Simple and Robust Realtime QRS Detection Algorithm Based on Spatiotemporal Characteristic of the QRS Complex

• Published in: PloS one Vol. 11; no. 3; p. e0150144
• Main Authors: Kim, Jinkwon, Shin, Hangsik
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 04.03.2016; Public Library of Science (PLoS)
• Subjects: Accuracy; Algorithms; Arrhythmia; Biology; Biomedical engineering; Cardiac arrhythmia; Cardiovascular disease; Computer applications; Computer Systems; Data bases; Databases as Topic; Diagnosis; EKG; Electrocardiography; Electrocardiography - methods; Energy; Engineering; Engineering and Technology; FIR filters; Heart; Heart diseases; Humans; International conferences; Medicine; Medicine and Health Sciences; Methods; Noise; Noise levels; Physical Sciences; Physiological aspects; Real time; Research and Analysis Methods; Signal processing; Signal Processing, Computer-Assisted; Spatio-Temporal Analysis; Statistics as Topic; Transformation; Wavelet; Wavelet transforms; South Korea
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0150144

The purpose of this research is to develop an intuitive and robust realtime QRS detection algorithm based on the physiological characteristics of the electrocardiogram waveform. The proposed algorithm finds the QRS complex based on the dual criteria of the amplitude and duration of QRS complex. It consists of simple operations, such as a finite impulse response filter, differentiation or thresholding without complex and computational operations like a wavelet transformation. The QRS detection performance is evaluated by using both an MIT-BIH arrhythmia database and an AHA ECG database (a total of 435,700 beats). The sensitivity (SE) and positive predictivity value (PPV) were 99.85% and 99.86%, respectively. According to the database, the SE and PPV were 99.90% and 99.91% in the MIT-BIH database and 99.84% and 99.84% in the AHA database, respectively. The result of the noisy environment test using record 119 from the MIT-BIH database indicated that the proposed method was scarcely affected by noise above 5 dB SNR (SE = 100%, PPV > 98%) without the need for an additional de-noising or back searching process.