Development of novel devices and methods for blood pressure measurement

Abstract

Hypertension, a common condition that affects over 25% of the global population, is a significant risk factor for various cardiovascular and renal complications. It is also a leading cause of death worldwide. In India, hypertension is responsible for a significant number of stroke deaths (57%) and coronary heart disease deaths (24%). Accurate measurement of blood pressure is critical for managing hypertension and reducing the risk of cardiovascular morbidity and mortality. This thesis presents research on developing new blood pressure monitoring technologies that can potentially replace traditional methods that use mercury. The focus is on two specific methods: a mercury-free sphygmomanometer called Merkfree and a cuffless method using ultrasound. We have developed Merkfree, which is a mercury-free sphygmomanometer that looks, feels and operates just like a traditional mercury sphygmomanometer. It uses Galinstan as a substitute for mercury which is a non-toxic alloy of Gallium, Indium and Tin. Galinstan is nearly half as dense as mercury and sticks to glass. To work with the lower density, an enclosure and scale that is nearly double the length of MS was designed. The issue of stickiness with glass was resolved by maintaining a small meniscus of a reducing agent in the measuring tube and tank of Merkfree. Clinical trials have been conducted to validate the accuracy of Merkfree against MS and oscillometric sphygmomanometer (OS) over 252 patients at DMC&H, Ludhiana. The results show a good correlation of the systolic and diastolic BP measurements from Merkfree with respect to MS and the OS. The mean absolute percentage error is less than 10% for both systolic blood pressure (SBP) and diastolic blood pressure (DBP). We also found that Merkfree has lower rounding-off errors compared to MS. Another direction that we have explored is cuffless measurement of BP using ultrasound. In this method, the arterial wall is pushed with an acoustic radiation push impulse (ARFI). After the completion of the ARFI pulse, the artery undergoes impulsive unloading which stimulates a hoop mode vibration. The author designed two machine learning (ML) models which make it possible to estimate the internal pressure of the artery using ultrasonically measurable parameters. To generate the training data for the ML models, extensive FEM eigen frequency simulations were done for different tubes under pressure by sweeping through a range of values for inner lumen diameter (ILD), tube density (TD), elastic modulus, internal pressure (IP), tube length, and Poison’s ratio. Through image processing applied on images of different eigen modes supported for each simulated case, the hoop mode frequency (HMF) was identified. Two different ML models were designed based on the simulated data. One is a four-parameter model (FPM) that takes TT, TD, ILD, and HMF as the inputs and gives out IP as output. Second is a three-parameter model (TPM) that takes TT, ILD, HMF as inputs and IP as output. In addition to the accuracy of these models on simulated data, their performance was verified experimentally on two arterial phantoms at a range of pressures. In conclusion, this thesis presents new blood pressure monitoring technologies that can potentially replace traditional methods that use mercury. The focus is on two methods: a mercury-free sphygmomanometer called Merkfree and a cuffless method using ultrasound. Both methods have been tested and shown to have good correlation with traditional methods and have the potential for use in clinical settings. These technologies can aid in achieving the goal of eliminating mercury from healthcare while also providing accurate and accessible blood pressure measurement for clinicians and patients.