  The prime purpose of this project is to develop a portable cardiac
abnormality monitoring device which can drastically improvise the quality of
the monitoring and the overall safety of the device. While a generic, low cost,
wearable battery powered device for such applications may not yield sufficient
performance, such devices combined with the capabilities of Artificial Neural
Network algorithms can however, prove to be as competent as high end flexible
and wearable monitoring devices fabricated using advanced manufacturing
technologies. This paper evaluates the feasibility of the Levenberg-Marquardt
ANN algorithm for use in any generic low power wearable devices implemented
either as a pure real-time embedded system or as an IoT device capable of
uploading the monitored readings to the cloud.
