A Wearable Upper Limb Exoskeleton System and Intelligent Control Strategy

Heavy lifting operations frequently lead to upper limb muscle fatigue and injury. In order to reduce muscle fatigue, auxiliary force for upper limbs can be provided. This paper presents the development and evaluation of a wearable upper limb exoskeleton (ULE) robot system. A flexible cable transmits...

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Published inBiomimetics (Basel, Switzerland) Vol. 9; no. 3; p. 129
Main Authors Wang, Qiang, Chen, Chunjie, Mu, Xinxing, Wang, Haibin, Wang, Zhuo, Xu, Sheng, Guo, Weilun, Wu, Xinyu, Li, Weimin
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 21.02.2024
MDPI
Subjects
Algorithms
Cables
Control algorithms
Design
Efficiency
Elbow
Electromyography
Energy consumption
Exoskeleton
Fatigue
Health care industry
Human body
Innovations
Limbs
Rehabilitation
Technology application
upper limb assistance
wearable robotics
China
wearable robotics
exoskeleton
upper limb assistance
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Summary:Heavy lifting operations frequently lead to upper limb muscle fatigue and injury. In order to reduce muscle fatigue, auxiliary force for upper limbs can be provided. This paper presents the development and evaluation of a wearable upper limb exoskeleton (ULE) robot system. A flexible cable transmits auxiliary torque and is connected to the upper limb by bypassing the shoulder. Based on the K-nearest neighbors (KNN) algorithm and integrated fuzzy PID control strategy, the ULE identifies the handling posture and provides accurate active auxiliary force automatically. Overall, it has the quality of being light and easy to wear. In unassisted mode, the wearer’s upper limbs minimally affect the range of movement. The KNN algorithm uses multi-dimensional motion information collected by the sensor, and the test accuracy is 94.59%. Brachioradialis muscle (BM), triceps brachii (TB), and biceps brachii (BB) electromyogram (EMG) signals were evaluated by 5 kg, 10 kg, and 15 kg weight conditions for five subjects, respectively, during lifting, holding, and squatting. Compared with the ULE without assistance and with assistance, the average peak values of EMG signals of BM, TB, and BB were reduced by 19–30% during the whole handling process, which verified that the developed ULE could provide practical assistance under different load conditions.
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These authors contributed equally to this work.
ISSN:2313-7673
2313-7673
DOI:10.3390/biomimetics9030129