We implemented a moving average based filtering system based on Chen-Chen detector [1] , which can detect QRS complexes in real-time. We then propose improvements to this baseline algorithm. Here we implemented a more robust preprocessing of the original signal as proposed in Pan-Tompkins detector [2] . To reduce the amount of false positive detections, we introduce some additional restrictions in the decision making. All versions of detectors were tested on both LTST [3] and MIT/BIH [4] databases and the porposed improvements have show to have beneficial effect on the results.
| Name | Se (LTST) | +P (LTSLT) | Se (MIT/BIH) | +P (MIT/BIH) |
|---|---|---|---|---|
| Original | 96.14 | 88.48 | 96.84 | 83.92 |
| Preprocess | 97.20 | 82.53 | 99.68 | 77.44 |
| Min200 | 96.15 | 99.34 | 97.25 | 98.97 |
| PrepMin200 | 97.12 | 98.85 | 99.59 | 99.58 |
| PrepMin200TWave | 96.89 | 98.91 | 99.39 | 99.62 |
- Have a folder named "ltstDB" or "mitbihDB" where all files from the database are stored
- For every signal file in the database generate .mat file
- Change Fs (sampling frequency) in "Detector.m" (250 for ltstDB, 360 for mitbihDB)
- Comment/Uncomment parts of QRSDetect.m to run different version of the detector
- In Matlab run "runDetector.m" with a parameter which specifiec a database you would like to use ("ltstDB" or "mitbihDB")
- Put run_detector.sh inside folder where your results are
- Run run_detector.sh with with optional parameter whicih specific name of resulting .txt file
[1] H. Chen and S. Chen, “A moving average based filtering system with its application to real-time QRS detection,” in Computers in Cardiology, 2003, IEEE, 2003. [2] J. Pan and W. J. Tompkins, “A real-time QRS detection algorithm,” IEEE Transactions on Biomedical Engineering, vol. BME-32, pp. 230–236, Mar. 1985.[3] F. Jager, A. Taddei, G. B. Moody, M. Emdin, G. Antolič, R. Dorn, A. Smrdel, C. Marchesi, and R. G. Mark, “Long-term ST database: A reference for the development and evaluation of automated ischaemia detectors and for the study of the dynamics of myocardial ischaemia,” Medical & Biological Engineering & Computing, vol. 41, pp. 172–182, Mar. 2003. [4] G. Moody and R. Mark, “The impact of the MIT-BIH arrhythmia database,” IEEE Engineering in Medicine and Biology Magazine, vol. 20, no. 3, pp. 45–50, 2001. [5] A. L. Goldberger, L. A. N. Amaral, L. Glass, J. M. Hausdorff, P. C. Ivanov, R. G. Mark, J. E. Mietus, G. B. Moody, C.-K. Peng, and H. E. Stanley, “PhysioBank, PhysioToolkit, and PhysioNet,” Circulation, vol. 101, June 2000.