Department of Electrical and Computer Engineering, McGill University, Montreal, QC H3A 2T5, Canada.
MacDonald, Dettwiler and Associates Corporation, Ottawa, ON K2K 1Y5, Canada.
Sensors (Basel). 2019 Aug 8;19(16):3472. doi: 10.3390/s19163472.
Cardiography is an indispensable element of health care. However, the accessibility of at-home cardiac monitoring is limited by device complexity, accuracy, and cost. We have developed a real-time algorithm for heart rate monitoring and beat detection implemented in a custom-built, affordable system. These measurements were processed from seismocardiography (SCG) and gyrocardiography (GCG) signals recorded at the sternum, with concurrent electrocardiography (ECG) used as a reference. Our system demonstrated the feasibility of non-invasive electro-mechanical cardiac monitoring on supine, stationary subjects at a cost of $100, and with the SCG-GCG and ECG algorithms decoupled as standalone measurements. Testing was performed on 25 subjects in the supine position when relaxed, and when recovering from physical exercise, to record 23,984 cardiac cycles at heart rates in the range of 36-140 bpm. The correlation between the two measurements had r coefficients of 0.9783 and 0.9982 for normal (averaged) and instantaneous (beat identification) heart rates, respectively. At a sampling frequency of 250 Hz, the average computational time required was 0.088 s per measurement cycle, indicating the maximum refresh rate. A combined SCG and GCG measurement was found to improve accuracy due to fundamentally different noise rejection criteria in the mutually orthogonal signals. The speed, accuracy, and simplicity of our system validated its potential as a real-time, non-invasive, and affordable solution for outpatient cardiac monitoring in situations with negligible motion artifact.
心电图检查是医疗保健不可或缺的一部分。然而,家庭心脏监测的可及性受到设备复杂性、准确性和成本的限制。我们开发了一种实时心率监测和节拍检测算法,该算法在定制的、经济实惠的系统中实现。这些测量值是从胸骨处记录的地震心动图(SCG)和陀螺心动图(GCG)信号中处理得到的,同时使用心电图(ECG)作为参考。我们的系统展示了在成本为 100 美元的情况下,对仰卧、静止的受试者进行非侵入性机电心脏监测的可行性,并且 SCG-GCG 和 ECG 算法可以作为独立的测量值进行分离。在 25 名受试者仰卧放松和从体力活动中恢复时进行了测试,以记录心率在 36-140 bpm 范围内的 23984 个心动周期。两种测量方法的相关性在正常(平均)和瞬时(节拍识别)心率下的 r 系数分别为 0.9783 和 0.9982。在 250 Hz 的采样频率下,每个测量周期的平均计算时间为 0.088 秒,这是最大刷新速率。由于互成正交信号的基本不同的噪声抑制标准,SCG 和 GCG 的联合测量提高了准确性。我们的系统具有速度快、准确性高和简单易用的特点,验证了其作为一种实时、非侵入性和经济实惠的门诊心脏监测解决方案的潜力,适用于运动伪影可忽略不计的情况。