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Systolic Blood Pressure estimation from PPG signal using ANN

Benedetta Caterina Casadei

Systolic Blood Pressure estimation from PPG signal using ANN.

Rel. Gabriella Olmo. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2021

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Abstract:

High Blood Pressure is one of the precursors for Cardiovascular Diseases, the most common cause of death in 2015, as reported by the World Health Organization (WHO). Continuous and non-invasive blood pressure remote monitoring would be a great revolution, especially for hypertensive patients. Our work aims to propose a system in which Photoplethysmogram is used to continuously estimate Systolic Blood Pressure (SBP), (a more potent predictor for coronary heart disease, heart failure and mortality, at age 50), using Artificial Neural Network.

Relators: Gabriella Olmo
Academic year: 2020/21
Publication type: Electronic
Number of Pages: 123
Subjects:
Corso di laurea: Corso di laurea magistrale in Ingegneria Biomedica
Classe di laurea: New organization > Master science > LM-21 - BIOMEDICAL ENGINEERING
Aziende collaboratrici: STMICROELECTRONICS srl
URI: http://webthesis.biblio.polito.it/id/eprint/17609
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