Smartphones: A Tool for Detecting Systolic Hypertension in Underserved Populations
Introduction
Systolic hypertension, a common condition where blood pressure rises during heartbeats, significantly increases the risk of cardiovascular events. It disproportionately affects underserved populations, where access to blood pressure (BP) measuring devices is often limited. Smartphones, widely available even in low-income countries, offer a potential solution.
Smartphone-Based Blood Pressure Measurement
Researchers have developed a smartphone application that converts smartphones into BP sensors. The app employs the oscillometric principle, similar to conventional cuff devices. Users perform guided thumb and hand maneuvers to vary the transmural pressure of the thumb artery, while standard phone sensors measure pressure changes. These measurements are analyzed to compute systolic BP or diastolic BP, known as pulse pressure (PP).
Usability and Accuracy Studies
Studies involving 24 participants revealed that after a short learning period, users could obtain valid PP measurements with an average success rate of 60%. The smartphone app demonstrated high accuracy, with a correlation coefficient of 0.70 and a bias error of -1.0 mmHg and precision error of 7.2 mmHg against a validated cuff device over a 40 mmHg reference PP range.
Value of PP in Hypertension Detection
PP correlates well with systolic BP. Analysis of the National Health and Nutrition Examination Survey database showed a strong relationship between average systolic BP and average PP. Neural networks trained on PP, demographics, and smoking history could detect systolic hypertension with an area under the curve (AUC) of 0.9, indicating high accuracy.
Impact of Measurement Error
Adding Gaussian random noise to PP measurements to simulate measurement error caused a modest decrease in ROC AUC from 0.9 to 0.87, suggesting that the app’s PP measurement accuracy is sufficient for reliable hypertension detection.
Discussion
Previous attempts at smartphone-based BP measurement faced limitations due to the need for force sensors or inaccurate finger contact pressure assessment. The new smartphone app overcomes these challenges by leveraging screen touch sensors as a surrogate for contact pressure and focusing on PP.
The app’s accuracy and usability make it a valuable tool for detecting systolic hypertension, especially in underserved populations. It could help raise awareness, promote early intervention, and reduce the burden of hypertension globally.
Conclusion
This smartphone application offers a feasible and accurate method for detecting systolic hypertension in underserved populations. Its simplicity, widespread availability, and potential impact make it a promising tool for improving cardiovascular health equity.
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