ED-FNN: A New Deep Learning Algorithm to Detect Percentage of the Gait Cycle for Powered Prostheses

Throughout the last decade, a whole new generation of powered transtibial prostheses and exoskeletons has been developed. However, these technologies are limited by a gait phase detection which controls the wearable device as a function of the activities of the wearer. Consequently, gait phase detec...

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Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 18; H. 7; S. 2389
Hauptverfasser:	Vu, Huong Thi Thu, Gomez, Felipe, Cherelle, Pierre, Lefeber, Dirk, Nowé, Ann, Vanderborght, Bram
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 23.07.2018 MDPI
Schlagworte:	Accuracy Algorithms Amputation Artificial intelligence Electromyography exoskeleton Gait gait event detection gait phase prediction gait recognition International conferences lower limb prosthesis Neural networks Phase transitions Prostheses Sensors Skin United States > US Germany exoskeleton gait recognition gait event detection lower limb prosthesis gait phase prediction
ISSN:	1424-8220, 1424-8220
Online-Zugang:	Volltext
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