스마트폰을 이용한 심호흡 기반 자율신경계 테스트
Testing of Autonomic Nervous System by Deep Breathing Using a Smartphone
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초록
심호흡을 통해서 심박수 변이를 측정하고, 이를 이용하여 자율신경계를 평가하는 것은 잘 알려진 방법으로 다양한 임상 분야에서 널리 이용되고있다. 병원에서는 이를 위해서 고가의 장비가 설치되고 전문가에 의해서 운용되고 있다. 논문에서는 스마트폰을 이용하여 언제 어디서나 간편하게심호흡을 통해서 자율신경계를 테스트할 수 있는 앱을 개발하고, 실험을 통해서 개발된 앱을 검증하였다. 실험은 지원자 8명에 대해서 순천향대학교천안병원 신경과 임상실에서 진행되었다. 지원자에 대한 자율신경계 테스트를 다음 두 가지 방법으로 진행하였다. 먼저 병원에 설치된 근전도검사기를 이용하였고, 다음에 동일한 조건에서 개발된 앱을 적용하였다. Pearson 방법을 이용하여 이 두 가지 방법의 실험 결과간에 상관 분석을수행하였고, 분석 결과는 0.98의 매우 높은 상관관계를 보여준다.
Abstract
Measuring heart rate variability by deep breathing and using this to evaluate the autonomic nervous system is a well-known methodwidely used in various clinical fields. In hospitals, expensive equipment is installed and managed by experts for this purpose. Thispaper discusses an app we developed that can easily test the autonomic nervous system by deep breathing anytime, anywhere usinga smartphone, and then reviews experiments performed to verify the results. The experiments were conducted in the clinical roomof the Department of Neurology at Soonchunhyang University Cheonan Hospital on eight volunteers. We tested the autonomic nervoussystems of the volunteers first with an electromyography device installed in the hospital and then with the app under identical conditions. We performed a correlation analysis on the results of these two methods using the Pearson method, and this yielded a very highcorrelation of 0.98.
참고문헌 (16)
- Larry R. Squire, "Encyclopedia of Neuroscience" (2009), Academic Press
- F. Yasuma no, "Respiratory sinus arrhythmia : Why does the heartbeat synchronize with respiratory rhythm?", CHEST, 125(2), pp.683~690 (2004)
- P. M. Lehrer, "Using technology in mental health practice", pp.123~141, American Psychological Association
- R. W. Shields, "Heart rate variability with deep breathing as a clinical test of cardiovagal function", Cleveland Clinic Journal of Medicine, 76(2) (2009)
- D. Löllgen, "The deep breathing test : Median-based expiration-inspiration difference is the measure of choice", Muscle & Nerve, 39(4), pp.536~544 (2009)
- P. Novak, "Quantitative autonomic testing", journal of visualized experiments, 53, pp.1~24 (2011)
- "NEUROLITE Advanced Medical Solutions"[URL]
- R. Banerjee, "PhotoECG : Photoplethysmographyto estimate ECG parameters", 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.4404~4408 (2014)
- J. Allen, "Photoplethysmography and its application in clinical physiological measurement", Physiological Measurement, 28(3) (2007)
- M. Shabaan, "Survey : Smartphone-based assessment of cardiovascular diseases using ECG and PPG analysis", BMC Medical Informatics and Decision Making, 20, pp.1~16 (2020)
- M. J. Gregoski, "Development and validation of a smartphone heart rate acquisition application for health promotion and wellness telehealth applications", International Journal of Telemedicine and Applications, 2012(1) (2012)
- Y. Nam, "Respiratory rate estimation from the built-in cameras of smartphones and tablets", Annuals of Biomedical Engineering, 42(4), pp.885~898 (2014)
- A. Nemcova, "Monitoring of heart rate, blood oxygen saturation, and blood pressure using a smartphone", Biomedical Signal Processing and Control, 59 (2020)
- "Samsung Galaxy Watch review"[URL]
- "Apple Watch Series 7 review"[URL]
- "Camera API"[URL]