Recognizing human activities from accelerometer and physiological sensors

Sung Ihk Yang, Sung Bae Cho

Research output: Contribution to conferencePaper

18 Citations (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 to 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
Pages100-105
Number of pages6
DOIs
Publication statusPublished - 2008 Dec 1
Event2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI - Seoul, Korea, Republic of
Duration: 2008 Aug 202008 Aug 22

Other

Other2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI
CountryKorea, Republic of
CitySeoul
Period08/8/2008/8/22

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Computer Science Applications

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    Yang, S. I., & Cho, S. B. (2008). Recognizing human activities from accelerometer and physiological sensors. 100-105. Paper presented at 2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI, Seoul, Korea, Republic of. https://doi.org/10.1109/MFI.2008.4648116