DENOISING AND REMOTE MONITORING OF ECG SIGNAL WITH REAL-TIME EXTENDED KALMAN FILTER IN A WEARABLE SYSTEM

In this paper, a prototype of wearable and wireless electrocardiography (ECG) monitoring system is developed and implemented on DSP and PDA. We present a real-time extended Kalman filtering framework for extracting motion and electromyography (EMG) artifacts from a single-channel ECG in wearable systems as different from other or line studies. Realized prototype is a good example for the usage of the Kalman filter in biomedical real-time system. The average SNR advancement of 9.1430 dB was achieved for denoising, which is average 1 dB more than the other methods such as MABWT, EKF2 by using MIT-BIH database. Additionally, the usability and performances of conductive textile electrodes were evaluated with disposable Ag-AgCl electrodes by using daily activities. A novel textile electrode gave approximately 25.23% better results compared to Ag-AgCl electrodes. Also, UDP, TCP and Web Socket communication protocols have been tested. UDP has been the fastest method for the ECG signal transferring from the patient to the doctor. At the same time, a method is proposed for direct access to the patient by the doctor. The results illustrate that this type of system will submit highly ergonomic solutions among biomedical device technologies. In addition, the usage of such kinds of systems is foreseen for requiring long-term follow-up and disorders.