Forecasting Dropout in Home-Based Movement Rehabilitation after Stroke with Sensors and Machine Learning [0.03%]
基于传感器和机器学习的卒中后居家康复脱落预测研究
Sangjoon J Kim,George H Collier,Jacob Cartwright et al.
Sangjoon J Kim et al.
Adherence to home-based rehabilitation can support recovery after stroke, yet many patients disengage within the first few weeks. While prior studies have examined perseverance in small samples or under supervised settings, little is known ...
Adaptive Gait-Based Control for Assistive Robots Supporting Elderly on Inclined Surfaces [0.03%]
适应性步态控制助老机器人辅助老年人在倾斜地表行走
Kishore Vennela,B Balaji,M C Chinnaiah et al.
Kishore Vennela et al.
This paper presents an adaptive human-robot interaction framework designed to assist elderly individuals in navigating both flat and inclined surfaces using a mobile robotic platform. The proposed method integrates real-time gait estimation...
Using EMG Biofeedback to Restore Closed-Loop Neural Control on a Powered Prosthetic Ankle [0.03%]
基于肌电生物反馈的假肢踝关节闭环神经控制恢复
Brendan Driscoll,Joshua R Tacca,Kasey Preisser et al.
Brendan Driscoll et al.
This paper aims to present that biofeedback based on electromyography (EMG) can help transtibial amputees to improve their capability to manipulate powered prosthetic ankles using Direct Electromyography (dEMG) control. First, we constructe...
Guidance Framework for Selecting Virtual Hand Illusion Paradigms to Enhance Motor Imagery via Sense of Ownership in Stroke Rehabilitation [0.03%]
基于虚拟手幻觉的卒中患者运动想象脑机接口康复系统的本体感受所有权感知指导框架
Hojun Jeong,Haemin Jung,Seyoung Shin et al.
Hojun Jeong et al.
Virtual hand illusion (VHI)-based motor imagery (MI) guidance systems are a promising approach for enhancing MI by reinforcing the sense of ownership (SoO), a key factor in effective neurorehabilitation. Although VHI-based guidance has show...
Robust Decomposition of Surface EMG Signals via Lightweight Deep Learning-Based Adaptation [0.03%]
基于轻量级深度学习适应的表面EMG信号鲁棒分解方法
Zeyu Zhou,Yang Yu,Yang Xu et al.
Zeyu Zhou et al.
Real-time surface electromyography decomposition has emerged as a promising way for neural interfacing. However, the decomposition performance faces dramatic degradation when multiple non-stationary factors coexist, including noise increase...
A 3D-Printing-Based Optogenetic Neural Stimulator Integrated with Three Neural Recording Channels [0.03%]
一种基于3D打印技术的集成了三种神经记录通道的光遗传学神经刺激器
Keonghwan Oh,Jihong Lim,Yehhyun Jo et al.
Keonghwan Oh et al.
This paper presents an optical neural modulation device integrated with neural recording channels. While most optogenetic devices are fabricated using microfabrication techniques, this device is produced primarily using 3D printing, elimina...
Adaptive Gait Assistance for Foot Drop Rehabilitation Based on Uncertainty Fusion of Contralateral Limb Information [0.03%]
基于对侧肢体信息不确定性融合的足下垂康复自适应步态助行方法
Kehan Xu,Jun Huo,Yize Zheng et al.
Kehan Xu et al.
Foot drop resulting from neurological injury severely compromises mobility and gait stability, yet existing assistive solutions often overlook physiological bilateral coordination and lack adaptability to individual gait variability. This s...
Directional Tolerance of Electrode Displacement in STN-DBS: An Analysis Based on Volume of Tissue Activated [0.03%]
基于激活组织体积的STN-DBS电极偏移方向容差分析
Chenghuai Mo,Wanyu Hu,Yuhai Xie et al.
Chenghuai Mo et al.
The therapeutic efficacy of deep brain stimulation for Parkinson's disease critically depends on accurate electrode placement. While previous studies have described the side effects associated with directional displacements, their direct im...
A novel feedback-based compensation reduction with upper body reconstruction for upper-limb rehabilitation [0.03%]
基于反馈的上身重建上肢康复补偿减少的新方法
Yeji Hwang,Taegyun Kim,James Hyungsup Moon et al.
Yeji Hwang et al.
Compensatory movements frequently occur during upper-limb rehabilitation for patients with stroke, potentially impeding effective motor recovery. Vision-based systems offer practical solutions for monitoring such compensations, but their ap...
A Validated Framework for Decoding Motor Unit Firings and Resulting Ankle Moments during Walking [0.03%]
一种验证框架：解码步行时的运动单元放电及其产生的踝关节力矩
Antonio Gogeascoechea,Marco Carbonaro,Nathan Van Dieren et al.
Antonio Gogeascoechea et al.
Understanding how the central nervous system controls complex movements, such as walking, remains a fundamental challenge. Although motor units (MUs) are well-studied in isometric tasks, their role in generating joint moments during functio...