Bi-frequency symmetry difference EIT - feasibility and limitations of application to stroke diagnosis
MetadataShow full item record
This item's downloads: 59 (view details)
McDermott, B. J., Ohalloran, M., Avery, J., & Porter, E. (2019). Bi-Frequency Symmetry Difference EIT - Feasibility and Limitations of Application to Stroke Diagnosis. IEEE Journal of Biomedical and Health Informatics, doi: 10.1109/JBHI.2019.2960862
Objective: Bi-Frequency Symmetry Difference (BFSD)-EIT can detect, localize and identify unilateral perturbations in symmetric scenes. Here, we test the viability and robustness of BFSD-EIT in stroke diagnosis. Methods: A realistic 4-layer Finite Element Method (FEM) head model with and without bleed and clot lesions is developed. Performance is assessed with test parameters including: measurement noise, electrode placement errors, contact impedance errors, deviations in assumed tissue conductivity, deviations in assumed anatomy, and a frequency-dependent background. A final test is performed using ischemic patient data. Results are assessed using images and quantitative metrics. Results: BFSD-EIT may be feasible for stroke diagnosis if a signal-to-noise ratio (SNR) of ≥60dB is achievable. Sensitivity to errors in electrode positioning is seen with a tolerance of only ±5mm, but a tolerance of up to ±30mm is possible if symmetry is maintained between symmetrically opposite partner electrodes. The technique is robust to errors in contact impedance and assumed tissue conductivity up to at least ±50%. Asymmetric internal anatomy affects performance but may be tolerable for tissues with frequency-dependent conductivity. Errors in assumed external geometry marginally affect performance. A frequency-dependent background does not affect performance with carefully chosen frequency points or use of multiple frequency points across a band. The Global Left-Hand Side (LHS) & Right-Hand Side (RHS) Mean Intensity metric is particularly robust to errors. Conclusion: BFSD-EIT is a promising technique for stroke diagnosis, provided parameters are within the tolerated ranges. Significance: BFSD-EIT may prove an important step forward in imaging of static scenes such as stroke.
This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. Please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.
The following license files are associated with this item: