Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
38082960
The main challenge in adopting deep learning models is limited data for training, which can lead to poor generalization and a high risk of overfitting, particularly when detecting forearm abnormalities in X-ray images. Transfer learning from ImageNet...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
38064321
Though the forearm is the focus of the prostheses, myoelectric control with the electrodes on the wrist is more comfortable for general consumers because of its unobtrusiveness and incorporation with the existing wrist-based wearables. Recently, deep...
International journal of occupational safety and ergonomics : JOSE
38553890
. This study examines the role of different machine learning (ML) algorithms to determine which socio-demographic factors and hand-forearm anthropometric dimensions can be used to accurately predict hand function. . The cross-sectional study was cond...
IEEE transactions on bio-medical engineering
38133970
OBJECTIVE: The purpose of this study was to develop and evaluate the performance of RPC-Net (Recursive Prosthetic Control Network), a novel method using simple neural network architectures to translate electromyographic activity into hand position wi...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039372
Robotic systems for rehabilitating forearm have been an active area of research. A majority of the daily living activities require the use of the forearm significantly, and hence affecting the quality of life of the patient if not rehabilitated promp...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039048
For seemless control of advanced hand prostheses and augmented reality, accurate and immediate hand gestures recognition is essential. Surface electromyography (sEMG) signals obtained from the forearm are commonly employed for this purpose. In this p...
International journal of occupational safety and ergonomics : JOSE
39139048
This study explored the use of forearm electromyography data to distinguish eight hand gestures. The neural network (NN) and random forest (RF) algorithms were tested on data from 10 participants. As window sizes increase from 200 ms to 1000 ms, the ...
Haptic devices typically rely on rigid actuators and bulky power supply systems, limiting wearability. Soft materials improve comfort, but careful distribution of stiffness is required to ground actuation forces and enable load transfer to the skin. ...
The accurate assessment of muscle morphology and function is crucial for medical diagnostics, rehabilitation, and biomechanical research. This study presents a novel methodology for constructing volumetric models of forearm muscles based on three-dim...