Abstract
The mean arterial pressure (MAP) is a very important cardiovascular parameter for physicians to diagnose various cardiovascular diseases. Many algorithms were used to estimate MAP with different accuracy. These algorithms used different factors, such as blood level, pulses, and external applied pressure, photo-plethysmography (PPG) signal features, heart rate (HR), and other factors. In addition, some natural-based techniques were employed to minimize the difference between estimated and measured blood pressure, as well as to measure blood pressure continuously. This article presents an algorithm to estimate MAP, utilizing the HR, Stroke Volume (SV), and Total Peripheral Resistance (TPR), with considering SV changing influence; this consideration is investigated mathematically, and by the Particle Swarm Optimization (PSO) technique.
Key Terms in this Chapter
Auscultatory Method: The most common method to measure BP by using sphygmomanometer.
Particle Swarm Optimization: A natural-based technique which relays on a certain insight concerning on persons actions and cognitions.
Mean Arterial Pressure: The mean of the force of blood flow against the artery walls.
Heart Rate: The rate of heart beating during a minute.
Arterial Cannulation Method: The oldest method used to measure BP, by inserting a catheter on subject’s artery.
Total Peripheral Resistance: The summation of all body vessels’ resistance against blood.
Photo-Plethysmography: The new method to measure the blood flow within the artery by PPG sensor.
Stroke Volume: The volume of the blood pumped by heart.