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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Huang, Y. F., Hsu, Y. H., Chang, C. C., Liu, S. H., Wei, C. C., Yao, T. Y., & Lin, C. B. (2017). An improved sleep posture recognition based on force sensing resistors. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10192 LNAI, pp. 318–327). Springer Verlag. https://doi.org/10.1007/978-3-319-54430-4_31
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