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    题名: A Comparative Study on Human Activity Recognition Using Inertial Sensors in a Smartphone
    作者: Aiguo Wang;Guilin Chen;Jing Yang;Shenghui Zhao;Chih-Yung Chang
    关键词: Accelerometers;Gyroscopes;Acceleration;Sensor systems and applications;Biomedical monitoring;Legged locomotion
    日期: 2016-03-23
    上传时间: 2016-11-15 02:10:36 (UTC+8)
    出版者: IEEE
    摘要: Activity recognition plays an essential role in bridging the gap between the low-level sensor data and the high-level applications in ambient-assisted living systems. With the aim to obtain satisfactory recognition rate and adapt to various application scenarios, a variety of sensors have been exploited, among which, smartphone-embedded inertial sensors are widely applied due to its convenience, low cost, and intrusiveness. In this paper, we explore the power of triaxial accelerometer and gyroscope built-in a smartphone in recognizing human physical activities in situations, where they are used simultaneously or separately. A novel feature selection approach is then proposed in order to select a subset of discriminant features, construct an online activity recognizer with better generalization ability, and reduce the smartphone power consumption. Experimental results on a publicly available data set show that the fusion of both accelerometer and gyroscope data contributes to obtain better recognition performance than that of using single source data, and that the proposed feature selector outperforms three other comparative approaches in terms of four performance measures. In addition, great improvement in time performance can be achieved with an effective feature selector, indicating the way of power saving and its applicability to real-world activity recognition.
    關聯: IEEE Sensors Journal 16(11), p.4566-4578
    DOI: 10.1109/JSEN.2016.2545708
    显示于类别:[資訊工程學系暨研究所] 期刊論文

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