the automatic recognition and counting of cough咳嗽的自动识别和计数.pdf

Cough BioMed Central Methodology Open Access The automatic recognition and counting of cough 1 1 2 Samantha J Barry , Adrie D Dane , Alyn H Morice* and Anthony D Walmsley 1 Address: 1Department of Chemistry, Faculty of Science and the Environment, University of Hull, Cottingham Road, Hull, HU6 7RX, UK and 2Department of Academic Medicine, University of Hull, Cottingham Road, Hull, HU6 7RX, UK Email: Samantha J Barry - s.j.barry@chem.hull.ac.uk; Adrie D Dane - adriedane@; Alyn H Morice* - a.h.morice@hull.ac.uk; Anthony D Walmsley - a.d.walmsley@hull.ac.uk * Corresponding author Published: 28 September 2006 Received: 02 March 2006 Accepted: 28 September 2006 Cough 2006, 2:8 doi:10.1186/1745-9974-2-8 This article is available from: /content/2/1/8 © 2006 Barry et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: Cough recordings have been undertaken for many years but the analysis of cough frequency and the temporal relation to trigger factors have proven problematic. Because cough is episodic, data collection over many hours is required, along with real-time aural analysis which is equally time-consuming. A method has been developed for the automatic rec