LSTM-Based Lower Limbs Motion Reconstruction Using Low-Dimensional Input of Inertial Motion Capture System

doi:10.1109/JSEN.2019.2959639

	LSTM-Based Lower Limbs Motion Reconstruction Using Low-Dimensional Input of Inertial Motion Capture System
	Tong, Lina 1; Liu, Rongkai 1; Peng, Liang2
发表期刊	IEEE SENSORS JOURNAL
ISSN	1530-437X
	2020-04-01
卷号	20 期号:7 页码:3667-3677
通讯作者	Peng, Liang(liang.peng@ia.ac.cn)
摘要	Motion capture system has been widely used in virtual reality and rehabilitation area. This study proposed a data-driven method using low-dimensional input of inertial motion capture system to reconstruct human lower-limb motions. The long short-term memory (LSTM) neural network was used and an ensemble LSTM architecture was involved to improve reconstruction performance. Besides, the selection of optimal sensor configuration scheme and time-step parameters of LSTM network was discussed in detail. The reconstruction experiment shows that the method could get the lowest reconstruction joint angle root mean square (RMS) errors of 4.031 degrees on separated motion dataset, and 5.105 degrees on completely new dataset of synthetic motions using ensemble LSTM model with 18 base learner and three sensors units. The computational consumption test shows that the single and ensemble LSTM model spend 0.15ms and 0.91ms respectively to predict next frame. These findings demonstrate that the proposed method is effective and efficient for motions reconstruction of lower limbs.
关键词	Motion reconstruction LSTM neural networks inertial motion capture dimension reduction sensor configuration
DOI	10.1109/JSEN.2019.2959639
关键词[WOS]	SENSORS
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61603386] ; National Natural Science Foundation of China[61720106012] ; National Natural Science Foundation of China[U1613228] ; Beijing Municipal Natural Science Foundation[Z170003]
项目资助者	National Natural Science Foundation of China ; Beijing Municipal Natural Science Foundation
WOS研究方向	Engineering ; Instruments & Instrumentation ; Physics
WOS类目	Engineering, Electrical & Electronic ; Instruments & Instrumentation ; Physics, Applied
WOS记录号	WOS:000524351800032
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
七大方向——子方向分类	多模态智能
引用统计	被引频次：11[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/38920
专题	复杂系统认知与决策实验室_先进机器人
通讯作者	Peng, Liang
作者单位	1.China Univ Min & Technol Beijing, Elect Engn & Automat Dept, Beijing 100083, Peoples R China 2.Chinese Acad Sci, Inst Automat, SKLMCCS, Beijing 100190, Peoples R China
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	Tong, Lina,Liu, Rongkai,Peng, Liang. LSTM-Based Lower Limbs Motion Reconstruction Using Low-Dimensional Input of Inertial Motion Capture System[J]. IEEE SENSORS JOURNAL,2020,20(7):3667-3677.
APA	Tong, Lina,Liu, Rongkai,&Peng, Liang.(2020).LSTM-Based Lower Limbs Motion Reconstruction Using Low-Dimensional Input of Inertial Motion Capture System.IEEE SENSORS JOURNAL,20(7),3667-3677.
MLA	Tong, Lina,et al."LSTM-Based Lower Limbs Motion Reconstruction Using Low-Dimensional Input of Inertial Motion Capture System".IEEE SENSORS JOURNAL 20.7(2020):3667-3677.