KEYWORDS: Head, Electrodes, Analog to digital converters, Skull, 3D modeling, Brain imaging, Analog electronics, Tomography, Medical image reconstruction, 3D image reconstruction, Electrical engineering
Electrical Impedance Tomography (EIT) is a medical imaging technique that reconstructs impedance distribution inside a target object by injecting electrical currents into pairs of electrodes and measuring induced voltages on the remaining electrodes. Since neural signals result from the activity of ion channels causing impedance changes in the cell membrane, EIT can image these neural activities for understanding brain function and medical purposes. In our research, our self-developed electronic prototype board was used to generate high-quality electrical current and collect the data on electrodes with a high sampling rate and bit-resolution. In image reconstruction, a preprocessing data analysis algorithm was newly developed and applied to improve the accuracy of our EIT imaging. The human head has complex anatomical geometry and non-uniform resistivity distribution along with the highly resistive skull, which makes brain-EIT remains challenging inaccurate image reconstruction. To mimic the human head, a multi-layered human head phantom was designed and tested to investigate the effect of the skull structure on imaging. In this presentation, comparison studies for measurements and simulation results will be introduced to discuss the source of errors and improve the accuracy and efficiency of our brain-EIT system.
KEYWORDS: Neuroimaging, Tomography, Digital signal processing, Analog electronics, Signal processing, Signal to noise ratio, Digital electronics, Data acquisition, Brain, Visualization
Functional neuroimaging techniques are becoming mandatory tools for neuroscience research and brain disorders medical therapy, respectively. Electrical Impedance Tomography (EIT) has been impressed neuroscientists for its advantages of fast, radiation-free, and low-cost brain visualization method. Implementation of EIT on neuroimaging requires high performance data acquisition system which significantly depends on analog and digital electronic circuitry to achieve high and improve signal to noise ratio (SNR). A proposed EIT system based on high performance digital signal processor (DSP) has been successfully designed and developed for first prototype. A precise data acquisition unit that provides 24-bit 16 channels simultaneously sampling up to 100ksps was integrated into the system alongside with stable and biocompatible stimulation analog current source. Simulation of analog circuitry was constructed using PSPICE software. The proposed EIT system was designed using Cadence PCB Editor software to acquire compact integration requirements with all EIT components on a single circuit board. Evaluation of the proposed EIT system was conducted in a neural simulated environment phantom experiment. With this proposed system, EIT study on neural activity recording and neuroimaging has potentials to accelerate both in speed and performance to approach real-time imaging.
KEYWORDS: Algorithm development, Tomography, Reconstruction algorithms, Signal processing, Switching, Surgery, Signal to noise ratio, Neurological disorders, Multiplexers, Medical devices
Electrical impedance tomography (EIT) is a rising and emerging imaging technique with great potential in many areas, especially in functional brain imaging applications. An EIT system with high speed and accuracy can have many applications to medical devices supporting in diagnosis and treatment of neurological disorders and diseases. In this research, EIT algorithms and hardware are developed and improved to increase reconstructed images' accuracy and decrease the reconstruction time. Due to multiplexer design limitations, EIT measurements are subject to strong capacitive effects from charging and discharging in switching cycles around 300 to 400 samples per 1280 samples (in 10 milliseconds sampling). We developed an algorithm to choose data in steady-state condition only selectively. This method improves the signal-to-noise ratio and results in better reconstruction images. An algorithm to effectively synchronize the beginning points of data was developed to increase the system's speed. This presentation also presents the EIT system's hardware architecture based on Texas Instruments Fixed-Point Digital Signal Processor - TMS320VC5509A, which is low-cost, high potential in popularity the community in the future. For high operation speed, we propose the EIT system used Sitara™ AM57x processors of Texas Instruments.
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