A wearable computing approach for hand gesture and daily activity recognition in human-robot interaction
Chun Zhu · Journal of Shandong University · 2010
Human-robot interaction(HRI) is an important topic in robotics,especially in assistive robotics.In this pa-per,we addressed the HRI problem in a smart assisted living(SAIL) system for elderly people,patients,and the disa-bled.Two problems were sloved that are very important for developing natural HRI: hand gesture recognition and daily ac-tivity recognition.For the problem of hand gesture recognition,an inertial sensor is worn on a finger of the human subject to collect hand motion data.A neural network is used for gesture spotting and a two-layer hierarchical hidden Markov mod-el(HHMM) is applied to integrate the context information in the gesture recognition.For the problem of daily activity rec-ognition,two inertial sensors are attached to one foot and the waist of the subject.A multi-sensor fusion scheme was devel-oped for recognition.First,data from these two sensors are fused for coarse-grained classification.Second,the fine-grained classification module based on heuristic discrimination or hidden Markov models(HMMs) are applied to further distinguish the activities.Experiments were conducted using a prototype wearable sensor system and the obtained results proved the effectiveness and accuracy of our algorithms.