The non-communicable Cardiovascular Diseases (CVD) is one of the leading causes of death globally each year. Electrocardiogram (ECG) is the easiest and fastest test to monitor heart function. Interpretation of morphology of ECG waves and time intervals on ECG curves are important to diagnose heart abnormalities. Determining the deviation of each segment like PR, QRS, ST etc. on the ECG curve from their normal range is very important to interpret heart abnormalities or cardiac arrhythmia and this information helps in diagnose heart disease. This paper presents an architecture level FPGA design of a Sigma-Delta Modulator (SDM) for accurate detection of QRS complex from ECG curve. The proposed SDM is implemented using Xilinx Systen Generator (XSG) models and validated through simulation in MATLAB simulink. The method is tested on 24 ECG recordings of MIT-BIH arrhythmia database. The performance of the method is measured by the matrices sensitivity, positive prediction rate, and percentage error and the average values are 99.4213 %, 97.9365 % and 2.9561 % respectively.
No takes yet. Share an insight, caveat, or question.
Barman et al. (2024) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: