Abstract
Every day risk of cardiovascular diseases is increasing in young adults. Now researchers are working on study related to a single bio-signal for prediction of maximum physiological parameters. One of such a bio-signal is photoplethysmogram (PPG). Non-invasive measurement of blood volume change is carried out by using PPG. PPG captured from a cranial site is known as cranial photoplethysmogram (CPPG). Most of the time various bio-signals acquired from the brain are used to study only the brain-related disorders. Near-infrared spectroscopy-based sensor used to record CPPG from frontal region can be used to predict heart rate, oxygen saturation, blood pressure, cardiac output and respiration rate. This paper explains the design specifications of sensor used and study of various time and amplitude indices of differentiated CPPG signal. Authors have studied two levels of differentiation of CPPG obtained by applying MATLAB-based algorithm. Features obtained from differentiated CPPG signal are compared with the standard available values to check the feasibility of this brain signal in the prediction of vascular health. The study was carried out on 19 healthy subjects aged between 19 and 30 years. Our results showed that the optical brain signal used to study hemodynamic changes in brain can also be used for the prediction of vascular health.
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Shriram, R., Martin, B., Sundhararajan, M., Daimiwal, N. (2018). Statistical Analysis of Derivatives of Cranial Photoplethysmogram in Young Adults. In: Bhateja, V., Tavares, J., Rani, B., Prasad, V., Raju, K. (eds) Proceedings of the Second International Conference on Computational Intelligence and Informatics . Advances in Intelligent Systems and Computing, vol 712. Springer, Singapore. https://doi.org/10.1007/978-981-10-8228-3_38
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