NDLI: A hybrid HMM/SVM classifier for motion recognition using μIMU data

Content Provider	IEEE Xplore Digital Library
Author	Weiwei Wan Hong Liu Lianzhi Wang Guangyi Shi Li, W.J.
Copyright Year	2007
Description	Author affiliation: Shenzhen Grad. Sch., Peking Univ., Beijing (Weiwei Wan; Hong Liu)
Abstract	This paper describes a novel approach for human motion recognition via motion features extracted from sensor data. The classification process consists of two phases. The first one is a preprocessing of raw signals. Median Filter is used to filter pulse noise while vector quantization is used for Gaussian noise and reducing dimensions in this phase. The second one consists of a hybrid HMM/SVM classifier. Outputs from the first phase will be estimated by different pre-trained HMMs, and the results of the likelihood will be classified by the SVM classifier to identify the motion. With data collected from the mulMU equipment, falling-down motion can be told from non-falling- down motions with a correct recognition rate better than 99%. When the SVM training samples are labeled carefully and chosen bias, 100% correct recognition rate can be reached. The algorithm proves robustness and accuracy.
Starting Page	115
Ending Page	120
File Size	598758
Page Count	6
File Format	PDF
ISBN	9781424417612
DOI	10.1109/ROBIO.2007.4522145
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-12-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hidden Markov models Support vector machines Support vector machine classification Filters Gaussian noise Humans Feature extraction Data mining Sensor phenomena and characterization Noise reduction μIMU Human motion recognition HMM SVM
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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