A Fast and Simple Method for Sleep Breathing Cycle Segmentation in Time Domain

An automatic sleep respiratory cycle segmentation method in time-domain is introduced. Unlike the methods using spectral analysis that require high computational process such as Fourier transform, our approach uses a nonoverlapping window for simple computation in time domain, which is suitable for...

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Bibliographic Details
Published in2024 18th International Conference on Ubiquitous Information Management and Communication (IMCOM) pp. 1 - 3
Main Authors Park, Rayoung, Lee, Heonzoo, Nguyen, Tan Loc, Kim, Sejin, Won, Yonggwan
Format Conference Proceeding
LanguageEnglish
Published IEEE 03.01.2024
Subjects
Fourier transforms
Information management
inspiration and expiration pauses
nonoverlapping moving window
Optimization
signal stairization
Sleep apnea
sleep respiratory cycles segmentation
Spectral analysis
Time-domain analysis
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Summary:An automatic sleep respiratory cycle segmentation method in time-domain is introduced. Unlike the methods using spectral analysis that require high computational process such as Fourier transform, our approach uses a nonoverlapping window for simple computation in time domain, which is suitable for low power computing systems. Typical sleep breathing sound files over 6-hour length were used to evaluate our method, and the experimental results showed that our method demonstrated the accuracy over 95% and possible improvement with further investigation on parameter optimization for the steps by close examination of the signal characteristics.
DOI:10.1109/IMCOM60618.2024.10418430