Adaptive R-wave detection method in dynamic ECG with heavy EMG artifact

Recently, the electrocardiogram (ECG) was applied in long-term and dynamic monitoring in daily life, and the R-wave detection is the key in all kinds of ECG monitorings. Electromyographic (EMG) interference is the most common noise in dynamic ECG, and it has great influence on detection of R-wave. Therefore, we propose an adaptive R-wave detection method, which is based on the analysis of EMG interference. In this paper, we first demonstrate different changes of ECG morphology due to different types of EMGs. Then we classify EMG interference by their frequency power ratios, zero-crossing rate and short time energy. The choice of R-wave detection methods (wavelet transform and Empirical Mode Decomposition method) are related to the result of classification. The proposed adaptive R-wave detection method is validated using the data collected in our laboratory, and the experimental results demonstrate that the proposed method is significantly applicable in case of dynamic ECG.