Sensor-activity relevance in human activity recognition with wearable motion sensors and mutual information criterion

Date
2014
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Source Title
Proceedings of the 28th International Symposium on Computer and Information Sciences, ISCIS 2013
Print ISSN
1876-1100
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Publisher
Springer
Volume
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Pages
285 - 294
Language
English
Type
Conference Paper
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Abstract

Selecting a suitable sensor configuration is an important aspect of recognizing human activities with wearable motion sensors. This problem encompasses selecting the number and type of the sensors, configuring them on the human body, and identifying the most informative sensor axes. In earlier work, researchers have used customized sensor configurations and compared their activity recognition rates with those of others. However, the results of these comparisons are dependent on the feature sets and the classifiers employed. In this study, we propose a novel approach that utilizes the time-domain distributions of the raw sensor measurements. We determine the most informative sensor types (among accelerometers, gyroscopes, and magnetometers), sensor locations (among torso, arms, and legs), and measurement axes (among three perpendicular coordinate axes at each sensor) based on the mutual information criterion.

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Keywords
Information science, Pattern recognition, Activity recognition, Coordinate axes, Human activities, Human activity recognition, Motion sensors, Mutual informations, Sensor configurations, Sensor location, Sensors
Citation
Published Version (Please cite this version)