A simulation-based framework with a proprioceptive musculoskeletal model for evaluating the rehabilitation exoskeleton system

Mo, Fuhao; Zhang, Qiang; Zhang, Haotian; Li, Jianjun; Wang, Yulong; Chen, Gong; Ye, Jing

doi:10.1016/j.cmpb.2021.106270

Cited by 9 publications

(2 citation statements)

References 29 publications

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“…where k ∈ [1,12] denotes the locomotion modes, N s represents the number of successfully recognized data points in ( 13) Fig. 7 The hyper-parameter optimization process the locomotion mode k, and N t is the total number of sample data in the locomotion mode k.…”

Section: Recognition Effectsmentioning

confidence: 99%

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Integral Real-time Locomotion Mode Recognition Based on GA-CNN for Lower Limb Exoskeleton

Wang

Gao

et al. 2022

J Bionic Eng

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The wearable lower limb exoskeleton is a typical human-in-loop human–robot coupled system, which conducts natural and close cooperation with the human by recognizing human locomotion timely. Requiring subject-specific training is the main challenge of the existing approaches, and most methods have the problem of insufficient recognition. This paper proposes an integral subject-adaptive real-time Locomotion Mode Recognition (LMR) method based on GA-CNN for a lower limb exoskeleton system. The LMR method is a combination of Convolutional Neural Networks (CNN) and Genetic Algorithm (GA)-based multi-sensor information selection. To improve network performance, the hyper-parameters are optimized by Bayesian optimization. An exoskeleton prototype system with multi-type sensors and novel sensing-shoes is used to verify the proposed method. Twelve locomotion modes, which composed an integral locomotion system for the daily application of the exoskeleton, can be recognized by the proposed method. According to a series of experiments, the recognizer shows strong comprehensive abilities including high accuracy, low delay, and sufficient adaption to different subjects.

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Section: Recognition Effectsmentioning

confidence: 99%

“…Technology advancements have led to the development of numerous wearable exoskeleton robots for military and medical purposes through abilities augment and physical assistance [1], 2. Developing appropriate strategies to predict the intentions of wearers is one of the challenging issues.…”

Section: Introductionmentioning

confidence: 99%