A Novel Approach in Determining the vitals in the ECG, SCG and Respiratory Signals

ECG (Echocardiogram) has three major components which need to be determined accurately for the diagnosis of any cardiac disease. These are: the P wave, which represents the depolarization of the atria; the QRS complex, which represents the depolarization of the ventricles; and the T wave, which represents the repolarization of the ventricles [15]. Determination of these peaks in an ECG waveform is a major challenge as it is not very intuitive. Hence it requires the involvement of an expert. In this work we have come up with an algorithm that automatically detects these essential peaks from just the raw data set. Coming to the SCG (Seismocardiogram), its main aim is to analyze the beats in a signal. Each beat is a cluster of rapidly changing signal. We need to identify these clusters in order to calculate the beat rate. In our work, we have identified the clusters by identifying the highest points or the local maxima of each cluster. Work has been carried out in this field and various algorithms have been developed. However the major drawback that these algorithms pose is the lack of universality. This implies that the algorithms need to be made adaptive manually for every single data set. On the other hand, the algorithm proposed in this work is independent of the data set and is hence applicable to any raw data.