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arXiv · 2309.06673

Ridge detection for nonstationary multicomponent signals with time-varying wave-shape functions and its applications

Yan-Wei Su·Gi-Ren Liu·Yuan-Chung Sheu·Hau-Tieng Wu
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Abstract

We introduce a novel ridge detection algorithm for time-frequency (TF) analysis, particularly tailored for intricate nonstationary time series encompassing multiple non-sinusoidal oscillatory components. The algorithm is rooted in the distinctive geometric patterns that emerge in the TF domain due to such non-sinusoidal oscillations. We term this method \textit{shape-adaptive mode decomposition-based multiple harmonic ridge detection} (\textsf{SAMD-MHRD}). A swift implementation is available when supplementary information is at hand. We demonstrate the practical utility of \textsf{SAMD-MHRD} through its application to a real-world challenge. We employ it to devise a cutting-edge walking activity detection algorithm, leveraging accelerometer signals from an inertial measurement unit across diverse body locations of a moving subject.

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Yan-Wei Su, Gi-Ren Liu, Yuan-Chung Sheu, Hau-Tieng Wu. 2023-09-13. Ridge detection for nonstationary multicomponent signals with time-varying wave-shape functions and its applications. https://arxiv.org/abs/2309.06673

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