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

Hansong Xu, Kun Hua, Guang-Chong Zhu, Jun Huang
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引用次数: 3

Abstract

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.
用于情绪应激评估的心电信号传输自适应前向纠错
在这项工作中,我们尝试通过实时可穿戴无线身体区域网络(WBAN)从心电图(ECG)信号中收集有用的情绪压力信息。对采集到的心电信号进行离散小波变换(DWT)进行特征提取,该特征为应力水平识别提供了重要信息。采用k近邻法对心电信号的应力水平进行分类后,根据不同的应力水平,采用自适应卷积编码对心电信号进行传输保护,在保证较低误码率的同时,实现了有效的能量消耗。
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