References
Sufi F, Fang Q, Khalil I, et al. Novel methods of faster cardiovascular diagnosis in wireless telecardiology. IEEE J Sel Areas Commun, 2009, 27: 537–552
Pallavi M, Chandrashekar H M. Study and analysis of ECG compression algorithms. In: Proceedings of International Conference on Communication and Signal Processing, 2016. 2028–2032
Kohler B U, Hennig C, Orglmeister R. The principles of software QRS detection. IEEE Eng Med Biol Mag, 2002, 21: 42–57
Luo K, Wang Z G, Li J Q, et al. Information-enhanced sparse binary matrix in compressed sensing for ECG. Electron Lett, 2014, 50: 1271–1273
Li P, Liu M, Zhang X, et al. A low-complexity ECG processing algorithm based on the Haar wavelet transform for portable health-care devices. Sci China Inf Sci, 2014, 57: 122303
Pang B, Liu M, Zhang X, et al. A novel approach framework based on statistics for reconstruction and heartrate estimation from PPG with heavy motion artifacts. Sci China Inf Sci, 2018, 61: 022312
Balouchestani M, Raahemifar K, Krishnan S. Highresolution QRS detection algorithm for wireless ECG systems based on compressed sensing theory. In: Proceedings of the 56th International Midwest Symposium on Circuits and Systems (MWSCAS), 2013. 1326–1329
Acknowledgements
This work was supported by National Key Technologies R&D Program (Grant No. 2017-YFB0405604), Key Research Program of Frontier Science, Chinese Academy of Sciences (Grant No. QYZDY-SSW-JSC004), Basic Research Project of Shanghai Science and Technology Commission (Grant No. 16JC1400101), and Beijing S&T Planning Task (Grant No. Z161100002616019).
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Wang, S., Pang, B., Liu, M. et al. A novel compression framework using energy-sensitive QRS complex detection method for a mobile ECG. Sci. China Inf. Sci. 62, 69409 (2019). https://doi.org/10.1007/s11432-018-9838-3
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DOI: https://doi.org/10.1007/s11432-018-9838-3