gionfrida, Elliott J Rouse, Guillaume Durandau, Seungmoon Song","doi":"10.1109/ICORR66766.2025.11063089","DOIUrl":"https://doi.org/10.1109/ICORR66766.2025.11063089","url":null,"abstract":"Accurate and reliable digital twins of humans and wearable robots can revolutionize rehabilitation robotics. Here, we introduce MyoAssist 0.1, a sub-suite of MyoSuite focused on musculoskeletal simulation environments with assistive devices such as prosthetics and exoskeletons. This open-source platform enables the study and development of human-device interactions, control strategies, and assistive robotics. We present two new simulation environments: myoMPL featuring an arm amputee model with a robotic prosthetic arm, and myoOSL featuring a leg amputee model with a robotic prosthetic leg. The myoMPL environment features a bimanual manipulation task for a shoulder disarticulation amputee using a Modular Prosthetic Limb (MPL), where the task is to pick up an object with the biological hand, pass it to the prosthetic hand, and place it at a target location. The myoOSL environment simulates an above-knee amputee using the Open-Source Leg (OSL) to traverse challenging terrains such as rough surfaces, hills, and stairs. Despite some simplifications in modeling the nuanced constraints of human and prosthetic systems under real-world conditions, these environments provide a foundational simulation framework that supports interdisciplinary research on the interplay between musculoskeletal dynamics and assistive devices. Both myoMPL and myoOSL are featured in MyoChallenge, an annual competition at the NeurIPS conference. All code is accessible through the MyoSuite GitHub repository.","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2025 ","pages":"437-442"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144612653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Neural Network Sparsity in Brain-Body-Machine Interfaces. 脑-体-机接口中的神经网络稀疏性。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2025-05-01 DOI: 10.1109/ICORR66766.2025.11062950

Laura C Petrich, Samuel Neumann, Patrick M Pilarski, Alona Fyshe

{"title":"Neural Network Sparsity in Brain-Body-Machine Interfaces.","authors":"Laura C Petrich, Samuel Neumann, Patrick M Pilarski, Alona Fyshe","doi":"10.1109/ICORR66766.2025.11062950","DOIUrl":"10.1109/ICORR66766.2025.11062950","url":null,"abstract":"Brain-body-machine interfaces acquire, process, and translate brain signals for individuals with severe motor impairments to communicate and control the assistive technology that supports their daily life activities. Electroencephalography (EEG) is a standard approach for acquiring such brain signals due to its low cost and high temporal resolution. EEG signals can be thought of as a proxy for the user's intent. One established method for translating this intent into inferences and actions are neural networks. However, densely connected neural networks can be computationally expensive-a problem for real-time, deployed brain-body-machine interface systems. In this paper we investigate the use of sparsity in neural networks for EEG-based motor classification, with the goal of reducing the number of neuronal connections without sacrificing a system's performance. We compare two sparsity-inducing algorithms, weight pruning and sparse evolutionary training, with a dense neural network under three experimental conditions. Overall, our results show that sparse neural networks can achieve higher performance accuracy and generalization than their densely-connected counterparts for an EEG-based classification task. We found that sparse evolutionary training achieves the highest and most stable performance across all experiments. Introducing sparsity into the network is a viable option for efficient EEG-based control, with promising applications in a range of related rehabilitation and assistive technologies. This brings us closer to helping individuals with severe motor impairments reclaim independence through more computationally realizable methods of interacting with their technology and the world around them.","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2025 ","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144612655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Rehabilitation of Chronic Stroke Using Neurofeedback, Functional Electrical Stimulation and Cerebrospinal Direct Current Stimulation. 神经反馈、功能电刺激和脑脊液直流电刺激对慢性脑卒中康复的影响。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2025-05-01 DOI: 10.1109/ICORR66766.2025.11063073

Teodiano Bastos-Filho, Aura Ximena Gonzalez-Cely, Sheida Mehrpour, Fernanda Souza, Ana Cecilia Villa-Parra, Fernando Cabral

{"title":"Rehabilitation of Chronic Stroke Using Neurofeedback, Functional Electrical Stimulation and Cerebrospinal Direct Current Stimulation.","authors":"Teodiano Bastos-Filho, Aura Ximena Gonzalez-Cely, Sheida Mehrpour, Fernanda Souza, Ana Cecilia Villa-Parra, Fernando Cabral","doi":"10.1109/ICORR66766.2025.11063073","DOIUrl":"https://doi.org/10.1109/ICORR66766.2025.11063073","url":null,"abstract":"This work presents the application of a rehabilitation protocol using a novel Non-Invasive Brain Stimulation (NIBS) technique, called cerebrospinal Direct Current Stimulation (csDCS), together with the use of a Brain-Computer Interface (BCI) based on Motor Imagery (MI) with Neurofeedback (NFB), and applying Functional Electrical Stimulation (FES) plus the use of a pedal exerciser. This protocol uses the concept of Alternating Treatment Design (ATD), in which a chronic post-stroke subject is submitted to these techniques to recover his left hand and leg movements. The rehabilitation progress was verified through metrics, such as Fugl Meyer Assessment (FMA), Functional Independence Measure (FIM), Ashworth Scale, Muscle Strength Grading (MSG), and surface Electromyography (sEMG). Results from these metrics include a 41% gain in hand function recovery, a 5% gain in performance in motor and cognitive/social domains, and a 50% improvement in both wrist extensor muscle strength and finger extensor muscle strength. In addition, there was a 17% gain of Maximum Voluntary Contraction (MVC) for the tibialis anterior muscle of the patient's left leg. On the other hand, there was a worsening in some values of EMG, probably due to the participant having received application of botulinum toxin in his hand.","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2025 ","pages":"1203-1208"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144612701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robotic Individualized Driving Evaluation (RIDE): Design and Preliminary Evaluation. 机器人个性化驾驶评估（RIDE）：设计与初步评估。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2025-05-01 DOI: 10.1109/ICORR66766.2025.11063090

Tim D Yang, Laura Rice, Seth Hutchinson, Yih-Kuen Jan

{"title":"Robotic Individualized Driving Evaluation (RIDE): Design and Preliminary Evaluation.","authors":"Tim D Yang, Laura Rice, Seth Hutchinson, Yih-Kuen Jan","doi":"10.1109/ICORR66766.2025.11063090","DOIUrl":"https://doi.org/10.1109/ICORR66766.2025.11063090","url":null,"abstract":"Power wheelchair driving entails safety risks, including tips and collisions. Thus, driving assessments are important to safeguard both drivers and their surroundings. However, current driving assessments are deterministic, whereas driving itself is stochastic due to individual and environmental uncertainty. Moreover, disabilities magnify this uncertainty. In this study, a robotic wheelchair was used for a novel function: stochastic assessment of PWC driving. The Robotic Individualized Driving Evaluation (RIDE) is a stochastic assessment that contrasts with deterministic assessments by accounting for individual differences via assessment profiles. The robotic wheelchair acquired the information needed for the stochastic model, and a probabilistic risk score was formulated. The purpose of this preliminary study was to test the effect of assessment profiles within and between driving tasks. Within tasks, there were significant differences in RIDE risk between the profiles. Between tasks, there were significant differences in the new stochastic RIDE metrics but not in the conventional deterministic metrics. Results demonstrated potential for this novel use of robotic wheelchairs to support personalized assessment and training in power mobility rehabilitation.","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2025 ","pages":"1693-1698"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144612709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Digital Design Workflow for Individualized 2-DOF Ankle Exoskeletons. 个性化2-DOF踝关节外骨骼的数字化设计工作流程。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2025-05-01 DOI: 10.1109/ICORR66766.2025.11062994

Hunter M Schmidt, Andy Li, Aytac Teker, Mariana H Rocha, Biruk A Gebre, Karen J Nolan, Kishore Pochiraju, Damiano Zanotto

引用次数: 0

Assessing Stylistic Differences in the Underlying Biomechanical Objectives of Walking Using Simulation-Based Observational Gait Analysis. 使用基于模拟的观察步态分析评估步行潜在生物力学目标的风格差异。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2025-05-01 DOI: 10.1109/ICORR66766.2025.11063203

McKenna C Everett, Wentao Li, Ann Majewicz Fey, Nicholas P Fey

{"title":"Assessing Stylistic Differences in the Underlying Biomechanical Objectives of Walking Using Simulation-Based Observational Gait Analysis.","authors":"McKenna C Everett, Wentao Li, Ann Majewicz Fey, Nicholas P Fey","doi":"10.1109/ICORR66766.2025.11063203","DOIUrl":"10.1109/ICORR66766.2025.11063203","url":null,"abstract":"Observational gait analysis and categorical ratings are commonly used by clinicians to assess pathologies. The purpose of this study was to determine the capacity of novice observers to characterize the gait behavior underlying biomechanical performance objectives using stylistic labels. We hypothesized that visual characterization of physics-based musculoskeletal predictive simulations of walking would be sensitive to the biomechanical objective employed by individuals, as well as the visual perspective. We developed 75 full-body muscle-driven predictive gait simulation videos, corresponding to five subject models, five biomechanical objectives, and three visual perspectives. Subject models were constructed for five individuals performing straight line walking, with optimal tracking simulations generated for each using computed muscle control. Direct collocation was used to apply five different objectives to each individual's nominal behavior including metabolic cost, summed and squared muscle activations, time-integrated whole-body angular momentum, time-integrated bilateral ground reaction forces, and an equally weighted multi-objective cost function summing the individual objectives. 100 crowd workers characterized each simulation on a 1-5 scale using stylistic labels corresponding to each objective. Multinomial logistic regression analysis revealed that loading and activation ratings were significant predictors of muscle activation-optimized movements, while activation ratings were significant predictors of movement perspective. Balance ratings were significant for the frontal view alone, suggesting that balance indicators are more easily distinguished in the frontal plane. Collectively, the wisdom of crowds could distinguish motion associated with some biomechanical objectives, but due to the redundancy of motor control strategies used by individuals, the resolution of this observational approach is limited.","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2025 ","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144612508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Muscle Activation and Postural Sway in Response to Task Complexity: A Study of Balance Control in Older Adults. 任务复杂性对肌肉激活和姿势摇摆的影响：老年人平衡控制的研究。

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Pub Date : 2025-05-01 DOI: 10.1109/ICORR66766.2025.11063123

Longbin Zhang, Ananda Sidarta, Yu Chin Lim, Carol Er, Xiaoyue Yan, Tsung-Lin Wu, Wei Tech Ang

{"title":"Muscle Activation and Postural Sway in Response to Task Complexity: A Study of Balance Control in Older Adults.","authors":"Longbin Zhang, Ananda Sidarta, Yu Chin Lim, Carol Er, Xiaoyue Yan, Tsung-Lin Wu, Wei Tech Ang","doi":"10.1109/ICORR66766.2025.11063123","DOIUrl":"10.1109/ICORR66766.2025.11063123","url":null,"abstract":"In this study, we investigate muscle activation patterns and postural sway in older adults across different stance conditions with varying challenges. Muscle activity from lower limb and trunk muscles was recorded in seven older adults during four stance tasks: double stance, tandem stance, tandem stance with a cognitive task, and tandem stance with combined cognitive and motor tasks (TSCM). We analyzed CoP (centre of pressure) features, EMG (electromyography) patterns, and the coherence between EMG-CoP, to gain insights into neuromuscular coordination and balance control. Our findings indicate that task complexity significantly impacts postural stability, with tandem stances-particularly TSCM-leading to increased instability along the anterior-posterior axis. Key stabilizing muscles, such as the gastrocnemius medialis and tibialis anterior, showed heightened activation and strong EMGCoP coherence under complex tasks, highlighting their essential role in counteracting gravitational forces to maintain balance. A lateral asymmetry in muscle activation was also observed, with left-side muscles consistently showing greater activity than right-side counterparts, suggesting lateralized contributions to postural control. These results emphasize the importance of specific muscles for stability in challenging postural tasks and may offer valuable insights for designing targeted interventions, including robotic rehabilitation systems and assistive technologies, to enhance balance and reduce fall risk in older adults.","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2025 ","pages":"82-87"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144612579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0