Adaptive Locomotion Transition Recognition With Wearable Sensors for Lower Limb Robotic Prosthesis

doi:10.1109/TMECH.2023.3278315

CORC > 自动化研究所 > 中国科学院自动化研究所 > 多模态人工智能系统全国重点实验室

	Adaptive Locomotion Transition Recognition With Wearable Sensors for Lower Limb Robotic Prosthesis
	Zheng, Enhao 1; Wan, Jiacheng 7; Gao, Siyuan 2,3; Wang, Qining 2,4,5,6
刊名	IEEE-ASME TRANSACTIONS ON MECHATRONICS
	2023-06-07
页码	11
关键词	Adaptive recognition model interday and interuser locomotion mode recognition lower limb robotic prostheses template generation
ISSN号	1083-4435
DOI	10.1109/TMECH.2023.3278315
通讯作者	Wang, Qining(qiningwang@pku.edu.cn)
英文摘要	Locomotion transition recognition with external disturbances is a key issue in lower limb robotic prostheses. Redonning the prosthetic socket and individual differences are encountered frequently in daily life. They change the feature distribution and further fail the previously trained recognition model. To bridge the technical gap between laboratory validation and practical demands, researchers need to construct an adaptive recognition method with high accuracy, quick response, time-efficient calibration, and minimal interference to the human body. Our study developed an adaptive recognition algorithm based on two miniaturized inertial sensors (anterior thigh and forefoot) and a foot pressure sensor, which can easily be integrated into the prosthesis. The algorithm fused probability-based fuzzy classifiers, which took heuristic-based features as inputs with a dynamic-time-warping-based automatic template generation block. It enables the recognition model to quickly fit the parameters for an untrained mode after external disturbances. We validated the proposed adaptive recognition method on 13 healthy subjects, performing 18 motion transitions with random interday intervals and across user evaluation, both offline and online. Even with the data of one subject as the prior knowledge, the other subjects produced an average accuracy of 98.04% and an average transition time latency of -180.99 ms without manual training in interday and intersubject uses. We also tested the method on two subjects using robotic prostheses, one person with a transfemoral amputation and the other person with a transtibial amputation. The average accuracy was still as high as 98.06% (transfemoral) and 100% (transtibial) without manual calibration after seven days of intervals. The results proved that the adaptive recognition method is robust to sensor redonning and user changes. Compared with the state-of-the-art methods, our study makes a further step toward the practical use of robotic prostheses. Future studies will be conducted to implement the algorithm on the robotic prosthesis for more extensive tests.
资助项目	National Natural Science Foundation of China[62073318] ; National Natural Science Foundation of China[91948302] ; Youth Innovation Promotion Association CAS
WOS关键词	TRANSFEMORAL PROSTHESIS ; KNEE ; IDENTIFICATION ; WALKING ; DESIGN ; SYSTEM
WOS研究方向	Automation & Control Systems ; Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:001005810500001
资助机构	National Natural Science Foundation of China ; Youth Innovation Promotion Association CAS
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/53483]
专题	多模态人工智能系统全国重点实验室
通讯作者	Wang, Qining
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China 2.Peking Univ, Coll Engn, Dept Adv Mfg & Robot, Beijing 100871, Peoples R China 3.Peking Univ, Beijing Engn Res Ctr Intelligent Rehabil Engn, Beijing 100871, Peoples R China 4.Univ Hlth & Rehabil Sci, Med Robot Lab, Qingdao 266071, Peoples R China 5.Beijing Inst Gen Artificial Intelligence, Beijing 100080, Peoples R China 6.Peking Univ, Inst Artificial Intelligence, Beijing 100871, Peoples R China 7.Beijing Inst Technol, Sch Mechatron Engn, Beijing 100081, Peoples R China
推荐引用方式 GB/T 7714	Zheng, Enhao,Wan, Jiacheng,Gao, Siyuan,et al. Adaptive Locomotion Transition Recognition With Wearable Sensors for Lower Limb Robotic Prosthesis[J]. IEEE-ASME TRANSACTIONS ON MECHATRONICS,2023:11.
APA	Zheng, Enhao,Wan, Jiacheng,Gao, Siyuan,&Wang, Qining.(2023).Adaptive Locomotion Transition Recognition With Wearable Sensors for Lower Limb Robotic Prosthesis.IEEE-ASME TRANSACTIONS ON MECHATRONICS,11.
MLA	Zheng, Enhao,et al."Adaptive Locomotion Transition Recognition With Wearable Sensors for Lower Limb Robotic Prosthesis".IEEE-ASME TRANSACTIONS ON MECHATRONICS (2023):11.