Key result
Extended Kalman filter improves noncontact ECG signal-to-noise ratio by ~9 dB.
Absolute Event Rate: 47.79% vs 39.1%
Applying an extended Kalman filter to noncontact capacitive-coupled ECG sensors yields highly stable, noise-free signals suitable for real-time mobile heart rate monitoring.
May support technical refinement of noncontact ECG; leaves open clinical validation before mobile monitoring use.
Noncontact electrocardiogram (ECG) measurement using capacitive-coupled technique is a very reliable long-term noninvasive health-care remote monitoring system. It can be used continuously without interrupting the daily activities of the user and is one of the most promising developments in health-care technology. However, ECG signal is a very small electric signal. A robust system is needed to separate the clean ECG signal from noise in the measurement environment. Noise may come from many sources around the system, for example, bad contact between the sensor and body, common-mode electrical noise, movement artifacts, and triboelectric effect. Thus, in this paper, the extended Kalman filter (EKF) is applied to denoise a real-time ECG signal in capacitive-coupled sensors. The ECG signal becomes highly stable and noise-free by combining the common analog signal processing and the digital EKF in the processing step. Furthermore, to achieve ubiquitous monitoring, android-based application is developed to process the heart rate in a realtime ECG measurement.
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Rachim et al. (2014) studied Healthy (n=1). Extended Kalman Filter (EKF) vs. Unfiltered noisy ECG signal was evaluated on Signal-to-Noise Ratio (SNR). The application of the extended Kalman filter to a noncontact ECG measurement system successfully suppressed noise, increasing the signal-to-noise ratio from 39.1 dB to 47.79 dB and reducing the mean squared error.
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