Early prediction of non-cardiac disorders from ECG using lab view

Abstract

The Electrocardiogram (ECG) is one of the most basic cardiological test done for any suspected diseases related to cardiological system. Abnormalities in any other system can also be detected with change in morphology of ECG. In this paper we note the changes in morphology of ECG for prediction of non-cardiac diseases like Emphysema, CNS haemorrhage, Thyroidism, Hypokalemia and Hyperkalemia. ECG is used to predict these diseases as it is a non-invasive technique and also the morphology of ECG wave is repetitive until any abnormality manifests itself through ECG. If any of the above mentioned non-cardiac diseases occur, significant changes appear in ECG signal and with the knowledge of these changes, early clues are provided regarding the diseases which are lifesaving. This paper works on acquisition and segmentation of ECG for extraction of features that are inevitable for the prediction of above mentioned diseases. The extracted features are classified as normal or abnormal based on the comparison with the reference signal. The reference signal contains information about the normal and abnormal morphological conditions of ECG which are segmented, extracted and stored prior in the LabVIEW. The automatic prediction of non-cardiac diseases is carried out with LabVIEW through which a tolerance method is used to correctly compare and predict that particular kind of disease. This will be later extended to real-time acquisition, processing and classification. The basic motive behind this project is to create an awareness and alert the patient before the fatal stage.