NDLI: A novel outlier detection method for identifying torque-related transient patterns of in vivo muscle behavior

Content Provider	IEEE Xplore Digital Library
Author	Sheng Han Xin Chen Sheng Zhong Yongjin Zhou Zhiguo Zhang
Copyright Year	2014
Description	Author affiliation: Dept. of Electr. & Electron. Eng., Univ. of Hong Kong, Hong Kong, China (Sheng Han; Zhiguo Zhang) \|\| Guangdong Key Lab. for Biomed. Meas. & Ultrasound Imaging, Shenzhen Univ., Shenzhen, China (Xin Chen; Sheng Zhong; Yongjin Zhou)
Abstract	This paper proposed a novel outlier detection method, named l1-regularized outlier isolation and regression (LOIRE), to examine torque-related transient patterns of in vivo muscle behavior from multimodal signals, including electromyography (EMG), mechanomyography (MMG) and ultrasonography (US), during isometric muscle contraction. Eight subjects performed isometric ramp contraction of knee up to 90% of the maximal voluntary contraction, and EMG, MMG and US were simultaneously recorded from the rectus femoris muscle. Five features, including two root mean square amplitudes from EMG and MMG, muscle cross sectional area, muscle thickness and width from US were extracted. Then, local polynomial regression was used to obtain the signal-to-torque relationships and their derivatives. By assuming the signal-to-torque functions are basically quadratic, the LOIRE method is applied to identify transient torque-related patterns of EMG, MMG and US features as outliers of the linear derivative-to-torque functions. The results show that the LOIRE method can effectively reveal transient patterns in the signal-to-torque relationships (for example, sudden changes around 20% MVC can be observed from all features), providing important information about in vivo muscle behavior.
Sponsorship	IEEE Eng. Med. Biol. Soc.
Starting Page	4216
Ending Page	4219
File Size	937935
Page Count	4
File Format	PDF
ISBN	9781424479290
ISSN	1557170X
DOI	10.1109/EMBC.2014.6944554
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Muscles Torque Electromyography Transient analysis Polynomials Ultrasonic imaging In vivo
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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