Wearable Human Activity Recognition by Electrocardiograph and Accelerometer

This paper proposes a human activity estimation system using a wearable multi-sensor with a built-in electrocardiograph and triaxial accelerometers. The multi-sensor unconstraintly measures biological information, and provides these data to personal computer by wireless communication. We estimate hu...

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Bibliographic Details
Published in2013 IEEE 43rd International Symposium on Multiple-Valued Logic pp. 12 - 17
Main Authors Fujimoto, T., Nakajima, H., Tsuchiya, N., Marukawa, H., Kuramoto, K., Kobashi, S., Hata, Y.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2013
Subjects
Acceleration
Accelerometers
decision tree
Decision trees
electrocardiogram
Electrocardiography
Estimation
fuzzy logic
Heart rate
human activity
multi-sensor system
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ISBN9781467360678
1467360678
ISSN0195-623X
DOI10.1109/ISMVL.2013.60

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Summary:This paper proposes a human activity estimation system using a wearable multi-sensor with a built-in electrocardiograph and triaxial accelerometers. The multi-sensor unconstraintly measures biological information, and provides these data to personal computer by wireless communication. We estimate human activity in a series of activities by the biological information. In our experiment, the subjects have several activities such as "Walking", "Rest" and "Strength training". The system estimates these activities by a decision tree. Branch conditions of the decision tree are aided by fuzzy logic and state of activity transition from previous activity. Fuzzy membership functions are constructed from exercise intensity, distinction frequency and transitional probability. As the results, the proposed method estimated activities with good accuracy.
ISBN:9781467360678
1467360678
ISSN:0195-623X
DOI:10.1109/ISMVL.2013.60