Continuous Blood Pressure Measurement System Research Articles

A Machine Learning Approach to the Non-Invasive Estimation of Continuous Blood Pressure Using Photoplethysmography

Blood pressure is an important vital sign that sometimes requires continuous measurement. The current methods include cuff measurements (manual auscultation and oscillometric techniques) for non-continuous measurement and invasive arterial cannulation for continuous measurement. The use of photoplethysmography as a cuffless, non-invasive, and continuous blood pressure measurement system is investigated through the use of four neural networks. These predict the systolic blood pressure, diastolic blood pressure, mean arterial blood pressure, and waveform shape. The models are trained on 890 h of data from 1669 patients in the MIMIC-III database. Feature-trained artificial neural networks predict the systolic blood pressure to 5.26 ± 6.53 mmHg (mean error ± standard deviation), the diastolic blood pressure to 2.96 ± 3.31 mmHg, and the mean arterial pressure to 3.27 ± 3.55 mmHg. These are used to shift and scale the predicted waveform, allowing the waveform prediction neural network to optimise for the wave shape rather than the amplitude. The waveform prediction has 86.4% correlation with the actual arterial blood pressure waveform. All results meet international clinical blood pressure measurement standards and could potentially change how blood pressure is measured in both clinical and research settings. However, more data from healthy individuals and analysis of the models’ biases based on clinical features is required.

Development of a Portable Infrared-Type Noncontact Blood Pressure Measuring Device and Evaluation of Blood Pressure Elevation during Driving

Hypertension has been established as a major risk factor for cardiovascular morbidity and mortality. Therefore, prevention of hypertension is an urgent matter to maintain people’s health and avoid death, and out-of-office blood pressure measurement is said to be an integral part of the diagnosis and management of hypertension. Hypertension not only causes loss of productivity and economic loss but is also a major cause of road accidents. Therefore, it is important to develop an in-vehicle noncontact blood pressure measurement system for drivers. In addition to measurement accuracy, proper detection timing is also important, and there must be no difference between noncontact and contact detection times. In this study, we introduce an infrared cuffless and portable noncontact blood pressure monitoring system, its measurement principle, and performance evaluation. A total of 13 male adults participated in the experiment to evaluate the effect of time lag between the use of the infrared blood pressure monitoring system and the contact blood pressure monitoring system using a driving simulator. The changepoint method was applied to detect the first change point in the blood pressure time series data caused by the unexpected first appearance of the vehicle. The results showed that the detection time of the developed system was about 2.5 s shorter than that of the contact-type continuous blood pressure measurement system, with no significant difference.

Development of Continuous Blood Pressure Measurement System Using Photoplethysmograph and Pulse Transit Time

It is not only a problem for old age anyone. So, blood pressure is the one provides importance information with vital signs about cardiovascular health using oscillometric method. Unfortunately, this method required inflation and following deflation of the cuff. This method only gives instantaneous blood pressure and continuous measurement is not available. It is not available to the patients that required long term monitoring. To overcome this problem, the development of Continuous Non-Invasive Blood Pressure (NIBP) algorithm based on Pulse Transit Time (PTT) using two channel Photoplethysmograph (PPG) is proposed in this study. PPG is a non-invasive device for detecting blood volume changes can be affected by various physiological factors, analysis of the PPG signal can provide sufficient information on the human health condition; more specifically their cardio-vascular related performance. Literatures show that the PTT has linear relationship with blood pressure. Nevertheless, the determination of the model structure, order and real-time implementation to offer a continuous measurement of the PTT still remains challenging tasks in this area. PTT can be as index to monitor cardiovascular disease. In this project, dynamic model based on pulse transit time will be proposed to continuously monitor blood pressure by using PPG signals. Different kind of resolutions in microcontroller combined with PPG sensor will be used as well. MATLAB software is also been applied for PTT calculation based on two PPG sensors. PPG is method for detect blood volume changes with optical source transmitter send from one end and received the signal from another by receiver through body tissue as medium. MATLAB functions as Digital Signal Processing (DSP) for signals received in computer. Linear Regression technique and Fung's algorithm are applied to obtain the best fit line for all the points in order to systolic and diastolic blood pressure measurement. The results showed that the algorithm based on pulse transit time has been developed for the assessment of blood pressure and justify patient’ condition with 86.34% and 88.20% accuracy. Finally, this technique is a simple, user friendly and operator independent PPG system suitable for long term and wearable blood pressure monitor.

Design of a Continuous Blood Pressure Measurement System Based on Pulse Wave and ECG Signals.

With increasingly fierce competition for jobs, the pressures on people have risen in recent years, leading to lifestyle and diet disorders that result in significantly higher risks of cardiovascular disease. Hypertension is one of the common chronic cardiovascular diseases; however, mainstream blood pressure measurement devices are relatively heavy. When multiple measurements are required, the user experience and the measurement results may be unsatisfactory. In this paper, we describe the design of a signal collection module that collects pulse waves and electrocardiograph (ECG) signals. The collected signals are input into a signal processing module to filter the noise and amplify the useful physiological signals. Then, we use a wavelet transform to eliminate baseline drift noise and detect the feature points of the pulse waves and ECG signals. We propose the concept of detecting the wave shape associated with an instance, an approach that minimizes the impact of atypical pulse waves on blood pressure measurements. Finally, we propose an improved method for measuring blood pressure based on pulse wave velocity that improves the accuracy of blood pressure measurements by 58%. Moreover, the results meet the american medical instrument promotion association standards, which demonstrate the feasibility of our measurement system.

NONINVASIVE СONTINUOUS BLOOD PRESSURE MONITORING DEVICE

In medical practice it is often used continuous blood pressure measurement system. This monitor allows the doctor to see a graph of changes in blood pressure during the day in a familiar environment and in a typical rhythm of life for him. Such system involves a few measurements using oscillometric measurement method for every ten minutes. However, the cardiovascular system is extremely flexible and able to respond to drive very excitation. When unfortunate circumstances conventional blood pressure measurement systems is likely not to register such a reaction. In this article discussed a device for continuous blood pressure measurement which concurrently use photoplethysmography and oscillometric method of blood pressure measurement.

Recent Advance in Non-invasive Continuous Blood Pressure Measurement System

Recent Advance in Non-invasive Continuous Blood Pressure Measurement System