Optimized Non-invasive Cuff-less Continuous Blood Pressure Measurement Technique Using Artificial Neural Network

Continuous blood pressure (BP) monitoring is highly of assistance for detection of the major public health issue which is cardiovascular problems. Nowadays the BP monitoring technique which are commonly used are mostly using an uncomfortable cuff that makes continuous monitoring impossible since it slows the blood flow. However, measuring continues blood pressures are necessarily and crucial in some cases such as diagnostic of hypertension, for CVD patients, Sleep apnea and etc. The purpose of this study is to develop an optimized non-invasive cuff-less and continuous BP measuring technique which is capable of estimating BP in each heartbeat using arterial pulse waveform. The mentioned approach is based on the optical sensor integrated into the VitalTracer smartwatch which utilizes artificial neural network and genetic algorithm to optimize the structure and performance of the networks to obtain better results. TO BE CONT’D

Faculty Supervisor:

Hilmi Dajani

Student:

Zahra Zangenehmadar

Partner:

VitalTracer Ltd.

Discipline:

Engineering - computer / electrical

Sector:

Medical devices

University:

Program: