References
- Elgendi, M., Eskofier, B., Dokos, S., and Abbott, D., 2014, Revisiting QRS detection methodologies for portable, wearable, battery-operated, and wireless ECG systems. PLoS ONE, 9, e84018
- Friesen, G.M., Jannett, T.C., Jadallah, M.A., Yates, S.L., Quint, S.R., and Nagle, H.T., 1990, A comparison of the noise sensitivity of nine QRS detection algorithms. IEEE Transactions on Biomedical Engineering, 37, 85–98
- Pan, J., and Tompkins, W.J., 1985, A real-time QRS detection algorithm. IEEE Transactions on Biomedical Engineering, 32, 230–236
- Christov, I.I., 2004, Real time electrocardiogram QRS detection using combined adaptive threshold. Biomedical Engineering Online, 3, 1–9
- Moody, G.B., Muldrow, W.E., and Mark, R.G., 1984, A noise stress test for arrhythmia detectors. Computers in Cardiology, 11, 381–384
- Suárez, K.V. 1st, Silva, J.C., Berthoumieu, Y., Gomis, P., and Najim, M., 2007, ECG beat detection using a geometrical matching approach. IEEE Transactions on Biomedical Engineering, 54, 641–650
- Börjesson, P.O., Pahlm, O., Sörnmo, L., and Nygårds, M.E., 1982, Adaptive QRS detection based on maximum a posteriori estimation. IEEE Transactions on Biomedical Engineering, 29, 341–351
- Gribok, A.V., Chen, X., and Reifman, J., 2011, A robust method to estimate instantaneous heart rate from noisy electrocardiogram waveforms. Annals of Biomedical Engineering, 39, 824–834
- Kumar, M., Weippert, M., Stoll, N., and Stoll, R., 2010, A mixture of fuzzy filters applied to the analysis of heartbeat intervals. Fuzzy Optimization and Decision Making, 9, 383–412
- Hayn, D., Jammerbund, B., and Schreier, G., 2012, QRS detection based ECG quality assessment. Physiological Measurement, 33, 1449–1461
- Jekova, I., Krasteva, V., Christov, I., and Abächerli, R., 2012, Threshold-based system for noise detection in multilead ECG recordings. Physiol Meas, 33, 1463–1477
- Li, Q., Mark, R.G., and Clifford, G.D., 2008, Robust heart rate estimation from multiple asynchronous noisy sources using signal quality indices and a Kalman filter. Physiological Measurement, 29, 15–32
- Goldberger, A.L., Amaral, L.A.N., Glass, L., Hausdorff, J.M., Ivanov, P.C.H., Mark, R.G., Mietus, J.E., Moody, G.B., Peng, C.K., and Stanley, H.E., 2000, PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation, 101, e215–e220
- Vanoli, E., Adamson, P.B., Ba-Lin, M.P.H., Pinna, G.D., Lazzara, R., and Orr, W.C., 1995, Heart rate variability during specific sleep stages. A comparison of healthy subjects with patients after myocardial infarction. Circulation, 91, 1918–1922
- Hatfield, B.D., 1st Spalding, T.W., Santa Maria, D.L., Porges, S.W., Potts, J.T., Byrne, E.A., Brody, E.B., and Mahon, A.D., 1998, Respiratory sinus arrhythmia during exercise in aerobically trained and untrained men. Medicine & Science in Sports & Exercise, 30, 206–214
- Ankerst, M., Breunig, M.M., Kriegel, H.P., and Sander, J., 1999, OPTICS: Ordering Points To Identify the Clustering Structure. ACM SIGMOD International conference on Management of data. 1999. Philadelphia, PA, pp. 49–60
- Liu, N.T., Batchinsky, A.I., Cancio, L.C., and Salinas, J., 2013, The impact of noise on the reliability of heart-rate variability and complexity analysis in trauma patients. Computers in Biology & Medicine, 43, 1955–1964
- Knoepfli-Lenzin, C., Haenggli, B., and Boutellier, U., 2014, Optimised heart rate formulae to monitor endurance training in sedentary individuals. Journal of Sports Sciences, 32, 557–562