Recognizing human activities from accelerometer and physiological sensors

Sung Ihk Yang, Sung Bae Cho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Recently the interest about the services in the ubiquitous environment has increased. These kinds of services are focusing on the context of the user's activities, location or environment. There were many studies about recognizing these contexts using various sensory resources. To recognize human activity, many of them used an accelerometer, which shows good accuracy to recognize the user's activities of movements, but they did not recognize stable activities which can be classified by the user's emotion and inferred by physiological sensors. In this paper, we exploit multiple sensor signals to recognize user's activity. As Armband includes an accelerometer and physiological sensors, we used them with a fuzzy Bayesian network for the continuous sensor data. The fuzzy membership function uses three stages differed by the distribution of each sensor data. Experiments in the activity recognition accuracy have conducted by the combination of the usages of accelerometers and physiological signals. For the result, the total accuracy appears to be 74.4% for the activities including dynamic activities and stable activities, using the physiological signals and one 2-axis accelerometer. When we use only the physiological signals the accuracy is 60.9%, and when we use the 2 axis accelerometer the accuracy is 44.2%. We show that using physiological signals with accelerometer is more efficient in recognizing activities.

Original languageEnglish
Title of host publicationMultisensor Fusion and Integration for Intelligent Systems
Subtitle of host publicationAn Edition of the Selected Papers from the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems 2008
Pages187-199
Number of pages13
DOIs
Publication statusPublished - 2009 Sep 25
Event7th IEEE International Conference on Multi-Sensor Integration and Fusion, IEEE MFI 2008 - Seoul, Korea, Republic of
Duration: 2008 Aug 202008 Aug 22

Publication series

NameLecture Notes in Electrical Engineering
Volume35 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Other

Other7th IEEE International Conference on Multi-Sensor Integration and Fusion, IEEE MFI 2008
CountryKorea, Republic of
CitySeoul
Period08/8/2008/8/22

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

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    Yang, S. I., & Cho, S. B. (2009). Recognizing human activities from accelerometer and physiological sensors. In Multisensor Fusion and Integration for Intelligent Systems: An Edition of the Selected Papers from the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems 2008 (pp. 187-199). (Lecture Notes in Electrical Engineering; Vol. 35 LNEE). https://doi.org/10.1007/978-3-540-89859-7_14