Basiri, B. and Vali, M. and Agah, S. (2018) Classification of normal and dysphagia in patients with GERD using swallowing sound analysis. In: UNSPECIFIED.
Full text not available from this repository.Abstract
In recent years, acoustical analysis of the swallowing mechanism has received considerable attention and because of many damages of invasive methods, it is preferred. This paper proposes acoustic-based method to separate dysphagia patients with reflux disorder from normal persons. In this work, we have used swallowing sound of 22 individuals (11 normal and 11 abnormal). Swallowing sound signals were recorded with sound recorder over the trachea and ambient noise was removed and spectral features were extracted from the sounds. Classification is done by non-linear support vector machines, using leave-one-out. According to the experimental results, the system can classify 66.1 of total swallow signals correctly (signal accuracy) and 95.7 of the total subject in a group of healthy and dysphagia patients (subject accuracy). The experimental results show that the proposed system can provide concrete features for clinicians to diagnose dysphagia in reflux patients. © 2017 IEEE.
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Additional Information: | cited By 0 |
| Uncontrolled Keywords: | Artificial intelligence; Classification (of information); Signal analysis; Signal processing, Acoustical analysis; Ambient noise; dysphagia; Invasive methods; Leave one out; Non linear; Spectral feature; Swallowing sounds, Biological organs |
| Subjects: | WI Digestive System |
| Depositing User: | eprints admin |
| Date Deposited: | 17 Dec 2018 05:23 |
| Last Modified: | 17 Dec 2018 05:23 |
| URI: | http://eprints.iums.ac.ir/id/eprint/6792 |
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