A Real-time Human Activity Recognition Approach with Generalization Performance

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 机器人学研究室

	A Real-time Human Activity Recognition Approach with Generalization Performance
	Wei, Shi-Jie 3; Zhang B(张弼)1,2; Tan XW(谈晓伟)1,2,4; Zhao XG(赵新刚)1,2; Ye D(叶丹)3
	2020
会议日期	July 27-29, 2020
会议地点	Shenyang, China
关键词	Human Activity Recognition Feature Selection Generalization Performance Real-time Performance Transfer Learning
页码	6334-6339
英文摘要	The current human activity recognition (HAR) methods need training data from users. The data collection causes discomfort to the users and most of the studies ignore the real-time performance of classification. This paper presents a real-time human activity recognition approach with strong generalization performance. It uses existing dataset to avoid long-term data collection of subjects, so that the machine can be quickly applied to each specific individual. Also, it takes advantage of both combined accuracy and limited feature selection proposed by this paper to implement feature-selection-based transfer learning which improves HAR in both real-time and generalization performance. In view of the recognition time and accuracy, the depth neural network is selected, changeable structure of which is more suitable for feature selection. This approach utilizes four inertial measurement units placed on the outside of human thighs and shanks. A total of seven activities are taken into account that includes level-walking, upstairs, downstairs, uphill, downhill, standing and sitting. The experiments are performed on six healthy male subjects in free-living settings to evaluate the efficacy of the algorithm. This approach achieved a notable activity recognition accuracy of 98.89%, and reported a fast average activity classification time of 28.6 ms.
源文献作者	Systems Engineering Society of China (SESC) ; Technical Committee on Control Theory (TCCT) of Chinese Association of Automation (CAA)
产权排序	2
会议录	Proceedings of the 39th Chinese Control Conference, CCC 2020
会议录出版者	IEEE Computer Society
会议录出版地	Washington, USA
语种	英语
ISSN号	1934-1768
ISBN号	978-9-8815-6390-3
WOS记录号	WOS:000629243506084
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/27703]
专题	沈阳自动化研究所_机器人学研究室
通讯作者	Zhang B(张弼)
作者单位	1.State Key Lab of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, P. R. China 2.Institutes of Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, P. R. China 3.College of Information Science and Engineering, Northeastern University, Shenyang 110819, P. R. China 4.University of Chinese Academy of Sciences, Beijing 100049, P. R. China
推荐引用方式 GB/T 7714	Wei, Shi-Jie,Zhang B,Tan XW,et al. A Real-time Human Activity Recognition Approach with Generalization Performance[C]. 见:. Shenyang, China. July 27-29, 2020.