Wearable Sensor-Based Hand Gesture and Daily Activity Recognition for Robot-Assisted Living

Authors:
Chun Zhu; Weihua Sheng
Affiliations:
Sch. of Electr. & Comput. Eng., Oklahoma State Univ., Stillwater, OK, USA;-
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Year:
2011

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Abstract

In this paper, we address natural human-robot interaction (HRI) in a smart assisted living (SAIL) system for the elderly and the disabled. Two common HRI problems are studied: hand gesture recognition and daily activity recognition. For hand gesture recognition, we implemented a neural network for gesture spotting and a hierarchical hidden Markov model for context-based recognition. For daily activity recognition, a multisensor fusion scheme is developed to process motion data collected from the foot and the waist of a human subject. Experiments using a prototype wearable sensor system show the effectiveness and accuracy of our algorithms.