심정지 감지를 위한 다생체 신호 측정 웨어러블 디바이스 개발
Multi-modal Wearable Device for Cardiac Arrest Detection
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참고문헌
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초록
Cardiac arrest is owing to the failure of the heart that makes the blood circulation stop. Arrested blood circulation prevents the supply of the oxygen and the glucose and it results the loss of consciousness and, finally, brain death. Many public institution installed the AED for emergency treatment, but, it is not efficient when the patient is alone. In this paper, we made multiplexed wearable device for cardiac arrest detection. With this device, we measure the individual’s electrocardiography, heart sound and motion. If the cardiac arrest is detected, the device make a warning horn and transmit the signal for defibrillation. We obtain 98.33% of ECG data, 94.5% of PCG data and 98.38% of IMU data accuracy for each evaluation and 93.33% accuracy for integrated evaluation.
Abstract
Cardiac arrest is owing to the failure of the heart that makes the blood circulation stop. Arrested blood circulation prevents the supply of the oxygen and the glucose and it results the loss of consciousness and, finally, brain death. Many public institution installed the AED for emergency treatment, but, it is not efficient when the patient is alone. In this paper, we made multiplexed wearable device for cardiac arrest detection. With this device, we measure the individual’s electrocardiography, heart sound and motion. If the cardiac arrest is detected, the device make a warning horn and transmit the signal for defibrillation. We obtain 98.33% of ECG data, 94.5% of PCG data and 98.38% of IMU data accuracy for each evaluation and 93.33% accuracy for integrated evaluation.
참고문헌 (13)
- "What is Sudden Cardiac Arrest" (2016)[URL]
- "What Causes Sudden Cardiac Arrest" (2016)[URL]
- S.Y. Sin, "Survival Rate of Out of Hospital CA Patients", Korean Institute of fire science & engineering International symposium (2014)
- Johnson Francis, "Wearable cardioverter defibrillator: A life vest till the life boat (ICD) arrives", Indian Heart Journal, 66(1), pp.68~72 (2014)
- Richard Kobza, "Recorded heart sounds for identification of ventricular tachycardia", Resuscitation, 79(2), pp.265~272 (2008)
- A.K. Bourke, "A threshold-based fall-detection algorithm using a bi-axial gyroscope sensor", Medical Engineering & Physics, 30(1), pp.84~90 (2008)
- A.K. Bourke, "Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm", Gait & Posture, 26(2), pp.194~199 (2007)
- Madalena Costa, "PhysioNet : and NIH research resource for complex signals", Journal of Electrocardiology, 36(1), pp.139~144 (2003)
- GD Clifford, "Classification of Normal", Abnormal Heart Sound Recordings : the PhysioNet, Computing in Cardiology Conference (CinC), pp.2016[DOI]
- JIAPU PAN, "A Real-Time QRS Detection Algorithm", IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, BME-32(3), pp.230~236 (1985)
- H. Liang, "Heart sound segmentation algorithm based on heart sound envelogram", Computers in Cardiology (1997)
- Kumar D, "A new algorithm for detection of S1 and S2 heart sounds", Acoustics, Speech and Signal Processing, 2006ICASSP 2006 Proceedings 2006 IEEE International Conference, pp.II~II (2006), IEEE