A Thorax Simulator for Complex Dynamic Bioimpedance Measurements With Textile Electrodes

Area of Science:

• Biomedical Engineering
• Medical Devices
• Wearable Technology

Background:

• Bioimpedance measurements offer non-invasive assessment of body composition and hemodynamic parameters like stroke volume.
• Integrating bioimpedance into textiles enhances personal healthcare by improving measurement ease, comfort, and coverage.
• Current bioimpedance measurement methods include bioimpedance spectroscopy (BIS) and impedance cardiography (ICG).

Purpose of the Study:

• To develop a novel thorax simulator for testing and calibrating bioimpedance devices.
• To create a simulator capable of mimicking the complete time-variant properties of the human thorax during impedance measurements.
• To evaluate bioimpedance devices, especially those using textile electrodes, by simulating complex electrode-skin contact impedances.

Main Methods:

• Development of a thorax simulator with adjustable base impedance and dynamic impedance components (real and imaginary parts).
• Inclusion of adjustable complex electrode-skin contact impedances for up to 8 electrodes.
• Integration of an electrocardiographic (ECG) signal to simulate physiological impedance changes and enable cardiographic measurements.

Main Results:

• The simulator successfully mimics dynamic thoracic impedance properties, including adjustable base impedance (24.6 Ω to 51.6 Ω) and dynamic impedance variations (peak-to-peak 0.2 Ω).
• The simulator provides a realistic electrocardiographic (ECG) signal alongside simulated physiological impedance changes.
• Testing with commercial BIS and ICG devices showed high correlation (r = 0.996) between preset and measured signals.

Conclusions:

• The developed thorax simulator accurately replicates human thoracic impedance variations, crucial for bioimpedance device development.
• This simulator facilitates the testing and calibration of bioimpedance devices, including those integrated with textiles.
• The ability to simulate stroke volume (SV), pre-ejection period (PEP), and extracellular resistance (Re) enhances the development of advanced personal healthcare monitoring tools.