In vitro localisation of intracranial haematoma using electrical impedance tomography semi-array

A Review of EMG-, FMG-, and EIT-Based Biosensors and Relevant Human–Machine Interactivities and Biomedical Applications

Wearables developed for human body signal detection receive increasing attention in the current decade. Compared to implantable sensors, wearables are more focused on body motion detection, which can support human–machine interaction (HMI) and biomedical applications. In wearables, electromyography (EMG)-, force myography (FMG)-, and electrical impedance tomography (EIT)-based body information monitoring technologies are broadly presented. In the literature, all of them have been adopted for many similar application scenarios, which easily confuses researchers when they start to explore the area. Hence, in this article, we review the three technologies in detail, from basics including working principles, device architectures, interpretation algorithms, application examples, merits and drawbacks, to state-of-the-art works, challenges remaining to be solved and the outlook of the field. We believe the content in this paper could help readers create a whole image of designing and applying the three technologies in relevant scenarios.

Advances in electrical impedance tomography-based brain imaging

Novel advances in the field of brain imaging have enabled the unprecedented clinical application of various imaging modalities to facilitate disease diagnosis and treatment. Electrical impedance tomography (EIT) is a functional imaging technique that measures the transfer impedances between electrodes on the body surface to estimate the spatial distribution of electrical properties of tissues. EIT offers many advantages over other neuroimaging technologies, which has led to its potential clinical use. This qualitative review provides an overview of the basic principles, algorithms, and system composition of EIT. Recent advances in the field of EIT are discussed in the context of epilepsy, stroke, brain injuries and edema, and other brain diseases. Further, we summarize factors limiting the development of brain EIT and highlight prospects for the field. In epilepsy imaging, there have been advances in EIT imaging depth, from cortical to subcortical regions. In stroke research, a bedside EIT stroke monitoring system has been developed for clinical practice, and data support the role of EIT in multi-modal imaging for diagnosing stroke. Additionally, EIT has been applied to monitor the changes in brain water content associated with cerebral edema, enabling the early identification of brain edema and the evaluation of mannitol dehydration. However, anatomically realistic geometry, inhomogeneity, cranium completeness, anisotropy and skull type, etc., must be considered to improve the accuracy of EIT modeling. Thus, the further establishment of EIT as a mature and routine diagnostic technique will necessitate the accumulation of more supporting evidence.

Arrangement of boundary electrodes for detection of frontal lobe disease with electrical impedance tomography

Purpose: Caused by brain trauma or blood vessel abnormality, intracerebral hemorrhage and secondary ischemia have become prevalent and severe neurological diseases. The timely and accurate detection of disease is essential for the recovery of patients. As an emerging visualization technique, electrical impedance tomography (EIT) offers an alternative. It is able to reconstruct the conductivity distribution that reflects the pathological variation of human tissue. Approach: In the EIT-based detection, electrodes are usually in uniform arrangement, which may be not suitable in some conditions. To enhance sensitivity in the region of interest, EIT with a novel offset arrangement of boundary electrodes is proposed to image a simulated frontal lobe hemorrhage and secondary ischemia. To cope with the ill-posed inverse problem, the L1 regularization method is developed during the reconstruction. In addition, the impact of noise with a signal-to-noise ratio of 56 dB is studied. Results: Compared with the traditional uniform electrode arrangement, the results demonstrate that EIT with the proposed offset arrangement of electrodes is more advantageous for imaging frontal lobe disease. Conclusions: The proposed offset arrangement of electrodes is superior to the traditional uniform arrangement in imaging frontal lobe disease, especially under the impact of noise.

Real-time imaging of infarction deterioration after ischemic stroke in rats using electrical impedance tomography

OBJECTIVE

This study investigated the feasibility of electrical impedance tomography (EIT) for monitoring the deterioration of ischemic lesion after the onset of stroke.

APPROACH

Fifteen rats were randomly distributed into two groups: rats operated to establish a right middle cerebral artery occlusion (MCAO) (n  =  10), and sham-operated rats (n  =  5). Then, the operated rats were kept 2 h under anesthesia for EIT monitoring. Subsequently, descriptive statistical analysis was performed on whole-brain resistivity changes, and repeated-measures analysis of variance (ANOVA) on the average resistivity variation index. Additionally, pathological examinations were performed after 6 h of infarction.

MAIN RESULTS

The results obtained showed that ischemic damage developed in the right corpus striatum of the rats with MCAO, whereas the brains of the sham group showed no anomalies. The descriptive statistical analysis revealed that the whole-brain resistivity changes after 30, 60, 90, and 120 min of infarction were 0.063  ±  0.038, 0.097  ±  0.046, 0.141  ±  0.062, and 0.204  ±  0.092 for the rats with MCAO and 0.029  ±  0.021, 0.002  ±  0.002, 0.017  ±  0.011, and  -0.001  ±  0.011 for the sham-operated rats, respectively. The repeated-measures ANOVA revealed that the right MCAO model resulted in a significant impedance increase in the right hemisphere, which continued to increase over time after infarction.

SIGNIFICANCE

The overall study results indicate that EIT facilitates monitoring of local impedance variations caused by MCAO and may be a solution for real-time monitoring of intracranial pathological changes in ischemic stroke patients.