웨어러블 디바이스를 위한 실시간 부정맥 검출 및 BLE기반 데이터 통신 알고리즘 개발과 적용
Development of Real-Time Arrhythmia Detection and BLE-based Data Communication Algorithm for Wearable Devices
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초록
Because arrhythmia occurs irregularly, it should be examined for at least 24 hours for accurate diagnosis. For this reason, this paper developed firmware software for arrhythmia detection and prevented consumption of tem- poral and human resources and enabled continuous management and early diagnosis. Prior to the experiment, the interval between the R peaks of the QRS Complex was calculated using the Pan-Tompkins algorithm. The developed firmware software designed and implemented an algorithm to detect arrhythmia such as tachycardia, bradycardia, ventricular tachycardia, persistent tachycardia, and non-persistent tachycardia, and a data transmission format to monitor the collected data based on BLE. As a result of the experiment, arrhythmia was found in real time according to the change in BPM as designed in this paper. And the data quality for BLE communication was verified by com- paring the sensor’s serial communication value with the Android application reception value. In the future, wearable devices for real-time arrhythmia detection will be lightweight and developed firmware software will be applied.
Abstract
Because arrhythmia occurs irregularly, it should be examined for at least 24 hours for accurate diagnosis. For this reason, this paper developed firmware software for arrhythmia detection and prevented consumption of tem- poral and human resources and enabled continuous management and early diagnosis. Prior to the experiment, the interval between the R peaks of the QRS Complex was calculated using the Pan-Tompkins algorithm. The developed firmware software designed and implemented an algorithm to detect arrhythmia such as tachycardia, bradycardia, ventricular tachycardia, persistent tachycardia, and non-persistent tachycardia, and a data transmission format to monitor the collected data based on BLE. As a result of the experiment, arrhythmia was found in real time according to the change in BPM as designed in this paper. And the data quality for BLE communication was verified by com- paring the sensor’s serial communication value with the Android application reception value. In the future, wearable devices for real-time arrhythmia detection will be lightweight and developed firmware software will be applied.
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