Abstract
In this work, a simple method for monitoring sleeping conditions by all-night breath sound measurement is proposed. Our research target is to develop and validate a high performance method to classify sleeping conditions into several stages based on breath sound. Subjects were recorded in home/group house using bluetooth breath sound sensor. Breath sound-based features extracted from time and spectral domains can accurately discriminate between snore or non-snore and respiratory variance of breath sound, and so on. This breath sound signal analysis method enables detection and analysis of apnea/hypopnea. This work is the first study that successfully used simple method to monitor sleeping conditions. The experiment validate the effectiveness of the proposed method.
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