The ASIC for ECG signal processing achieved 99.86% sensitivity and 99.93% specificity for QRS complex detection, with a detection failure rate of only 0.16%.
Does a novel ASIC-based forward search algorithm accurately and efficiently detect QRS complexes in ECG signals?
A novel, highly energy-efficient ASIC for real-time ECG QRS complex detection demonstrates excellent sensitivity and specificity, showing potential for ambulatory cardiovascular disease monitoring.
A novel algorithm based on forward search is developed for real‐time electrocardiogram (ECG) signal processing and implemented in application specific integrated circuit (ASIC) for QRS complex related cardiovascular disease diagnosis. The authors have evaluated their algorithm using MIT‐BIH database and achieve sensitivity of 99.86% and specificity of 99.93% for QRS complex peak detection. In this Letter, Physionet PTB diagnostic ECG database is used for QRS complex related disease detection. An ASIC for cardiovascular disease detection is fabricated using 130‐nm CMOS high‐speed process technology. The area of the ASIC is 0.5 mm 2 . The power dissipation is 1.73 μW at the operating frequency of 1 kHz with a supply voltage of 0.6 V. The output from the ASIC is fed to their Android application that generates diagnostic report and can be sent to a cardiologist through email. Their ASIC result shows average failed detection rate of 0.16% for six leads data of 290 patients in PTB diagnostic ECG database. They also have implemented a low‐leakage version of their ASIC. The ASIC dissipates only 45 pJ with a supply voltage of 0.9 V. Their proposed ASIC is most suitable for energy efficient telemetry cardiovascular disease detection system.
Jain et al. (2016) studied this question. The ASIC for ECG signal processing achieved 99.86% sensitivity and 99.93% specificity for QRS complex detection, with a detection failure rate of only 0.16%.