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http://dx.doi.org/10.5762/KAIS.2020.21.5.7

Cross Correlation based Signal Classification for Monitoring System of Abnormal Respiratory Status  

Lee, Deokwoo (Department of Computer Engineering, Keimyung University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.21, no.5, 2020 , pp. 7-13 More about this Journal
Abstract
This paper focuses on detecting abnormal patterns of respiration of humans. In this study, a contact-based device was used to acquire both normal and abnormal respiration signals. To this end, this paper reports the development of a monitoring system to investigate the respiratory status of humans in a normal environment. This work aims to classify the respiratory status, i.e., normal and abnormal status, quantitatively. The respiration signal is acquired using a contact-based medical device (BIOBPAC), and noise reduction is carried out before classifying the respiratory status. To reduce noise, a mixed filter that combines the Savitzky-Golay filter and Median filter is applied to the acquired respiration signals. The inter-class distance is maximized, and the intra-class distance is minimized. The proposed algorithm is straightforward and can be applied to a practical environment. In addition, the experimental results are provided to substantiate the proposed approach.
Keywords
Respiration signal; Classification; Cross correlation coefficient; Apnea; Intra class distance; Inter-class distance;
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