Long-term signal detection, segmentation and summarization using wavelets and fractal dimension: a bioacoustics application in gastrointestinal-motility monitoring |
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Authors: | Dimoulas C Kalliris G Papanikolaou G Kalampakas A |
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Affiliation: | Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki University Campus, 54124, Greece. babis@eng.auth.gr |
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Abstract: | The current paper describes a wavelet-based method for long-term processing and analysis of gastrointestinal sounds (GIS). Windowing techniques are used to select sequential blocks of the prolonged multi-channel recordings and proceed to various wavelet-domain processing stages. De-noising, significant-activity detection, automated segmentation and extraction of summary curves are applied in an integrated mode, allowing for enhanced content manipulation and analysis. The proposed analysis scheme combines flexible long-term graphical representation tools, while maintaining the ability of quick browsing via visualization and auralization of the detected short-term events. This work is part of a project aiming to implement non-invasive diagnosis over gastrointestinal-motility (GIM) physiology. However, the proposed techniques might be applied to any study of long-term bioacoustics time series. |
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Keywords: | Wavelets Fractal dimension De-noising Long-term processing Signal detection Bowel sounds Gastrointestinal sounds Gastrointestinal phonography Gastrointestinal motility |
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