Effective Analysis and Accurate Detection of Common Diseases in ECG Signals and Classifications and Monitoring Through Cloud Computing Technology

Abstract

In the modern age of technology and advancements, the world is shrinking and accessible to everyone, in all ways including the medical field at the outset to save the lives. As the various experts are spread over the globe with their expertise, even the human dis-orders are also growing equally with the same speed. Hence it requires an assimilation of various sensors, embedded systems and some regularized protocol for hassle free interaction over the finger tips. In the proposed work we are attempting to interface few biosensors to capture ECG signals and to perform parametric estimation on breath-rate, heart beat rate, systolic pulse and other required parameters to classify the signal into any disease oriented or normal human being and uploaded the results along with type of disease. From the cloud, the concern medical experts can access and can treat the patient for further diagnosis. In this paper we are considering Epilepsy, heart beat rate, systolic pulse compared with normal condition of the human being. To classify the recorded ECG signals to discriminate among above condition we make use of Artificial Neural Network model and the entire processing of bio-medical signals are done on Matlab Platform. The processing of database is selected from the standard universally available database MIMIC II. The Matlab processed signals are again processed over a common protocol to communicate to the expert for exact diagnosis of the patient conditions over the captured bio-signals, the entire system we make use of modified LED algorithm and we term it as Health-Raid algorithm.