Multi-sensor fusion for human daily activity recognition in robot-assisted living

In this paper, we propose a human activity recognition method by fusing the data from two wearable inertial sensors attached to one foot and the waist of a human subject, respectively. Our multi-sensor fusion based method combines neural networks and hidden Markov models (HMMs), and can reduce the c...

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Bibliographic Details
Published inProceedings of the 4th ACM/IEEE international conference on Human robot interaction pp. 303 - 304
Main Authors Zhu, Chun, Sheng, Weihua
Format Conference Proceeding
LanguageEnglish
Published New York, NY, USA ACM 09.03.2009
SeriesACM Conferences
Subjects
Computing methodologies > Machine learning
Information systems > Information systems applications
assisted living
sensor fusion
wearable sensor
activity recognition
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ISBN1605584045
9781605584041
DOI10.1145/1514095.1514187

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Summary:In this paper, we propose a human activity recognition method by fusing the data from two wearable inertial sensors attached to one foot and the waist of a human subject, respectively. Our multi-sensor fusion based method combines neural networks and hidden Markov models (HMMs), and can reduce the computation load. We conducted experiments using a prototype wearable sensor system and the obtained results prove the effectiveness and the accuracy of our algorithm.
ISBN:1605584045
9781605584041
DOI:10.1145/1514095.1514187