Ahmed Nuzhat, Zhu Yong
Bioengineering 4+1 Program, Wilkes University, Wilkes-Barre, PA 18701, USA.
Mechanical Engineering, Wilkes University, Wilkes-Barre, PA 18701, USA.
Bioengineering (Basel). 2020 Feb 13;7(1):16. doi: 10.3390/bioengineering7010016.
Atrial fibrillation, often called AF is considered to be the most common type of cardiac arrhythmia, which is a major healthcare challenge. Early detection of AF and the appropriate treatment is crucial if the symptoms seem to be consistent and persistent. This research work focused on the development of a heart monitoring system which could be considered as a feasible solution in early detection of potential AF in real time. The objective was to bridge the gap in the market for a low-cost, at home use, noninvasive heart health monitoring system specifically designed to periodically monitor heart health in subjects with AF disorder concerns. The main characteristic of AF disorder is the considerably higher heartbeat and the varying period between observed R waves in electrocardiogram (ECG) signals. This proposed research was conducted to develop a low cost and easy to use device that measures and analyzes the heartbeat variations, varying time period between successive R peaks of the ECG signal and compares the result with the normal heart rate and RR intervals. Upon exceeding the threshold values, this device creates an alert to notify about the possible AF detection. The prototype for this research consisted of a Bitalino ECG sensor and electrodes, an Arduino microcontroller, and a simple circuit. The data was acquired and analyzed using the Arduino software in real time. The prototype was used to analyze healthy ECG data and using the MIT-BIH database the real AF patient data was analyzed, and reasonable threshold values were found, which yielded a reasonable success rate of AF detection.
心房颤动,通常称为房颤,被认为是最常见的心律失常类型,这是一个重大的医疗挑战。如果症状似乎持续且一致,早期检测房颤并进行适当治疗至关重要。这项研究工作专注于开发一种心脏监测系统,该系统可被视为实时早期检测潜在房颤的可行解决方案。目标是填补市场上低成本、家用、非侵入性心脏健康监测系统的空白,该系统专门设计用于定期监测有房颤疾病担忧的受试者的心脏健康。房颤疾病的主要特征是心跳明显加快以及心电图(ECG)信号中观察到的R波之间的间期变化。本研究旨在开发一种低成本且易于使用的设备,该设备可测量和分析心跳变化、心电图信号连续R峰之间的变化时间段,并将结果与正常心率和RR间期进行比较。一旦超过阈值,该设备就会发出警报,通知可能检测到房颤。本研究的原型包括一个Bitalino心电图传感器和电极、一个Arduino微控制器以及一个简单电路。使用Arduino软件实时采集和分析数据。该原型用于分析健康的心电图数据,并使用麻省理工学院 - 贝斯以色列女执事医疗中心(MIT - BIH)数据库分析真实房颤患者的数据,找到了合理的阈值,从而获得了合理的房颤检测成功率。