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Updated: Jan 21, 2026
06:49
Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
Published on: December 11, 2015
9.3K
A Dual-Accelerometer System for Detecting Human Movement in a Free-living Environment
Anantha Narayanan1, Tom Stewart, Lisa Mackay
1School of Sport and Recreation, Auckland University of Technology, Auckland, NEW ZEALAND.
Medicine and Science in Sports and Exercise
|July 31, 2019
Summary
A dual-accelerometer system accurately measures human movement behaviors in semi free-living settings for both children and adults. The thigh-back placement combination demonstrated the highest classification accuracy for physical activity recognition.
Area of Science:
- Biomedical Engineering
- Human Movement Science
- Wearable Technology
Background:
- Accurate measurement of human movement behaviors is crucial for developing 24-hour movement profiles.
- Dual-accelerometer systems show promise for classifying behaviors in controlled settings.
Purpose of the Study:
- To validate a dual-accelerometer system in semi free-living conditions for children and adults.
- To evaluate the efficacy of different accelerometer placement sites (wrist, thigh, back).
Main Methods:
- Thirty participants (15 children) wore three accelerometers and a clip camera.
- A random forest machine-learning classifier was trained on accelerometer data.
- Evaluated three placement combinations (thigh-back, thigh-wrist, back-wrist) using cross-validation.
Main Results:
- The thigh-back accelerometer combination achieved the highest accuracy: 95.6% for adults (7 activity classes) and 92.0% for children (8 activity classes).
- Other placement combinations showed a significant drop in accuracy (at least 11.0%).
Conclusions:
- The dual-accelerometer system, validated in a lab, performs well in semi free-living conditions.
- Further research is needed to detect activity intensity and sleep for comprehensive health behavior assessment.
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