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Engagement Enhancement Based on Human-in-the-Loop Optimization for Neural Rehabilitation

文献类型：期刊论文

作者Wang, Jiaxing1,3; Wang, Weiqun3; Ren, Shixin1,3; Shi, Weiguo1,3; Hou, Zeng-Guang1,2,3
刊名FRONTIERS IN NEUROROBOTICS
出版日期2020-11-12
卷号14页码:11
关键词human-in-the-loop optimization EEG based neural engagement sEMG based muscle activation tracking accuracy neural rehabilitation
ISSN号1662-5218
DOI10.3389/fnbot.2020.596019
通讯作者Wang, Weiqun(weiqun.wang@ia.ac.cn)
英文摘要Enhancing patients' engagement is of great benefit for neural rehabilitation. However, physiological and neurological differences among individuals can cause divergent responses to the same task, and the responses can further change considerably during training; both of these factors make engagement enhancement a challenge. This challenge can be overcome by training task optimization based on subjects' responses. To this end, an engagement enhancement method based on human-in-the-loop optimization is proposed in this paper. Firstly, an interactive speed-tracking riding game is designed as the training task in which four reference speed curves (RSCs) are designed to construct the reference trajectory in each generation. Each RSC is modeled using a piecewise function, which is determined by the starting velocity, transient time, and end velocity. Based on the parameterized model, the difficulty of the training task, which is a key factor affecting the engagement, can be optimized. Then, the objective function is designed with consideration to the tracking accuracy and the surface electromyogram (sEMG)-based muscle activation, and the physical and physiological responses of the subjects can consequently be evaluated simultaneously. Moreover, a covariance matrix adaption evolution strategy, which is relatively tolerant of both measurement noises and human adaptation, is used to generate the optimal parameters of the RSCs periodically. By optimization of the RSCs persistently, the objective function can be maximized, and the subjects' engagement can be enhanced. Finally, the performance of the proposed method is demonstrated by the validation and comparison experiments. The results show that both subjects' sEMG-based motor engagement and electroencephalography based neural engagement can be improved significantly and maintained at a high level.
WOS关键词EEG ; ATTENTION ; ASSISTANCE ; DISORDER ; PARTICIPATION ; HYPERACTIVITY ; PERFORMANCE ; ADAPTATION ; WORK
资助项目National Natural Science Foundation of China[U1913601] ; National Natural Science Foundation of China[91848110] ; National Key R&D Program of China[2018YFB1307804] ; Beijing Natural Science Foundation[4202074] ; Strategic Priority Research Program of Chinese Academy of Science[XDB32000000]
WOS研究方向Computer Science ; Robotics ; Neurosciences & Neurology
语种英语
WOS记录号WOS:000592233300001
出版者FRONTIERS MEDIA SA
资助机构National Natural Science Foundation of China ; National Key R&D Program of China ; Beijing Natural Science Foundation ; Strategic Priority Research Program of Chinese Academy of Science
源URL[http://ir.ia.ac.cn/handle/173211/41776]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
通讯作者Wang, Weiqun
作者单位1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
2.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing, Peoples R China
3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Jiaxing,Wang, Weiqun,Ren, Shixin,et al. Engagement Enhancement Based on Human-in-the-Loop Optimization for Neural Rehabilitation[J]. FRONTIERS IN NEUROROBOTICS,2020,14:11.
APA Wang, Jiaxing,Wang, Weiqun,Ren, Shixin,Shi, Weiguo,&Hou, Zeng-Guang.(2020).Engagement Enhancement Based on Human-in-the-Loop Optimization for Neural Rehabilitation.FRONTIERS IN NEUROROBOTICS,14,11.
MLA Wang, Jiaxing,et al."Engagement Enhancement Based on Human-in-the-Loop Optimization for Neural Rehabilitation".FRONTIERS IN NEUROROBOTICS 14(2020):11.

入库方式： OAI收割

来源：自动化研究所

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