This study evaluates Random Forest and Long Short-Term Memory and Long Short-Term Memory for five-class wrist-movement classification using six-channel inertial measurement unit (IMU) data, while surface electromyography (sEMG) is used for RMS-based muscle-activity monitoring.
Robotic wrist rehabilitation after stroke requires control signals that reflect the user’s volitional intent, while clinically deployable systems are constrained by the number of surface electromyography (sEMG) channels that can be practically placed on a hemiparetic forearm. This study evaluates how far a single sEMG...
Muhammad Restu Alvian Firmansyah, Alwi Harliansyah Hrp· Journal of Applied Science,...· 0 citations
The study findings highlight the feasibility of integrating wearable HAR systems into smart homes for real-time monitoring and adaptive assistance and show superior cross-dataset generalization in Random Forest and Multilayer Perceptron models.
O. Gorjani, René Jaros, P. Bilik· Frontiers in Bioengineering...· 0 citations
The low cost wearble monitoring framework for the automatic evaluation of exercises for stroke recovery of the upper limb with special attention to discrimination between the intended and compensatory motion of the elbow joint is designed. The monitoring framework utilizes a 9 degrees-of-freedom IMU combined with the E...
A. N, U. Kumar· Journal of Electronics and I...· 0 citations
Stroke is a leading cause of long-term disability worldwide, and with rising incidence and a global shortage of rehabilitation professionals, there is a growing need for scalable methods to assess motor impairment. Surface electromyography (sEMG) has emerged as a promising modality for capturing motor function. D...
Hao-Ping Lin, Li-Na Zhao, Daniel Woolley et al.· Journal of NeuroEngineering...· 0 citations
Reliable control of upper-limb prostheses remains challenging because muscle signals can change between sessions and wearable EMG sensors may suffer from poor electrode contact. This study presents a real-time prosthetic hand control platform based on an OYMotion gForce Pro armband and a five-finger Dynamixel-actuated...
Darkhan Zholtayev, Temirlan Meiramkhanov, A. Ozhikenova et al.· Scientific Journal of Astana...· 0 citations
ECA-ResNet1D-Lite is presented, a lightweight one-dimensional depthwise separable residual network augmented with efficient channel attention (ECA), trained and evaluated on the SPARS9x dataset comprising six shoulder exercises recorded from 20 subjects using a commercial wrist-worn smartwatch at 50 Hz, establishing th...
S. Mekruksavanich, A. Jitpattanakul· Computers· 0 citations
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