Abstract
The automatic step detection is a crucial component for the analysis of vegetative locomotor coordination during monitoring the patients with Parkinson's disease. It is aimed to develop the algorithms for automatic step detection in the accelerometer signal, which will be integrated in sensor networks for neurological rehabilitation research. In this paper, three algorithms (Pan-Tompkins method, template matching method and peak detection based on combined dual-axial signals) are detailed described. Finally, these methods will be discussed by means of dis- and advantages.
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Ying, H., Silex, C., Schnitzer, A., Leonhardt, S., & Schiek, M. (2007). Automatic step detection in the accelerometer signal. In IFMBE Proceedings (Vol. 13, pp. 80–85). Springer Verlag. https://doi.org/10.1007/978-3-540-70994-7_14
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