Input Feature Correlated Analog to Information Converter

TITLE: Input Feature Correlated Asynchronous Sampling Analog to Information Converter

Advisor: Sameer Sonkusale

Researcher: Robbie D'Angelo, Ritika Agarwal (Completed), Mike Trakimas (Completed)


In most biomedical and energy constrained sensing applications, it is futile to digitize the entire signal waveform and transmit the entire data wirelessly, due to the limited power available for sensing and transmission. A more clever approach is to sample the data only when needed. This has led us to utilize asynchronous sampling approach with adaptive thresholds for sampling the data in a very power efficient manner.  In most applications, the digital data is compressed and processed to extract important features from the signal. If this could be performed directly at the source, it could further save power and processing requirements

We have shown input feature correlated sampling asynchronous A/D converter for direct extraction of QRS complex from ECG waveforms as proof of concept.


See the publication page.