Estimation of Arterial Blood Pressure Based on Artificial Intelligence Using Single Earlobe Photoplethysmography during Cardiopulmonary Resuscitation
Author:
Publisher
Springer Science and Business Media LLC
Subject
Health Information Management,Health Informatics,Information Systems,Medicine (miscellaneous)
Link
http://link.springer.com/content/pdf/10.1007/s10916-019-1514-z.pdf
Reference8 articles.
1. Sakabe, T., Tateishi, A., Miyauchi, Y., Maekawa, T., Matsumoto, M., Tsutsui, T., and Takeshita, H., Intracranial pressure following cardiopulmonary resuscitation. Intensive Care Med 13(4):256–259, 1987. https://doi.org/10.1007/BF00265114.
2. Cheng, A., Brown, L. L., Duff, J. P. et al., Improving cardiopulmonary resuscitation with a CPR feedback device and refresher simulations (CPR CARES study): A randomized clinical trial. JAMA Pediatr 169(2):137–144, 2015. https://doi.org/10.1001/jamapediatrics.2014.2616.
3. Wei, L., Chen, G., Yang, Z. et al., Detection of spontaneous pulse using the acceleration signals acquired from CPR feedback sensor in a porcine model of cardiac arrest. PLoS ONE 12(12):e0189217, 2017. https://doi.org/10.1371/journal.pone.0189217.
4. Callaway, C. W., Soar, J., Aibiki, M. et al., Part 4: Advanced life support: 2015 international consensus on cardiopulmonary resuscitation and emergency cardiovascular care science with treatment recommendations. Circulation 132(16_suppl_1):S84–S145, 2015. https://doi.org/10.1016/j.resuscitation.2015.07.042.
5. Berve, P. O., Irusta, U., Kramer-Johansen, J. et al., Transthoracic impedance measured with defibrillator pads—New interpretations of signal change induced by ventilations. J Clin Med 8(5):724, 2019. https://doi.org/10.3390/jcm8050724.
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