University of California

Tao-Yi Lee

Nikil Dutt

The present invention is directed to an energy-efficient method of monitoring a physiological signal while maintaining high accuracy. The method may comprise a Deep Neural Network (DNN) receiving an uncompressed sample of a continuous ECG signal from a sensor. The method may further comprise the DNN determining a first probability that the received sample is abnormal and a second probability that the received sample is normal. Finally, the method may further comprise the DNN determining to transmit the uncompressed sample if a threshold of abnormality is less than or equal to the difference between the first probability and the second probability. In some embodiments, the DNN may be a Convolutional Neural Network (CNN).

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Irvine, CA, United States of America

Tao-Yi Lee