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Multi-Level Fusion Activity Recognition Framework using Smart Devices
http://doi.org/10.5626/JOK.2018.45.9.950
Traditional inertial sensor based activity recognition methods in which multiple sensor units are attached to the body is changing to accommodate the use of smart devices such as smartphones and smartwatches. In this paper, we propose a multi-level fusion activity recognition framework to recognize daily activities using smartphones and smartwatches which can be purchased easily for minimum sensor based activity recognition. The proposed framework uses various types of fusion techniques such as data fusion, feature fusion, and decision fusion. While the proposed framework does not use common methods of decision fusion such as majority voting or weighted voting, it does use posterior probability based fusion for better accuracy and confidence. Experiments are conducted to compare results between using and not using the probability and between using and not using each fusion technique. The results demonstrated the excellent performance of the proposed framework.
Accurate Step-Count Detection based on Recognition of Smartphone Hold Position
Taeho Hur, Haneul Yeom, Sungyoung Lee
As the walking exercise is emphasized in personalized healthcare, numerous services demand walking information. Along with the propagation of smartphones nowadays, many step-counter applications have been released. But these applications are error-prone to abnormal movements such as simple shaking or vibrations; also, different step counts are shown when the phone is positioned in different locations of the body. In this paper, the proposed method accurately counts the steps regardless of the smartphone position by using an accelerometer and a proximity sensor. A threshold is set on each of the six positions to minimize the error of undetection and over-detection, and the cut-off section is set to eliminate any noise. The test results show that the six position type were successfully identified, and through a comparison experiment with the existing application, the proposed technique was verified as superior in terms of accuracy.
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