Combining electrocardiogram signal with Accelerometer signals for Human Activity Recognition using Convolution neural network

As the environment getting polluted, people are suffering with different medical problems also causes about their health as well. Considering this in mind, Body sensor based human activity recognition attracting researcher towards direction. A fusion of electrocardiogram signals and accelerometer processed through convolution neural network is proposed paper. Accelerometer placed at location body fused signals, generated ECG sensors chest body. These signal to automatically detect features finally apply softmax for classification activities. We choose mHEALTH dataset experiment achieve 98.91% validation accuracy.