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University of Manchester

1. Quraishi, Tanviha. Clinical Applications of Electrical Impedance Tomography.

Degree: 2017, University of Manchester

INTRODUCTION Electrical Impedance Tomography (EIT) is an emerging clinical imaging technique. Functional EIT by Evoked Response (fEITER) was developed at the University of Manchester as a high-speed, functional brain imaging device for use at the bedside. This 32-electrode EIT system applies an injection frequency of 10kHz and captures data using a 10ms temporal resolution. This thesis reports on the first volunteer and patient trials undertaken using fEITER for the following conditions: (a) flashing visual sequence - 14 awake volunteers; (b) a voluntary Valsalva manoeuvre (VM) - 15 awake volunteers and (c) during the induction of anaesthesia - 16 elective surgical patients.AIMS The research presented in this thesis was undertaken to differentiate between noise and physiological changes in raw fEITER data signals.METHODS SNR was determined for fEITER. Raw fEITER signals were pre-processed to reduce noise and dominant trends before multiple comparisons between reference and stimulus data were undertaken. Histograms and ROC curves were produced to illustrate the difference between reference and stimulus fEITER data. AUC values for single-subject and pooled ROC curves were calculated to determine whether fEITER data can be reliably differentiated between reference and stimulus conditions. Approximate Entropy (ApEn) was applied to evaluate the regularity of high frequency components within fEITER data for each trial condition.RESULTS Average SNR values for fEITER acquired using mesh and physical phantoms ranged from 62.94dB to 63.58dB, and 28.29dB to 31.45dB respectively. The following AUC values were acquired: Visual stimulus-frontal electrode pairs and electrode pairs overlying the visual cortex 0.520 and 0.505 respectively; VM: 0.658; and induction of anaesthesia: 0.547. The VM induced the greatest difference between pooled reference and stimulus data. Visual stimulation and induction of anaesthesia data showed poor distinction between pooled reference and stimulus data, although some single subject data did show a significant response. No significant differences were acquired for the comparison of ApEn-reference and ApEn-stimulus data for all trial conditions using a Wilcoxon’s signed ranks test (visual stimulus-frontal electrode pairs: upper p = 0.998, visual stimulus-electrode overlying the visual cortex: upper p = 0.980; the VM: upper p = 0.976, and induction of anaesthesia: p = 0.912).DISCUSSION Although single-subject and pooled fEITER data recorded during the VM produced the greatest differences between reference and stimulus measurements, stimuli such as visual flashes and induction of anaesthesia may not be large enough to induce quantifiable changes between reference and stimulus data recorded from single electrode pairs.Collectively, these results provide little evidence to show that pre-processing of raw fEITER data amplifies features in fEITER waveforms which may be representative of physiological changes induced by an applied stimulus. Advisors/Committee Members: POLLARD, BRIAN BJ, MARCHANT, THOMAS T, Pollard, Brian, Bryan, Angella, Marchant, Thomas.

Subjects/Keywords: Electrical Impedance Tomography; Brain

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APA (6th Edition):

Quraishi, T. (2017). Clinical Applications of Electrical Impedance Tomography. (Doctoral Dissertation). University of Manchester. Retrieved from

Chicago Manual of Style (16th Edition):

Quraishi, Tanviha. “Clinical Applications of Electrical Impedance Tomography.” 2017. Doctoral Dissertation, University of Manchester. Accessed April 15, 2021.

MLA Handbook (7th Edition):

Quraishi, Tanviha. “Clinical Applications of Electrical Impedance Tomography.” 2017. Web. 15 Apr 2021.


Quraishi T. Clinical Applications of Electrical Impedance Tomography. [Internet] [Doctoral dissertation]. University of Manchester; 2017. [cited 2021 Apr 15]. Available from:

Council of Science Editors:

Quraishi T. Clinical Applications of Electrical Impedance Tomography. [Doctoral Dissertation]. University of Manchester; 2017. Available from: