# Blood Pressure Estimation Algorithm Based on Photoplethysmography Pulse Analyses
###### Abstract  
Though small wrist-type blood pressure (BP) measurement devices using simple sensors have recently been developed, they lack accuracy and require the input of personal user data. To miniaturize BP measurement devices, this study proposes the use of algorithms that can calculate BP using sensors that utilize only two photoplethysmographies (PPGs), without the need for electrocardiograms. To reduce the error of indirect BP measurement, specific values representing individual blood vessel conditions are improved via the application of an algorithm developed using mean arterial pressure and PPG phase difference. To reduce the error that occurs when measuring BP using PPG, a specific value algorithm used to develop a miniaturized BP measuring device using two PPGs is proposed along with a new model. The developed ultra-small PPG measuring device uses a reflective photoplethysmography measurement circuit. This is presented as a PPG-only model that deviates from the method of additionally linking existing electrocardiography (ECG). The measurement device developed in this study is compared with the air-pressurized automatic BP measurement device in terms of the BP measurement value; the result of maintaining the error stably at 5% is derived to prove the superiority of the algorithm.  
blood pressure; photoplethysmography; systolic blood pressure; diastolic blood pressure; pulse interval; mean arterial pressure +
Footnote †: journal: Medical  
Accordingly, the final measurements vary depending on the area of the measurement and the physical conditions. Specifically, measurement methods employed by existing wearable BP measurement devices involve the indirect inference of BP via the calculation of characteristics and correlations such as blood flow velocity and time [9].  
The pulse wave velocity (PWV) and pulse transit time (PTT) are affected by the distance from the heart to the measuring sensor, which in turn affects blood pressure [10; 11]. However, this indirect measurement method faces challenges in terms of using the information related to personal health conditions that affect PWV and PTT, such as the size of the vessel (representing the vessel's condition), blood concentration, and elasticity of the vessel wall [12]. Many existing studies have therefore proposed algorithms based on the correlation between PTT and photoplethysmography (PPG) in order to directly measure the factors that influence BP [13; 14]. It is known that the weight, mass of body fat, percentage of body fat, arm circumference, arm length, and height of an individual are the physical factors that directly affect PTT [15].  
BP can be calculated by measuring blood flow from the heart to the PPG measurement sensor in the peripheral blood vessel. The PPG measurement sensor can infer BP by measuring the pulse wave in peripheral blood vessels. If the variability of the electrocardiography (ECG) waves can be coupled to individual physical data via algorithms, the inconvenience of entering user-specific information can hypothetically be minimized or eliminated via the transformation of PPG waves into non-linear data whenever BP is measured using a PPG sensor. In this study, we develop a method to deduce the variations in phase difference, blood vessel size, blood concentration, and elasticity of blood vessels among various individuals using only two PPGs based on the correlation between the average arterial pressure and BP.  
In order to reduce the error of the existing PPG estimated BP device, it is necessary to calculate and input the blood vessel cross-sectional area, cardiac output, and blood specific gravity, which are specific values that represent the condition of an individual's blood vessels. However, in this study, errors in BP measurement values can be minimized by utilizing only the phase difference between mean arterial pressure (MAP) and PPG.