Non-contact optical fiber sensing-based sleep breathing event classification using enhanced K-nearest neighbor

Huasong Zhao; Honghai Wang; Tao Zhao

doi:10.1117/12.2687601

28 August 2023 Non-contact optical fiber sensing-based sleep breathing event classification using enhanced K-nearest neighbor

Huasong Zhao, Honghai Wang, Tao Zhao

Author Affiliations +

Proceedings Volume 12724, Second International Conference on Biomedical and Intelligent Systems (IC-BIS 2023); 127241M (2023) https://doi.org/10.1117/12.2687601
Event: Second International Conference on Biomedical and Intelligent Systems (IC-BIS2023), 2023, Xiamen, China

Abstract

Monitoring and recognizing sleep breathing events have important implications in the preliminary diagnosis of respiratory diseases. However, conventional sleep breathing monitoring devices that come in contact with human skin can cause sleep discomfort and thus affect sleep outcome, and they cannot monitor sleep breathing events for a long time. In this study, we propose a non-contact system based on fiber optic sensing for long-term sleep breathing event monitoring. A K-nearest neighbor(KNN) respiratory event classification method based on Gaussian kernel function and ball tree search is proposed to improve the accuracy of respiratory event classification and apnea localization. The changes in morphological features of respiratory signals are characterized by time domain, frequency domain, and waveform decomposition for feature extraction. The system collected overnight sleep breathing data from 30 subjects in sync with a polysomnography system, totaling 2000 breathing event samples (100 s per sample), and tested the enhanced KNN classification model. The experimental results show that the accuracy of the classification model reaches 96.4%, which is 2.1% higher than that of the traditional KNN classification model. The training time is reduced by 1.71 s, and the testing time is reduced by 0.02 s.

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Huasong Zhao, Honghai Wang, and Tao Zhao "Non-contact optical fiber sensing-based sleep breathing event classification using enhanced K-nearest neighbor", Proc. SPIE 12724, Second International Conference on Biomedical and Intelligent Systems (IC-BIS 2023), 127241M (28 August 2023); https://doi.org/10.1117/12.2687601

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KEYWORDS

Fiber optics sensors

Classification systems

Sleep apnea

Feature extraction

Optical sensing

Optical fibers

Education and training

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