A real-time walking pattern recognition method for soft knee power assist wear

Real-time recognition of walking-related activities is an important function that lower extremity assistive devices should possess. This article presents a real-time walking pattern recognition method for soft knee power assist wear. The recognition method employs the rotation angles of thighs and s...

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Veröffentlicht in:International journal of advanced robotic systems Jg. 17; H. 3
Hauptverfasser: Wang, Wenkang, Zhang, Liancun, Liu, Juan, Zhang, Bainan, Huang, Qiang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London, England SAGE Publications 01.05.2020
Sage Publications Ltd
SAGE Publishing
Schlagworte:
Algorithms
Ascent
Inertial platforms
Knee
Pattern recognition
Real time
Walking
Wear
Walking pattern recognition
rule-based algorithm
real-time recognition
soft knee power assist wear
inertial measurement units
ISSN:1729-8806, 1729-8814
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Zusammenfassung:Real-time recognition of walking-related activities is an important function that lower extremity assistive devices should possess. This article presents a real-time walking pattern recognition method for soft knee power assist wear. The recognition method employs the rotation angles of thighs and shanks as well as the knee joint angles collected by the inertial measurement units as input signals and adopts the rule-based classification algorithm to achieve the real-time recognition of three most common walking patterns, that is, level-ground walking, stair ascent, and stair descent. To evaluate the recognition performance, 18 subjects are recruited in the experiments. During the experiments, subjects wear the knee power assist wear and carry out a series of walking activities in an out-of-lab scenario. The results show that the average recognition accuracy of three walking patterns reaches 98.2%, and the average recognition delay of all transitions is slightly less than one step.
Bibliographie:ObjectType-Article-1
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ISSN:1729-8806
1729-8814
DOI:10.1177/1729881420925291