Abstract
The development of a reliable and robust algorithm for prediction of syncope events is still a major challenge, especially when it is based on the analysis of the photoplethysmogram (PPG) alone. Several algorithms have been proposed in the literature based on the joint analysis of the electrocardiogram, the blood pressure and also the PPG [1]. However, when considering the analysis of the PPG alone, the ability to predict syncope events is still unsatisfactory. The aim of this work is to provide a more reliable PPG-based algorithm with higher prediction ability, using a dataset with 43 patients.
Parameters related to the chronotropic, inotropic, blood pressure, vascular tone and autonomous nervous system responses have been extracted and evaluated. Several features were computed and the most relevant were selected and ranked with a proper score system. Additionally, different algorithm setups were also tested. The best setup achieved the following results: Fm=86%, SE=100%, SP=85%, FPRh=1.9h-1 and PT= 242.3±226.9 sec.
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Pinheiro, N., Couceiro, R., Muehlsteff, J., Eickholt, C., Henriques, J., Carvalho, P. (2018). Syncope Prediction using Photoplethysmography. In: Eskola, H., Väisänen, O., Viik, J., Hyttinen, J. (eds) EMBEC & NBC 2017. EMBEC NBC 2017 2017. IFMBE Proceedings, vol 65. Springer, Singapore. https://doi.org/10.1007/978-981-10-5122-7_157
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DOI: https://doi.org/10.1007/978-981-10-5122-7_157
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