Characteristic Ratio-Independent Arterial Stiffness-Based Blood Pressure Estimation

Intelligent Oscillometric System for Automatic Detection of Peripheral Arterial Disease

Peripheral arterial disease (PAD) is a progressing arterial disorder that is associated with significant morbidity and mortality. The conventional PAD detection methods are invasive, cumbersome, or require expensive equipment and highly trained technicians. Here, we propose a new automated, noninvasive, and easy-to-use method for the detection of PAD based on characterizing the arterial system by applying an external varying pressure using a cuff. The superposition of the internal arterial pressure and the externally applied pressure were measured and mathematically modeled as a function of cuff pressure. A feature-based learning algorithm was then designed to identify PAD patterns by analyzing the parameters of the derived mathematical models. Genetic algorithm and principal component analysis were employed to select the best predictive features distinguishing PAD patterns from normal. A RUSBoost ensemble model using neural network as the base learner was designed to diagnose PAD from genetic algorithm selected features. The proposed method was validated on data collected from 14 PAD patients and 19 healthy individuals. It achieved a high accuracy, sensitivity, and specificity of 91.4%, 90.0%, and 92.1%, respectively, in detecting PAD. The effect of age, a confounding factor that may have impacted our analyzes, was not considered in this study. The proposed method shows promise toward noninvasive and accurate detection of PAD and can be integrated into routine oscillometric blood pressure measurements.

Novel methods of testing and calibration of oscillometric blood pressure monitors

We present a robust method for testing and calibrating the performance of oscillometric non-invasive blood pressure (NIBP) monitors, using an industry standard NIBP simulator to determine the characteristic ratios used, and to explore differences between different devices. Assuming that classical auscultatory sphygmomanometry provides the best approximation to intra-arterial pressure, the results obtained from oscillometric measurements for a range of characteristic ratios are compared against a modified auscultatory method to determine an optimum characteristic ratio, Rs for systolic blood pressure (SBP), which was found to be 0.565. We demonstrate that whilst three Chinese manufactured NIBP monitors we tested used the conventional maximum amplitude algorithm (MAA) with characteristic ratios Rs = 0.4624±0.0303 (Mean±SD) and Rd = 0.6275±0.0222, another three devices manufactured in Germany and Japan either do not implement this standard protocol or used different characteristic ratios. Using a reference database of 304 records from 102 patients, containing both the Korotkoff sounds and the oscillometric waveforms, we showed that none of the devices tested used the optimal value of 0.565 for the characteristic ratio Rs, and as a result, three of the devices tested would underestimate systolic pressure by an average of 4.8mmHg, and three would overestimate the systolic pressure by an average of 6.2 mmHg.

Design and implementation of an advanced telemedicine model for the rural people of Bangladesh

OBJECTIVES

Telemedicine based healthcare service faces different difficulties especially in the remote people of Bangladesh. The objective of this study was to implement an advanced telemedicine model in order to provide the healthcare services for the rural people of Bangladesh.

METHODS

We developed the telemedicine model using an ardunio based low cost portable telemedicine tool kit by interfacing android application. Then we collected ECG, blood pressure, temperature, concentration of glucose in blood, SPO2, body position, airflow, height and weight through our developed model. Moreover, we designed a server for storing the recorded signal from the patients in order to treat them by health care professionals. Finally, this model is successfully tested with the patients of Marie Stopes Bangladesh Hospital Dhaka.

RESULTS

We have removed noise from the recorded signal successfully through our developed hardware and software based techniques. Real time data were visualized to the expert doctor in order to prescribe them through our model.

CONCLUSIONS

These results support that rural patient vital information can be collected in an automated way through the advanced model. Both rural and urban doctors can share and exchange patient information more effectively for the treatment of patient. The results of this research indicated that our developed telemedicine system can be used effectively in order to deliver healthcare services for the rural people of Bangladesh.