센서학회지 (Journal of Sensor Science and Technology)

  • 제23권1호
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  • Pages.7-14
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  • 2014
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  • 1225-5475(pISSN)
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  • 2093-7563(eISSN)
한국센서학회 (The Korean Sensors Society)
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Implementation of Extended Kalman Filter for Real-Time Noncontact ECG Signal Acquisition in Android-Based Mobile Monitoring System

  • 투고 : 2013.12.18
  • 심사 : 2014.01.09
  • 발행 : 2014.01.29
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초록

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.

키워드

참고문헌

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피인용 문헌

  1. Wearable Noncontact Armband for Mobile ECG Monitoring System vol.10, pp.6, 2016, https://doi.org/10.1109/TBCAS.2016.2519523
  2. A Robust Algorithm for Real-Time Peak Detection of Photoplethysmograms Using a Personal Computer Mouse vol.15, pp.8, 2015, https://doi.org/10.1109/JSEN.2015.2424979
  3. Reduction of Motion Artifacts and Improvement of R Peak Detecting Accuracy Using Adjacent Non-Intrusive ECG Sensors vol.16, pp.5, 2016, https://doi.org/10.3390/s16050715
  4. Denoising ECG Signals by Using Extended Kalman Filter to Train Multi-Layer Perceptron Neural Network vol.52, pp.6, 2018, https://doi.org/10.3103/S0146411618060044