Abstract
In this paper, we applied six force sensing-resistor sensors (FSR Sensors) to perform sleep posture recognition. The analog-to-digital converter (ADC) is used to extract the resistance signals of FSRs. The recorded FSR signals are averaged as reference pattern of six values. The reference patterns and test patterns of the postures are performed pattern matching with the mean squared error (MSE) method. With a scale adjusting method, the recognition accuracy is obtained by 87%. Moreover, after the moving average windows are adopted to remove the high ripple, the recognition accuracy can be improved to 96% with window length L = 7.
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Acknowledgments
This work was funded in part by Ministry of Science and Technology of Taiwan under Grant MOST 105-2221-E-324-019 and MOST 103-2632-E-324-001-MY3.
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Huang, YF. et al. (2017). An Improved Sleep Posture Recognition Based on Force Sensing Resistors. In: Nguyen, N., Tojo, S., Nguyen, L., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2017. Lecture Notes in Computer Science(), vol 10192. Springer, Cham. https://doi.org/10.1007/978-3-319-54430-4_31
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DOI: https://doi.org/10.1007/978-3-319-54430-4_31
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