An investigative study on motifs extracted features on real time big-data signals

In last decade, temporal medical data analysis is considered as core data samples in technological processing and research. However, a practical scenario of processing is unachieved. In this paper, the authors have projected a diagnosis of real time heart signals under motifs features over the Electro Cardio Graphic (ECG) and Phono Cardio Graphic (PCG) datasets. A combination of local motif patters for ECG datasets and Featured signal patters under PCG dataset with feed machine learning techniques is appended. A case study is performed on real time digital datasets of Electrocardiogram and Phonocardiogram. The selective outcome of study is constructive in comparison with raw temporal data processing techniques.