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High Density Event-related Potential Data Acquisition in Cognitive Neuroscience

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Advanced Computing Methods for Impedance Plethysmography Data Processing.

Volodymyr Khoma^1,2, Halyna Kenyo², Aleksandra Kawala-Sterniuk¹

¹Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, 45-758 Opole, Poland.

Sensors (Basel, Switzerland)

|March 26, 2022

Summary

This summary is machine-generated.

This study introduces computer methods to enhance impedance plethysmography (IP) rheograms for improved hemodynamic parameter analysis. The innovations ensure system stability and extend functionality, offering advanced artifact elimination and indicator determination.

Keywords:

analysis of rheographic signals avanced computing methods base impedance compensation digital signal processing impedance plethysmography rheogram characteristic points

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Area of Science:

Biomedical Engineering
Medical Signal Processing

Background:

Impedance plethysmography (IP) is crucial for hemodynamic monitoring.
Existing rheogram analysis methods face challenges in stability and functionality.
Computer-based signal processing offers potential for IP system enhancement.

Purpose of the Study:

To introduce innovative computer methods for improving rheograph characteristics and rheogram development efficiency.
To enhance the stability and functionality of IP systems using digital signal processing.
To develop advanced methods for determining hemodynamic parameters from rheograms.

Main Methods:

Digital signal processing techniques including digital potentiometer for base resistance compensation, quadrature excitation signal synthesis, and synchronous detection.
Development of three novel methods for respiratory artifact elimination: Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and spline function approximation.
Application of computer methods, including wavelet decomposition, for physiological indicator determination.
Evaluation of various rheogram compression algorithms.

Main Results:

Successfully implemented digital signal processing for enhanced rheograph stability and functionality.
Proposed and validated three effective methods for eliminating respiratory artifacts from rheograms.
Developed and described computer-based methods for accurate physiological indicator determination.
Presented an evaluation of different rheogram compression algorithm efficiencies.

Conclusions:

The proposed computer methods significantly improve impedance plethysmography rheogram analysis.
Digital signal processing enhances the reliability and scope of hemodynamic monitoring using IP.
Advanced artifact elimination and indicator determination methods contribute to more accurate physiological assessments.