Abstract
The human balance ability is investigated using a multi-sensor human balance assessment system. Based on the pressure sensor, the gyroscope, the accelerometer and the magnetometer, the quantitative perception of human balance under different postures is realized. The characteristics of human balance ability are extracted through time domain methods and a new hybrid feature extraction. The results demonstrate that the hybrid feature extraction method with the support vector machine method can effectively classify and evaluate the human balance ability under different postures.
Research supported by the National Natural Science Foundation of China (61473265,61803344), the Post-doctoral Funding in Henan province (001703041) and the Innovation Research Team of Science & Technology of Henan Province (17IRTSTHN013).
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Ren, H., Yue, Z., Liu, Y. (2019). Multi-sensor Based Human Balance Analysis. In: Yu, H., Liu, J., Liu, L., Ju, Z., Liu, Y., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2019. Lecture Notes in Computer Science(), vol 11741. Springer, Cham. https://doi.org/10.1007/978-3-030-27532-7_38
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DOI: https://doi.org/10.1007/978-3-030-27532-7_38
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