A robust technique for delineation and features extraction of ECG signal from mobile-phone photography

This paper reports the development of a software suite to be accessed in future with any General Packet Radio Service (GPRS) or High Speed Packet Access (HSPA) enabled mobile phone or Personal Digital Assistant (PDA) for the extraction and analysis of disease-related features from the photograph of paper based ECG records. In India and other developing countries, the cheaper paper based ECG machines are prevalently used. In rural areas of these countries cardiac diseases are still the major silent killers due to the acute dearth of qualified cardiologists. One way of addressing this problem is Tele-medicine which necessitates an intelligent cardiac parameter extraction algorithm. In our bid to address this requirement, an algorithm is developed with the help of few image processing techniques. Initially, the background noises i.e. the gridlines are removed by thresholding technique. Applying the Sauvola method for adaptive image binarization and subsequent morphological operations to get pure ECG signature on white background, this algorithm intelligently applies Bresenham's line drawing algorithm to join the disjoined ECG signature where required. Then thinning has been done for extraction of digital time-plane data and then Discrete Wavelet Transform (DWT) and water reservoir based pattern recognition technique are subsequently used to delineate other important time-plane features for ECG interpretation.