Systolic Time Interval Extraction in Hypertensive and Hypotensive Pig Models Using Wearable Near-Field...

Area of Science:

• Biomedical Engineering
• Cardiovascular Physiology
• Medical Sensor Technology

Background:

• Cardiovascular diseases (CVDs) screening and monitoring rely on analyzing systolic time intervals (STIs).
• Hypertension is a major risk factor for CVDs, necessitating accurate STI measurement in hypertensive individuals.
• Validating non-invasive sensors in diverse hemodynamic conditions is crucial for reliable clinical application.

Purpose of the Study:

• To evaluate the accuracy of a near-field radio-frequency (RF) sensor for extracting STIs.
• To assess sensor performance in measuring isovolumic contraction time (ICT) and left ventricular ejection time (LVET) under normotensive, hypertensive, and hypotensive conditions.
• To validate the RF sensor as a potential screening tool for CVDs, particularly in hypertensive states.

Main Methods:

• Utilized a non-invasive near-field RF sensor to capture cardiac signals in a pig model.
• Extracted STIs, specifically ICT and LVET, by analyzing waveform features of valve dynamics during systole.
• Benchmarked RF sensor-derived STIs against traditional methods: phonocardiogram and aortic catheterization.

Main Results:

• Achieved study-wide mean relative errors of -4.4ms for ICT and -3.6ms for LVET.
• Demonstrated high accuracy of the RF sensor across normotensive, hypertensive, and hypotensive systemic pressures.
• Confirmed sensor performance with errors consistently below 5 ms.

Conclusions:

• The non-invasive RF sensor accurately extracts STIs under various systemic pressures.
• The validated accuracy supports the use of this RF sensor for CVD screening, including in hypertensive patients.
• This technology offers a promising, non-invasive approach for cardiovascular health monitoring.