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Related Experiment Videos

To detect lung ventilation with multi-frequency EIT system.

Shuai Zhang1, Guizhi Xu, Renping Wang

  • 1Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability, Hebei University of Technology, Tianjin, PR China. zs@hebut.edu.cn

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|November 16, 2007
PubMed
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This study introduces a multi-frequency electrical impedance tomography (EIT) system for monitoring human lung ventilation. The system proved effective and reliable for assessing respiration function.

Area of Science:

  • Biomedical Engineering
  • Medical Imaging
  • Physiological Monitoring

Background:

  • Electrical Impedance Tomography (EIT) is a non-invasive imaging technique.
  • Monitoring human lung ventilation is crucial for respiratory function assessment.
  • Existing EIT systems may have limitations in current sourcing and data acquisition speed.

Purpose of the Study:

  • To develop and evaluate a novel multi-frequency EIT system.
  • To assess the system's capability for monitoring human lung ventilation.
  • To determine the reliability and extendibility of the proposed EIT approach.

Main Methods:

  • Implementation of an EIT system utilizing the DDS AD9852.
  • Development of a multi-frequency current source for enhanced imaging.

Related Experiment Videos

  • Fast data acquisition capabilities for dynamic monitoring.
  • Utilizing differential imaging to visualize lung ventilation.

    • Main Results:

    • Successful experimental validation of the multi-frequency EIT system.
    • Demonstration of system consistency and extendibility.
    • Acquisition of differential images reflecting human lung ventilation.

    Conclusions:

    • The developed multi-frequency EIT system is a reasonable and reliable method for imaging lung ventilation.
    • The EIT technique shows significant potential as a tool for monitoring respiration function.
    • This approach offers a promising advancement in non-invasive respiratory monitoring.