Estimating Blood Pressure from Photoplethysmogram Signal and Demographic Features using Machine Learning Techniques

Hypertension is a potentially unsafe health ailment, which can be indicated directly from the Blood pressure (BP). Hypertension always leads to other health complications. Continuous monitoring of BP is very important; however, cuff-based BP measurements are discrete and uncomfortable to the user. To address this need, a cuff-less, continuous and a non-invasive BP measurement system is proposed using Photoplethysmogram (PPG) signal and demographic features using machine learning (ML) algorithms. PPG signals were acquired from 219 subjects, which undergo pre-processing and feature extraction steps. Time, frequency and time-frequency domain features were extracted from the PPG and their derivative signals. Feature selection techniques were used to reduce the computational complexity and to decrease the chance of over-fitting the ML algorithms. The features were then used to train and evaluate ML algorithms. The best regression models were selected for Systolic BP (SBP) and Diastolic BP (DBP) estimation individually. Gaussian Process Regression (GPR) along with ReliefF feature selection algorithm outperforms other algorithms in estimating SBP and DBP with a root-mean-square error (RMSE) of 6.74 and 3.59 respectively. This ML model can be implemented in hardware systems to continuously monitor BP and avoid any critical health conditions due to sudden changes.Comment: Accepted for publication in Sensor, 14 Figures, 14 Table

Performance Measures Using Electronic Health Records: Five Case Studies

Presents the experiences of five provider organizations in developing, testing, and implementing four types of electronic quality-of-care indicators based on EHR data. Discusses challenges, and compares results with those from traditional indicators

Blood pressure control by home monitoring : meta-analysis of randomised trials

Objective To determine the effect of home blood pressure monitoring on blood pressure levels and proportion of people with essential hypertension achieving targets. Design Meta-analysis of 18 randomised controlled trials. Participants 1359 people with essential hypertension allocated to home blood pressure monitoring and 1355 allocated to the "control" group seen in the healthcare system for 2-36 months. Main outcome measures Differences in systolic (13 studies), diastolic (16 studies), or mean (3 studies) blood pressures, and proportion of patients achieving targets (6 studies), between intervention and control groups. Results Systolic blood pressure was lower in people with hypertension who had home blood pressure monitoring than in those who had standard blood pressure monitoring in the healthcare system (standardised mean difference 4.2 (95% confidence interval 1.5 to 6.9) mm Hg), diastolic blood pressure was lower by 2.4 (1.2 to 3.5) mm Hg, and mean blood pressure was lower by 4.4 (2.0 to 6.8) mm Hg. The relative risk of blood pressure above predetermined targets was lower in people with home blood pressure monitoring (risk ratio 0.90, 0.80 to 1.00). When publication bias was allowed for, the differences were attenuated: 2.2 ( − 0.9 to 5.3) mm Hg for systolic blood pressure and 1.9 (0.6 to 3.2) mm Hg for diastolic blood pressure. Conclusions Blood pressure control in people with hypertension (assessed in the clinic) and the proportion achieving targets are increased when home blood pressure monitoring is used rather than standard blood pressure monitoring in the healthcare system. The reasons for this are not clear. The difference in blood pressure control between the two methods is small but likely to contribute to an important reduction in vascular complications in the hypertensive population

Intracranial pressure monitoring in normal dogs using subdural and intraparenchymal miniature strain-gauge transducers.

BackgroundMonitoring of intracranial pressure (ICP) is a critical component in the management of intracranial hypertension. Safety, efficacy, and optimal location of microsensor devices have not been defined in dogs.Hypothesis/objectiveAssessment of ICP using a microsensor transducer is feasible in anesthetized and conscious animals and is independent of transducer location. Intraparenchymal transducer placement is associated with more adverse effects.AnimalsSeven adult, bred-for-research dogs.MethodsIn a prospective investigational study, microsensor ICP transducers were inserted into subdural and intraparenchymal locations at defined rostral or caudal locations within the rostrotentorial compartment under general anesthesia. Mean arterial pressure and ICP were measured continuously during physiological maneuvers, and for 20 hours after anesthesia.ResultsBaseline mean ± SD values for ICP and cerebral perfusion pressure were 7.2 ± 2.3 and 78.9 ± 7.6 mm Hg, respectively. Catheter position did not have a significant effect on ICP measurements. There was significant variation from baseline ICP accompanying physiological maneuvers (P < .001) and with normal activities, especially with changes in head position (P < .001). Pathological sequelae were more evident after intraparenchymal versus subdural placement.Conclusions and clinical importanceUse of a microsensor ICP transducer was technically straightforward and provided ICP measurements within previously reported reference ranges. Results support the use of an accessible dorsal location and subdural positioning. Transient fluctuations in ICP are normal events in conscious dogs and large variations associated with head position should be accounted for when evaluating animals with intracranial hypertension

Intervention planning and modification of the BUMP intervention: a digital intervention for the early detection of raised blood pressure in pregnancy

Background: Hypertensive disorders in pregnancy, particularly pre-eclampsia, pose a substantial health risk for both maternal and foetal outcomes. The BUMP (Blood Pressure Self-Monitoring in Pregnancy) interventions are being tested in a trial. They aim to facilitate the early detection of raised blood pressure through self-monitoring. This article outlines how the self-monitoring interventions in the BUMP trial were developed and modified using the person-based approach to promote engagement and adherence. Methods: Key behavioural challenges associated with blood pressure self-monitoring in pregnancy were identified through synthesising qualitative pilot data and existing evidence, which informed guiding principles for the development process. Social cognitive theory was identified as an appropriate theoretical framework. A testable logic model was developed to illustrate the hypothesised processes of change associated with the intervention. Iterative qualitative feedback from women and staff informed modifications to the participant materials. Results: The evidence synthesis suggested women face challenges integrating self-monitoring into their lives and that adherence is challenging at certain time points in pregnancy (for example, starting maternity leave). Intervention modification included strategies to address adherence but also focussed on modifying outcome expectancies, by providing messages explaining pre-eclampsia and outlining the potential benefits of self-monitoring. Conclusions: With an in-depth understanding of the target population, several methods and approaches to plan and develop interventions specifically relevant to pregnant women were successfully integrated, to address barriers to behaviour change while ensuring they are easy to engage with, persuasive and acceptable