Although myoelectric prosthetic hands provide amputees with intuitive
control, their reliance on many EMG sensors limits accessibility and makes them
complex and expensive. To address this problem, this work presents a different
perspective that makes use of a single EMG sensor and brief impulse signals in
conjunction with Dynamic Time Warping (DTW) for accurate pattern detection.
Conventional techniques rely on real-time data from multiple sensors, which can
be costly and bulky. The method presents high accuracy while lowering hardware
complexity and expense. A DTW-based system that reliably identifies muscle
activation patterns from short EMG signals was created and tested. Results show
that this single-sensor approach obtained an accuracy rate of 92%, which is
similar to that of conventional multi-sensor systems. This research provides a
more straightforward and economical approach that can be used to obtain
enhanced myoelectric control. These findings provide a different perspective on
more easily accessible and user-friendly prosthetic devices, which will be
especially helpful in disaster-affected areas where quick deployment is
essential. Future improvements would investigate this system’s dependability
over time and wider implementations in real situations, to take prosthetic
technology one step further.

Cet article explore les excursions dans le temps et leurs implications.

Télécharger PDF: