Motion-Pattern Recognition System Using a Wavelet-Neural Network

This paper presents a wavelet-neural network recognition system for personal fitness assistance and elderly daily activity monitoring applications. This discrete wavelet transform radial basis neural network (DWT-RBNN) analyzes vibration induced by human motions, and identifies motion status automat...

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Veröffentlicht in:IEEE transactions on consumer electronics 2019-05, Vol.65 (2), p.170-178
Hauptverfasser: Yang, Wen-Ren, Wang, Chau-Shing, Chen, Chien-Pu
Format: Artikel
Sprache:eng
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Zusammenfassung:This paper presents a wavelet-neural network recognition system for personal fitness assistance and elderly daily activity monitoring applications. This discrete wavelet transform radial basis neural network (DWT-RBNN) analyzes vibration induced by human motions, and identifies motion status automatically. The 3-D vibration signals are measured by integrated accelerometer chip, and then DWT extracts vibration features. Local energy of extracted feature is calculated and used by RBNN. A multi-channel RBNN is designed and used for recognition. The computation burden is reduced because of the DWT pre-processing. From experiment results, RBNN shows successful recognition capability. This paper also presents flow diagram to determine engineering parameters for the present and future product developments.
ISSN:0098-3063
1558-4127
DOI:10.1109/TCE.2019.2895050