篇名 |
A Machine-Learning-Based Detection Method for Snoring and Coughing
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並列篇名 | A Machine-Learning-Based Detection Method for Snoring and Coughing |
作者 | Chun-Hung Yang、Yung-Ming Kuo、I-Chun Chen、Fan-Min Lin、Pau-Choo Chung |
英文摘要 | Poor sleep quality is a common disease for modern people. Snoring is one of the essential indicators to measure Obstructive Sleep Apnea (OSA). When sleeping, the number of episodes of snoring and coughing are related to the estimated sleep quality. This study proposes a method to detect snoring and coughing in patients when sleeping. The proposed method includes three stages. Firstly, the nightly sound data for a patient are segmented to each independent event. Secondly, the time domain signal is changed to a frequency domain signal by Fourier Transform, and then the features are extracted from the snoring and coughing episodes. Lastly, the Support Vector Machine (SVM) and the Hidden Markov Model (HMM) are used to recognize snoring and coughing. The result of our experiment demonstrates that this method has good detection performance.
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起訖頁 | 1233-1244 |
關鍵詞 | Coughing detection、Snoring detection、Machine learning、Hidden Markov Model、Support Vector Machine |
刊名 | 網際網路技術學刊 |
期數 | 202211 (23:6期) |
出版單位 | 台灣學術網路管理委員會 |
DOI |
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