Literature DB >> 34915462

Simplifying the hardware requirements for fast neural EIT of peripheral nerves.

Enrico Ravagli1, Svetlana Mastitskaya1, David Holder1, Kirill Aristovich1.   

Abstract

Objective. The main objective of this study was to assess the feasibility of lowering the hardware requirements for fast neural electrical impedance tomography (EIT) in order to support the distribution of this technique. Specifically, the feasibility of replacing the commercial modules present in the existing high-end setup with compact and cheap customized circuitry was assessed.Approach. Nerve EIT imaging was performed on rat sciatic nerves with both our standard ScouseTom setup and a customized version in which commercial benchtop current sources were replaced by custom circuitry. Electrophysiological data and images collected in the same experimental conditions with the two setups were compared. Data from the customized setup was subject to a down-sampling analysis to simulate the use of a recording module with lower specifications.Main results. Compound action potentials (573 ± 287μV and 487 ± 279μV,p=0.28) and impedance changes (36 ± 14μV and 31 ± 16μV,p=0.49) did not differ significantly when measured using commercial high-end current sources or our custom circuitry, respectively. Images reconstructed from both setups showed neglibile (<1voxel, i.e. 40μm) difference in peak location and a high degree of correlation (R2 = 0.97). When down-sampling from 24 to 16 bits ADC resolution and from 100 to 50 KHz sampling frequency, signal-to-noise ratio showed acceptable decrease (<-20%), and no meaningful image quality loss was detected (peak location difference <1voxel, pixel-by-pixel correlationR2 = 0.99).Significance: The technology developed for this study greatly reduces the cost and size of a fast neural EIT setup without impacting quality and thus promotes the adoption of this technique by the neuroscience research community. Creative Commons Attribution license.

Entities:  

Keywords:  current source; electrical impedance tomography; fast neural; hardware; peripheral nerves

Mesh:

Year:  2022        PMID: 34915462     DOI: 10.1088/1361-6579/ac43c0

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  1 in total

1.  Opinion: the Future of Electrical Impedance Tomography.

Authors:  Kirill Aristovich
Journal:  J Electr Bioimpedance       Date:  2022-03-31
  1 in total

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