An Adaptive and Time-Efficient ECG R-Peak Detection Algorithm

作者：Qin, Qin; Li, Jianqing^*; Yue, Yinggao; Liu, Chengyu

来源：Journal of Healthcare Engineering, 2017, 2017: 5980541.

DOI：10.1155/2017/5980541

• FEATURE-EXTRACTION
• NOISE REMOVAL
• SIGNAL
• COMPONENTS
• ELECTRODE
• IMPACT

R-peak detection is crucial in electrocardiogram (ECG) signal analysis. This study proposed an adaptive and time-efficient R-peak detection algorithm for ECG processing. First, wavelet multiresolution analysis was applied to enhance the ECG signal representation. Then, ECG was mirrored to convert large negative R-peaks to positive ones. After that, local maximums were calculated by the first-order forward differential approach and were truncated by the amplitude and time interval thresholds to locate the R-peaks. The algorithm performances, including detection accuracy and time consumption, were tested on the MITBIH arrhythmia database and the QT database. Experimental results showed that the proposed algorithm achieved mean sensitivity of 99.39%, positive predictivity of 99.49%, and accuracy of 98.89% on the MIT-BIH arrhythmia database and 99.83%, 99.90%, and 99.73%, respectively, on the QT database. By processing one ECG record, the mean time consumptions were 0.872 s and 0.763 s for the MIT-BIH arrhythmia database and QT database, respectively, yielding 30.6% and 32.9% of time reduction compared to the traditional Pan-Tompkins method.

• 出版日期2017
• 单位东南大学