This study proves that GMH-D is a reliable framework for assessing 3D hand movements in clinical applications and contributes to the advancement of hand tracking technology, and the establishment of a validation procedure as a good-practice to prove efficacy of deep-learning-based hand-tracking.
A wearable hand gesture recognition system employing an MPU6500 gyroscope to detect tri-axial angular velocity corresponding to five different pre-defined hand gestures, making it ideal for applications in rehabilitation monitoring, assistive communication, and wearables.
Neela Harish, Deepa S., Umasankar Loganathan et al.· Journal of Innovative Image...· 2 citations
This review evaluates electromyography (EMG), force myography (FMG), sonomyography (SMG), and optical myography (OMG) for prosthetic hand control, comparing the modalities across signal propagation, signal accuracy, noise resistance, real-time processing, suitability for prosthetic control, and relative cost and system...
D. K. Yusuf, N. H. Okeke, Purity T. Y. Gandu et al.· Cureus· 0 citations
This work presents a novel pipeline for 3-D hand joint location and pose estimation using neural rendering that overcomes the inefficiencies of manual measurement and the inaccuracies of existing software, providing a robust tool for objective functional assessment.
Emmett Chen, Neal Chen, Xiang Li et al.· 0 citations
A motion measurement system that improves body positioning by using computer vision techniques to quantitatively assess elbow flexibility and range of motion during rehabilitation, using a novel posture estimation model.
Kok Swee Sim, Mahda Laina Arnumukti· International Journal on Adv...· 0 citations
A markerless pipeline that analyzes monocular RGB video entirely on-device in the browser, so it never leaves the machine is presented, offering an accessible, privacy-preserving proof-of-concept foundation for home telerehabilitation.
A. Pavlikov, V. Petrosyan, Vladislav Agapov et al.· Italian National Conference...· 0 citations
