The effects of compressive sensing on extracted features from tri-axial swallowing accelerometry signals

Ervin Sejdić; Faezeh Movahedi; Zhenwei Zhang; Atsuko Kurosu; James L. Coyle

doi:10.1117/12.2225466

4 May 2016 The effects of compressive sensing on extracted features from tri-axial swallowing accelerometry signals

Ervin Sejdić, Faezeh Movahedi, Zhenwei Zhang, Atsuko Kurosu, James L. Coyle

Proceedings Volume 9857, Compressive Sensing V: From Diverse Modalities to Big Data Analytics; 985704 (2016) https://doi.org/10.1117/12.2225466
Event: SPIE Commercial + Scientific Sensing and Imaging, 2016, Baltimore, MD, United States

Abstract

Acquiring swallowing accelerometry signals using a comprehensive sensing scheme may be a desirable approach for monitoring swallowing safety for longer periods of time. However, it needs to be insured that signal characteristics can be recovered accurately from compressed samples. In this paper, we considered this issue by examining the effects of the number of acquired compressed samples on the calculated swallowing accelerometry signal features. We used tri-axial swallowing accelerometry signals acquired from seventeen stroke patients (106 swallows in total). From acquired signals, we extracted typically considered signal features from time, frequency and time-frequency domains. Next, we compared these features from the original signals (sampled using traditional sampling schemes) and compressively sampled signals. Our results have shown we can obtain accurate estimates of signal features even by using only a third of original samples.

Citation Download Citation

Ervin Sejdić, Faezeh Movahedi, Zhenwei Zhang, Atsuko Kurosu, and James L. Coyle "The effects of compressive sensing on extracted features from tri-axial swallowing accelerometry signals", Proc. SPIE 9857, Compressive Sensing V: From Diverse Modalities to Big Data Analytics, 985704 (4 May 2016); https://doi.org/10.1117/12.2225466

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