Abstract
OBJECTIVE: Many commercially available arterial blood pressure measurement devices suffer from a range of weaknesses. For example, common weaknesses include being inaccurate, invasive, and ad hoc; many also require explicit user calibration or cut off blood flow to a limb. A novel algorithmic approach is presented to accurately estimate systolic and diastolic blood pressure in a way that does not require any explicit user calibration, is noninvasive, and does not cut off blood flow. METHODS: The approach uses ultrasound images of the arterial wall and corresponding contact force data to obtain blood pressure estimates. To acquire data, an ultrasound probe was placed on the patient's carotid artery and the contact force was increased from 1.5 to 12 N. The artery was then algorithmically segmented from the recorded DICOM B-Mode data. The segmentation data and the contact force were used as input into the Levenberg-Marquardt optimization method to solve for the parameters, including blood pressure, of a simple finite element model of the carotid artery. RESULTS: The algorithm was validated on 24 healthy volunteers. Algorithm arterial blood pressure predictions were compared to oscillometric blood pressure cuff readings. Regression and Bland-Altman analyses were performed on the data. CONCLUSION: Both systolic pressure and diastolic pressure can be estimated using this novel noninvasive ultrasound-based method (systolic accuracy/precision: $-$ 2.36 mmHg/10.21 mmHg; diastolic accuracy/precision: $-$ 0.32/8.23 mmHg). SIGNIFICANCE: The method occupies a clinical middle ground between the arterial catheter and cuff-based techniques. It has the potential to give accurate results for patients with hypertension and atherosclerosis.