Wireless handheld ECG for stroke patient (CU ΣCG)
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วัตถุประสงค์
Ischemic Heart Disease (IHD) and stroke are statistically the leading causes of death world-wide. Both diseases deal with various types of cardiac arrhythmias, e.g. premature ventricular contractions (PVCs), ventricular and supra-ventricular tachycardia, atrial fibrillation. For monitoring and detecting such an irregular heart rhythm accurately, we are now developing a very cost-effective ECG monitor, which is implemented in 8-bit MCU with an efficient QRS detector using steep-slope algorithm and arrhythmia detection algorithm using a simple heart rate variability (HRV) parameter. This work shows the results of evaluating the real-time steep-slope algorithm using MIT-BIH Arrhythmia Database. The performance of this algorithm has 99.72% of sensitivity and 99.19% of positive predictivity. We then show the preliminary results of arrhythmia detection using various types of normal and abnormal ECGs from an ECG simulator. The result is, 18 of 20 ECG test signals were correctly detected.
แนวคิด เหตุผล หรือสมมติฐาน
Ischemic Heart Disease (IHD) and stroke are statistically the leading causes of death world-wide. Both diseases deal with various types of cardiac arrhythmias, e.g. premature ventricular contractions (PVCs), ventricular and supra-ventricular tachycardia, atrial fibrillation. For monitoring and detecting such an irregular heart rhythm accurately, we are now developing a very cost-effective ECG monitor, which is implemented in 8-bit MCU with an efficient QRS detector using steep-slope algorithm and arrhythmia detection algorithm using a simple heart rate variability (HRV) parameter. This work shows the results of evaluating the real-time steep-slope algorithm using MIT-BIH Arrhythmia Database. The performance of this algorithm has 99.72% of sensitivity and 99.19% of positive predictivity. We then show the preliminary results of arrhythmia detection using various types of normal and abnormal ECGs from an ECG simulator. The result is, 18 of 20 ECG test signals were correctly detected.
ผลงานตีพิมพ์
Lek-uthai, A., Somboon, P., & Teeramongkonrasmee, A. (2016, December). Development of a cost-effective ECG monitor for cardiac arrhythmia detection using heart rate variability. In 2016 9th Biomedical Engineering International Conference (BMEiCON) (pp. 1-5). IEEE.
Teeramongkonrasmee, A., Somboon, P., & Lek-uthai, A. (2017, August). Performance of a QRS detector on self-collected database using a handheld two-electrode ECG. In 2017 10th Biomedical Engineering International Conference (BMEiCON) (pp. 1-5). IEEE.
ความร่วมมือ
ศูนย์ความเป็นเลิศทางการแพทย์ด้านโรคหลอดเลือดสมองแบบครบวงจร โรงพยาบาลจุฬาลงกรณ์ สภากาชาดไทย
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