Human motion recognition using a wireless sensor-based wearable system

Authors:
John Paul Varkey;Dario Pompili;Theodore A. Walls
Affiliations:
Department of Electrical and Computer Engineering, Rutgers University, New Brunswick, USA;Department of Electrical and Computer Engineering, Rutgers University, New Brunswick, USA;Department of Psychology, University of Rhode Island, Kingston, USA
Venue:
Personal and Ubiquitous Computing
Year:
2012

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Abstract

The future of human computer interaction systems lies in how intelligently these systems can take into account the user's context. Research on recognizing the daily activities of people has progressed steadily, but little focus has been devoted to recognizing jointly activities as well as movements in a specific activity. For many applications such as rehabilitation, sports medicine, geriatric care, and health/fitness monitoring the importance of combined recognition of activity and movements can drive health care outcomes. A novel algorithm is proposed that can be tuned to recognize on-the-fly range of activities and fine movements within a specific activity. Performance of the algorithm and a case study on obtaining optimal features from sensor and parameter values for the algorithm to detect fine motor movements are presented.