압전센서를 통한 호흡 측정 및 수면 중 무호흡 검출 실험과 분석
Breathing Measurement and Sleep Apnea Detection Experiment and Analysis using Piezoelectric Sensor
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초록
In this paper, we implemented a respiration measurement system consisting of piezoelectric sensor, respiration signal processing device, and a viewer on a notebook. We tried an experiment for measuring respiration and detecting sleep apnea syndrome when a subject lay on a bed. We applied the respiration measurement algorithm to sensor data obtained from four subjects. In order to get a good graph shape, data manipulation methods such as moving averages and maximum values were applied. The window size for moving average was chosen as N=70, and the threshold value for each subject was customized. In this case, the proposed system showed 96.0% accuracy. When the maximum value among 90 data was applied instead of moving average, our system achieved 95.1% accuracy. In an experiment for detecting sleep apnea syndrome, the system showed that sleep apnea occurred correctly and calculated the average interval of sleep apnea. While infants or the elderly as well as patients with sleep apnea syndrome are lying down on a bed, our results are also expected to be able to cope with some accidental emergency situation by observing their respiration and detecting sleep apnea.
Abstract
In this paper, we implemented a respiration measurement system consisting of piezoelectric sensor, respiration signal processing device, and a viewer on a notebook. We tried an experiment for measuring respiration and detecting sleep apnea syndrome when a subject lay on a bed. We applied the respiration measurement algorithm to sensor data obtained from four subjects. In order to get a good graph shape, data manipulation methods such as moving averages and maximum values were applied. The window size for moving average was chosen as N=70, and the threshold value for each subject was customized. In this case, the proposed system showed 96.0% accuracy. When the maximum value among 90 data was applied instead of moving average, our system achieved 95.1% accuracy. In an experiment for detecting sleep apnea syndrome, the system showed that sleep apnea occurred correctly and calculated the average interval of sleep apnea. While infants or the elderly as well as patients with sleep apnea syndrome are lying down on a bed, our results are also expected to be able to cope with some accidental emergency situation by observing their respiration and detecting sleep apnea.
참고문헌 (13)
- "Owelt Monitor"[URL]
- "Sleep Time"[URL]
- "Korea Centers for Disease Control and Prevention"[URL]
- Min Myeong Ki, "A Study on the Respiration Calculation using Double Threshold from Piezoelectric Sensor Signal during Sleep", Korea Information and Communications Society Conference, pp.3~4 (2014)
- 이명호, "전기용량성 섬유 압력센서를 이용한 호흡측정 시스템", 전기학회 논문지 P권, 59(1), pp.58~63 (2010), 대한전기학회
- Jang Yu Rim, "An Algorithm for Respiration Rate and Depth Estimation using Force Sensing Resistor", Proceedings of Korean Institute of Communications and Information Sciences, pp.688~689 (2017)
- T. Reinvuo, "Measurement of Respiratory Rate with high-Resolution Accelerometer and EMFit Pressure Sensor", SAS’06, IEEE Sensors Applications Symposium, pp.192~195 (2006)
- Y. Yamana, "A Sensor for Monitoring Pulse Rate, Respiration Rhythm, and Body Movement in Bed", The 33rd Annual International Conference of the IEEE EMBC (Engineering in Medicine International Biology Society), pp.5323~5326 (2011)
- Xin Zhu, "Analysis of Pulse Rate, Respiration Rhythm, and Body Movement during Sleep Detected by Pressure Sensor", The 2nd International Symposium on Aware Computing(ISAC), pp.213~219 (2010)
- Ji-Young Cha, "Unconstrained Respiration and Heart Rate Monitoring System Based on a PPG Pillow during Sleep", The 30th Annual International IEEE EMBS Conference, pp.3224~3226 (2008)
- "Texas Instruments"[URL]
- "Interlink Electronics"[URL]
- "EMFIT"[URL]