Long-term signal detection, segmentation and summarization using wavelets and fractal dimension: a bioacoustics application in gastrointestinal-motility monitoring.
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.
Dimoulas
C
C
Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki University Campus, 54124, Greece. babis@eng.auth.gr
Kalliris
G
G
Papanikolaou
G
G
Kalampakas
A
A
D000465:Algorithms; D016477:Artifacts; D002940:Circadian Rhythm / Q000502:physiology; D003196:Computer Graphics; D005215:Fasting; D017709:Fractals; D005769:Gastrointestinal Motility / Q000502:physiology*; D006801:Humans; D008432:Mathematical Computing; D018670:Monitoring, Ambulatory; D019518:Postprandial Period / Q000502:physiology; D012016:Reference Values; D012815:Signal Processing, Computer-Assisted; D012984:Software; D013018:Sound Spectrography