A Muscle Synergy-Inspired Method of Detecting Human Movement Intentions Based on Wearable Sensor Fusion

Detecting human movement intentions is fundamental to neural control of robotic exoskeletons, as it is essential for achieving seamless transitions between different locomotion modes. In this study, we enhanced a muscle synergy-inspired method of locomotion mode identification by fusing the electrom...

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Veröffentlicht in:	IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING Jg. 29; S. 1089 - 1098
Hauptverfasser:	Liu, Yi-Xing, Wang, Ruoli, Gutierrez-Farewik, Elena M.
Format:	Journal Article Verlag
Sprache:	Englisch
Veröffentlicht:	New York IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Acceleration Accuracy Angular velocity Ascent Classification Electromyography Exoskeleton Exoskeletons Feature extraction Finite state machines Human motion Inclination angle Inertial platforms Inertial sensing devices Intent recognition Legged locomotion Locomotion locomotion modes identification Mechanical sensors Motion perception Multisensor fusion muscle synergies Muscles Robot control robotic exoskeletons sensor fusion Sensors Stairs Stairways Velocity Walking Wearable technology
ISSN:	1534-4320, 1558-0210, 1558-0210
Online-Zugang:	Volltext
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