Study of an Automatic Sphygmomanometer System

A simple and dependable method of automatically measuring blood pressure indirectly would be of great help to the medical profession. An electronic system to implement the measurement of blood pressure using a double cuff method is presented. The scheme is to determine diastolic pressure from the amplitude of the difference signal obtained by subtracting the pulse wave observed in one cuff from that of the other, and to determine systolic pressure from the amplitude of the pulse wave observed in the cuff furthermost from the heart. Although the system is electronically practical, the results obtained from this system show that the difference signal does not give a dependable indication of the diastolic pressure point. The method of determining systolic pressure is workable

Improving the design of arterial blood pressure monitor

This paper present the implementation of a blood pressure monitor which provides taking measurements during inflation of the arm cuff. Brief overview of functions of modern BPM is given. Methods of blood pressure measuring are shown. Block diagram of a device is pictured and the operation principle of blood pressure monitor is described. Signal filtering and amplification stage is suggested. Neural networks algorithm is presented. Using this algorithm for signal processing affords getting results with sufficient precision

Blood pressure estimation using pulse transit time models

Abstract. Blood pressure (BP) is an important indicator of human health. Common methods for measuring BP continuously are either invasive, intermittent or they require using a cumbersome cuff. Pulse Transmit Time (PTT) -based measurement can be an alternative for such methods, as it ensures continue and non-invasive monitoring. However, since the method is indirect, it requires careful modelling of PTT-BP relation. In this thesis, three approaches of BP estimation from PTT are tested: linear regression, nonlinear Moens and Korteweg model and nonlinear model developed by Gesche. In the experiments, cardiovascular pulses for PTT were sensed using two fiber optics based accelerometers developed at the University of Oulu. To evaluate feasibility of presented models, the results were compared with reference BP values, measured using methods accepted for the commercial use. There were two groups of data. One was compared with BP measured using invasive catheter. Second group was compared with BP measured using volume clamp method. Obtained results suggest, that the presented calculation methods in present state still require further development in order to provide accurate BP values, however, they can be potentially used for observation of BP changes

Mobile Personal Healthcare System for Non-Invasive, Pervasive and Continuous Blood Pressure Monitoring: A Feasibility Study

Background: Smartphone-based blood pressure (BP) monitor using photoplethysmogram (PPG) technology has emerged as a promising approach to empower users with self-monitoring for effective diagnosis and control ofhypertension (HT). Objective: This study aimed to develop a mobile personal healthcare system for non-invasive, pervasive, and continuous estimation of BP level and variability to be user-friendly to elderly. Methods: The proposed approach was integrated by a self-designed cuffless, calibration-free, wireless and wearable PPG-only sensor, and a native purposely-designed smartphone application using multilayer perceptron machine learning techniques from raw signals. We performed a pilot study with three elder adults (mean age 61.3 ± 1.5 years; 66% women) to test usability and accuracy of the smartphone-based BP monitor. Results: The employed artificial neural network (ANN) model performed with high accuracy in terms of predicting the reference BP values of our validation sample (n=150). On average, our approach predicted BP measures with accuracy \u3e90% and correlations \u3e0.90 (P \u3c .0001). Bland-Altman plots showed that most of the errors for BP prediction were less than 10 mmHg. Conclusions: With further development and validation, the proposed system could provide a cost-effective strategy to improve the quality and coverage of healthcare, particularly in rural zones, areas lacking physicians, and solitary elderly populations

Conduit Artery Photoplethysmography and its Applications in the Assessment of Hemodynamic Condition

Elektroniskā versija nesatur pielikumusPromocijas darbā ir izstrādāta maģistrālo artēriju fotopletizmogrāfijas (APPG) metode hemodinamisko parametru novērtējumam. Pretstatot referentām metodēm, demonstrēta iespēja iegūt arteriālo elasticitāti raksturojošus parametrus, izmantojot APPG signāla formas analīzi (atvasinājuma un signāla formas aproksimācijas parametri) un ar APPG iegūtu pulsa izplatīšanās ātrumu unilaterālā gultnē. Izstrādāta APPG reģistrācijas standartizācija, mērījuma laikā nodrošinot optimālo sensora piespiedienu. Šis paņēmiens validēts ārējās ietekmes (sensora piespiediens) un hemodinamisko stāvokļu (perifērā vaskulārā pretestība) izmaiņās femorālā APPG signālā, identificējot būtiskākos faktorus APPG pielietojumos. Veikta APPG validācija asinsrites fizioloģijas un preklīniskā pētījumā demonstrējot APPG potenciālu pētniecībā un diagnostikā. Izstrādāts pulsa formas parametrizācijas paņēmiens, saistot fizioloģiskās un aproksimācijas modeļa komponentes. Atslēgas vārdi: maģistrālā artērija, fotopletizmogrāfija, arteriālā elasticitāte, metodes standartizācija, pulsa formas kvantifikācija, vazomocija, sepseThe doctoral thesis features the development of a conduit artery photoplethysmography technique (APPG) for the evaluation of hemodynamic parameters. Contrasting referent methods, the work demonstrates the possibility to receive parameters characterizing the arterial stiffness by means of APPG waveform analysis (derivation and waveform approximation parameters) and APPG obtained pulse wave velocity in a unilateral vascular bed. In this work APPG standardization technique was developed providing optimal probe contact pressure conditions. It was validated by altering the external factors (probe contact pressure) and hemodynamic conditions (peripheral vascular resistance) on the femoral APPG waveform identifying the key factors in APPG applications. The APPG validation in blood circulation physiology and a pre-clinical trial was performed demonstrating APPG potential in the extension of applications. An arterial waveform parameterization was developed relating the physiological wave to approximation model components. Keywords: conduit artery, photoplethysmography, arterial stiffness, method standardization, waveform parametrization, vasomotion, sepsi

Cuffless Blood Pressure Estimation

The blood pressure is an important factor in the diagnosis and evaluation of several diseases, such as acute myocardial infarction and stroke. This way, continuous monitorization of this parameter is crucial to a correct health evaluation. The current methods, like the oscillometric method, have some major drawbacks, that can influence the output values or even make the measurements impossible. One example is the high frequency evaluation of the blood pressure, in the standard used methods the process of measuring can take up to 3 minutes, and a waiting time is necessary between consecutive measurements. This dissertation presents two different cuffless solution to solve those problems. One based on physical models of the human body, and the other using machine learning techniques. In the first solution seven models that correlate pulse transit time and blood pressure, deducted by different authors, were tested to evaluate which one performed better. The testes were performed in a custom dataset acquired at Fraunhofer AICOS and in clinical environment, with two different devices (low cost device and medical grade device). The results indicate that pulse transit time can be used to track blood pressure, the developed device/method was evaluated as grade A based in the Standard IEEE 1708-2014. The second solution it’s a proof of concept using a public database and three different machine learning methods (Random Forest, Neural Network and AdaBoost). Two sets of features are calculated from the ECG and PPG signals, one using TSFEL (spectral, frequency and time domain features) and a total of 15 custom features. The proposed method outperforms the methods presented in bibliography with mean absolute error of 3.6 mmHg and 2.0 mmHg to systolic and diastolic blood pressure respectively

Estimating pulse wave velocity using mobile phone sensors

Pulse wave velocity has been recognised as an important physiological phenomenon in the human body, and its measurement can aid in the diagnosis and treatment of chronic diseases. It is the gold standard for arterial stiffness measurements, and it also shares a positive relationship with blood pressure and heart rate. There exist several methods and devices via which it can be measured. However, commercially available devices are more geared towards working health professionals and hospital settings, requiring a significant monetary investment and specialised training to operate correctly. Furthermore, most of these devices are not portable and thus generally not feasible for private home use by the common individual. Given its usefulness as an indicator of certain physiological functions, it is expected that having a more portable, affordable, and simple to use solution would present many benefits to both end users and healthcare professionals alike. This study investigated and developed a working model for a new approach to pulse wave velocity measurement, based on existing methods, but making use of novel equipment. The proposed approach made use of a mobile phone video camera and audio input in conjunction with a Doppler ultrasound probe. The underlying principle is that of a two-point measurement system utilising photoplethysmography and electrocardiogram signals, an existing method commonly found in many studies. Data was collected using the mobile phone sensors and processed and analysed on a computer. A custom program was developed in MATLAB that computed pulse wave velocity given the audio and video signals and a measurement of the distance between the two data acquisition sites. Results were compared to the findings of previous studies in the field, and showed similar trends. As the power of mobile smartphones grows, there exists potential for the work and methods presented here to be fully developed into a standalone mobile application, which would bring forth real benefits of portability and cost-effectiveness to the prospective user base