Remote detection of photoplethysmographic signal and SVM based classification

Remote photoplethysmography is most recent method for measuring the heart rate according to skin color variations. The heart is essential part of human body and all the heart related issues causes because of anxiety. Firstly we have to consider ROI for experiment and hence Viola Jones algorithm is used for the face detection. We have presented a new automated method for detection of the systolic and diastolic peaks of a PPG waveform captured remotely using a digital camera. The top to-crest time amongst systolic and diastolic point is in a roundabout way identified with the heart rate. After extraction of BVP pulse, we are extending our work toward classification of these pulses in to six different types as Normal Sinus Rhythm (NSR), Premature Ventricular Contraction (PVC), Atrial Premature Contraction (APC), Ventricular Tachycardia (VT), Ventricular Fibrillation (VF) and Supraventricular Tachycardia (SVT). For classification we will use Support Vector Machine Classifier (SVM).