Implementation of Wavelet-Transform-Based Algorithms in an FPGA for Heart Rate and RT Interval Automatic Measurements in Real Time: Application in a Long-Term Ambulatory Electrocardiogram Monitor

Robust algorithm for the detection and classification of QRS complexes with different morphologies using the continuous spline wavelet transform with automatic scale detection

This work presents an algorithm for the detection and classification of QRS complexes based on the continuous wavelet transform (CWT) with splines. This approach can evaluate the CWT at any integer scale and the analysis is not restricted to powers of two. The QRS detector comprises four stages: implementation of CWT with splines, detection of QRS complexes, searching for undetected QRS complexes, and correction of the R wave peak location in detected QRS complexes. After, the onsets and ends of the QRS complexes are detected. The algorithm was evaluated with synthetic ECG and with the manually annotated databases: MIT-BIH Arrhythmia, European ST-T, QT and PTB Diagnostic ECG. Evaluation results of the QRS detector were: MIT-BIH arrhythmia database (109,447 beats analyzed), sensitivity Se = 99.72% and positive predictivity P+ = 99.87%; European ST-T database (790522 beats analyzed), Se = 99.92% and P+ = 99.55% and QT database (86498 beats analyzed), Se = 99.97% and P+ = 99.99%. To evaluate the delineation algorithm of the QRS onset (Qi) and QRS end (J) with the QT and PTB Diagnostic ECG databases, the mean and standard deviations of the differences between the automatic and manual annotated location of these points were calculated. The standard deviations were close to the accepted tolerances for deviations determined by the CSE experts. The proposed algorithm is robust to noise, artifacts and baseline drifts, classifies QRS complexes, automatically selects the CWT scale according to the sampling frequency of the ECG record used, and adapts to changes in the heart rate, amplitude and morphology of QRS complexes.

Low-Power Long-Term Ambulatory Electrocardiography Monitor of Three Leads with Beat-to-Beat Heart Rate Measurement in Real Time

A low-power long-term ambulatory ECG monitor was developed for the acquisition, storage and processing of three simultaneous leads DI, aVF and V2 with a beat-to-beat heart rate measurement in real time. It provides long-term continuous ECG recordings until 84 h. The monitor uses a QRS complex detection algorithm based on the continuous wavelet transform with splines, which automatically selects the scale for the analysis of ECG records with different sampling frequencies. It includes a lead-off detection to continuously monitor the electrode connections and a real-time system of visual and acoustic alarms to alert users of abnormal conditions in its operation. The monitor presented is based in an ADS1294 analogue front end with four channels, 24-bit analog-to-digital converters and programmable gain amplifiers, a low-power dual-core ESP32 microcontroller, a microSD memory for data storage in a range of 4 GB to 32 GB and a 1.4 in thin-film transistor liquid crystal display (LCD) variant with a resolution of 128 × 128 pixels. It has programmable sampling rates of 250, 500 and 1000 Hz; a bandwidth of 0 Hz to 50% of the selected sampling rate; a CMRR of -105 dB; an input margin of ±2.4 V; a resolution of 286 nV; and a current consumption of 50 mA for an average battery life of 84 h. The ambulatory ECG monitor was evaluated with the commercial data-acquisition system BIOPAC MP36 and its module for ECG LABEL SS2LB, simultaneously comparing the morphologies of two ECG records and obtaining a correlation of 91.78%. For the QRS detection in real time, the implemented algorithm had an error less than 5%. The developed ambulatory ECG monitor can be used for the analysis of the dynamics of the heart rate variability in long-term ECG records and for the development of one's own databases of ECG recordings of normal subjects and patients with cardiovascular and noncardiovascular diseases.