ECG Signal Processing and Human State Detection Based on Wearable Electrodes

Detection and Recognition of a human's continuous states in real time plays an important role wearable devices. We present approach for heart rhythm recognition human status detection through the analysis ECG signal. The algorithm is comprised four components, including noise removal, QRS-P-T wave detection, features extraction classification. Discrete wavelet transform (DWT) applied random background removal. "Moving Integral – Changing Slope" method used to determine location QRS complex waves other characteristic Time interval, location, amplitude, area coefficients as each segment are input into support vector machine (SVM) so that can judge body. Finally, we develop single-lead delineation system collect data from 30 users different ages body experimental verification. Our evaluation shows this accurately detect time. In future, it be implemented on devices assist real-time physiological monitoring or customized health planning.