Early Disease Detection by Extracting Features of Biomedical Signals

Abstract

Elderly people face a lot of health problems in day to day life due to old age and so many reasons. Therefore a regular health check-up is needed for them which is much more expensive and cannot be afforded by many people. Again the diagnosis is much more complicated to understand and in many cases there is a chance of mistreatment. There is another chance of delay in the detection of disease and late treatment causing risk in their lives. So, the disease should be detected in the early stage for lower cost and lower risk in life. The present work is related to the different physiological parameters of a human being that are to be measured to accurately diagnose the related disease. Though there are numerous physiological parameters, this work emphasizes on some of the most common physiological parameters such as blood pressure, heart rate and ECG which are of primary importance to elderly people. Accurate measurement and analysis of these parameters can lead to diagnose of several lethal disease. In this work, the method of measurement and analysis of these physiological parameters are described. The simulation, processing and analyses of these signals are also done in the work. The prime objective of the research work is to analyze and extract the features of ECG signal and blood pressure signal for early diagnosis of life threatening diseases.