Engagement Enhancement Based on Human-in-the-Loop Optimization for Neural Rehabilitation | |
Wang, Jiaxing1,2; Wang, Weiqun2; Ren, Shixin1,2; Shi, Weiguo1,2; Hou, Zeng-Guang1,2,3 | |
发表期刊 | FRONTIERS IN NEUROROBOTICS |
ISSN | 1662-5218 |
2020-11-12 | |
卷号 | 12期号:无页码:11 |
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. |
关键词 | human-in-the-loop optimization EEG based neural engagement sEMG based muscle activation tracking accuracy neural rehabilitation |
DOI | 10.3389/fnbot.2020.596019 |
关键词[WOS] | EEG ; ATTENTION ; ASSISTANCE ; DISORDER ; PARTICIPATION ; HYPERACTIVITY ; PERFORMANCE ; ADAPTATION ; WORK |
收录类别 | SCI |
语种 | 英语 |
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] |
项目资助者 | 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 |
WOS研究方向 | Computer Science ; Robotics ; Neurosciences & Neurology |
WOS类目 | Computer Science, Artificial Intelligence ; Robotics ; Neurosciences |
WOS记录号 | WOS:000592233300001 |
出版者 | FRONTIERS MEDIA SA |
七大方向——子方向分类 | 多模态智能 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/41777 |
专题 | 复杂系统管理与控制国家重点实验室_先进机器人 |
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, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China 3.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
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,2020,12(无):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,12(无),11. |
MLA | Wang, Jiaxing,et al."Engagement Enhancement Based on Human-in-the-Loop Optimization for Neural Rehabilitation".FRONTIERS IN NEUROROBOTICS 12.无(2020):11. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
fnbot-14-596019-fina(2370KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论