García Limón José Alberto, Martínez-Suárez Frank, Alvarado-Serrano Carlos
Bioelectronics Section, Department of Electrical Engineering, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (CINVESTAV), Mexico City 07360, Mexico.
Micromachines (Basel). 2023 Sep 7;14(9):1748. doi: 10.3390/mi14091748.
Cardiovascular diseases are currently the leading cause of death worldwide. Thus, there is a need for non-invasive ambulatory (Holter) ECG monitors with automatic measurements of ECG intervals to evaluate electrocardiographic abnormalities of patients with cardiac diseases. This work presents the implementation of algorithms in an FPGA for beat-to-beat heart rate and RT interval measurements based on the continuous wavelet transform (CWT) with splines for a prototype of an ambulatory ECG monitor of three leads. The prototype's main elements are an analog-digital converter ADS1294, an FPGA of Xilinx XC7A35T-ICPG236C of the Artix-7 family of low consumption, immersed in a low-scale Cmod-A7 development card integration, an LCD display and a micro-SD memory of 16 Gb. A main state machine initializes and manages the simultaneous acquisition of three leads from the ADS1294 and filters the signals using a FIR filter. The algorithm based on the CWT with splines detects the QRS complex (R or S wave) and then the T-wave end using a search window. Finally, the heart rate (60/RR interval) and the RT interval (from R peak to T-wave end) are calculated for analysis of its dynamics. The micro-SD memory stores the three leads and the RR and RT intervals, and an LCD screen displays the beat-to-beat values of heart rate, RT interval and the electrode connection. The algorithm implemented on the FPGA achieved satisfactory results in detecting different morphologies of QRS complexes and T wave in real time for the analysis of heart rate and RT interval dynamics.
心血管疾病是目前全球主要的死亡原因。因此,需要一种能够自动测量心电图间期的非侵入式动态(Holter)心电图监测仪,以评估心脏病患者的心电图异常情况。本文介绍了一种算法在现场可编程门阵列(FPGA)中的实现,该算法基于连续小波变换(CWT)并采用样条函数,用于对三导联动态心电图监测仪原型进行逐搏心率和RT间期测量。该原型的主要元件包括一个模数转换器ADS1294、一个低功耗的Artix-7系列Xilinx XC7A35T-ICPG236C FPGA,该FPGA集成在一个小规模的Cmod-A7开发板中、一个液晶显示器和一个16GB的微型SD存储卡。一个主状态机初始化并管理从ADS1294同时采集三个导联的数据,并使用有限脉冲响应(FIR)滤波器对信号进行滤波。基于带样条函数的CWT算法检测QRS复合波(R波或S波),然后使用搜索窗口检测T波终点。最后,计算心率(60/RR间期)和RT间期(从R波峰到T波终点)以分析其动态变化。微型SD存储卡存储三个导联以及RR和RT间期的数据,液晶屏幕显示逐搏心率值、RT间期和电极连接情况。在FPGA上实现的算法在实时检测不同形态的QRS复合波和T波以分析心率和RT间期动态变化方面取得了令人满意的结果。