An asynchronous analog-to-information conversion system for wearable ECG sensors delivered an average R-peak detection accuracy of 98.3%, sensitivity of 98.89%, and positive prediction of 99.4%.
The proposed level-crossing based QRS-detection algorithm offers high accuracy and low power consumption, making it suitable for wearable wireless ECG sensors.
In this paper, an asynchronous analog-to-information conversion system is introduced for measuring the RR intervals of the electrocardiogram (ECG) signals. The system contains a modified level-crossing analog-to-digital converter and a novel algorithm for detecting the R-peaks from the level-crossing sampled data in a compressed volume of data. Simulated with MIT-BIH Arrhythmia Database, the proposed system delivers an average detection accuracy of 98.3%, a sensitivity of 98.89%, and a positive prediction of 99.4%. Synthesized in 0.13 μm CMOS technology with a 1.2 V supply voltage, the overall system consumes 622 nW with core area of 0.136 mm (2), which make it suitable for wearable wireless ECG sensors in body-sensor networks.
Ravanshad et al. (Thu,) conducted a other in Arrhythmia. Asynchronous analog-to-information conversion system with modified level-crossing ADC and novel R-peak detection algorithm was evaluated on R-peak detection accuracy. An asynchronous analog-to-information conversion system for wearable ECG sensors delivered an average R-peak detection accuracy of 98.3%, sensitivity of 98.89%, and positive prediction of 99.4%.