Input-Feature Correlated Asynchronous Analog to Information Converter for ECG Monitoring.

This paper illustrates an architectural design of a novel variable input-feature correlated asynchronous sampling and time-encoded digitization approach for source compression and direct feature extraction from physiological signals. The complete architecture represents an analog-to-information (A2I) converter, designed for ultra-low-power mixed-signal very-large-scale integrated implementation. The device will be suitable for long-term wearable monitoring of physiological signals, such as electrocardiogram (ECG). We show representative case studies on QRS detection in an ECG signal utilizing the proposed A2I converter to prove the functionality of the design. Simulation results show large source compression in the ECG signal and more than 98% efficiency in the detection of the Q, R, and S waves for challenging ECG waveforms, all with extremely low-power and storage requirements.