Adaptive Forward Error Correction for ECG Signal Transmission for Emotional Stress Assessment

In this work, we try to collect useful emotional stress information from electrocardiogram (ECG) signals via a real-time wearable Wireless Body Area Network (WBAN). Discrete Wavelet Transform (DWT) is applied on collected ECG signals for feature extraction, which carries important information for stress level identification. After the stress level is classified using K-Nearest Neighboring (KNN), adaptive convolutional coding is considered for ECG signal protection during transmission according to their various stress levels, which is able to provide an acceptable low Bit Error Rate (BER) and efficient energy consumption at the same time.