Model-based analysis of arterial pulse signals for tracking changes in arterial wall parameters: a pilot study

Area of Science:

• Biomedical Engineering
• Cardiovascular Physiology
• Medical Device Technology

Background:

• Arterial wall parameters like radius and viscoelasticity are key indicators for cardiovascular diseases (CVD).
• Current monitoring systems for these parameters are often too complex for convenient home use.
• Developing accessible methods for tracking arterial health is crucial for early CVD detection and management.

Purpose of the Study:

• To investigate if model-based analysis of arterial pulse signals can track arterial wall parameter changes.
• To evaluate the efficacy of a microfluidic-based tactile sensor for this purpose.
• To establish a non-calibrated, home-use monitoring solution for cardiovascular health.

Main Methods:

• A microfluidic-based tactile sensor was employed to measure arterial pulse signals.
• A data-processing algorithm extracted key features from the pulse signal, including radius waveform derivatives.
• Dynamic system and hemodynamic models were developed to estimate arterial wall parameters (elasticity, viscosity) from extracted features without calibration.

Main Results:

• Model-based analysis successfully tracked changes in arterial radius, elasticity, and viscosity post-exercise.
• Estimated changes in arterial parameters at radial and carotid arteries aligned with existing literature.
• Significant differences were observed in estimated parameters between pre-exercise and post-exercise states.

Conclusions:

• Model-based analysis combined with a microfluidic tactile sensor enables effective tracking of arterial wall parameter changes.
• This approach demonstrates potential for developing a user-friendly, at-home cardiovascular monitoring system.
• The technology could facilitate early detection, timely intervention, and treatment assessment for cardiovascular diseases.