Dr. Kunal M. Mankodiya Profile

Dr. Kunal M. Mankodiya

Assistant Professor at Univ of Rhode Island

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Proceedings Article | 1 March 2019 Paper

A point-of-care handheld region-of-interest (ROI) 3D functional diffuse optical tomography (fDOT) system

Manob Jyoti Saikia, Kunal Mankodiya, Rajan Kanhirodan

Proceedings Volume 10874, 108742J (2019) https://doi.org/10.1117/12.2510926

KEYWORDS: Tissue optics, Sensors, Tissues, Image restoration, 3D image processing, Imaging systems, Control systems, Diffuse optical tomography, Near infrared, Embedded systems

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Functional Diffuse Optical Tomography (fDOT) has the potential to provide the functional status of tissue by mapping 3D distribution of chromophores concentration in deep tissue non-inversely. Region-of-Interest (ROI) DOT, we presented earlier, uses optical patch using only a few NIR light sources and detectors arranged in a circular pattern for the depth-sensitive 3D DOT imaging of the tissue at a high-speed. However, ROI DOT system is not portable enough to carry with and to operate in an unconstrained setting. In this work, we have developed a handheld ROI fDOT system that allows functional imaging of tissue wirelessly. We have proposed a new embedded system architecture based on the Internet-of-things (IoT) concept. Our low-level embedded system and analog circuit design, and embedded computing algorithm also capable of source modulation, lock-in detection, onboard calibration and basic signal processing for the continuous wave (cw) DOT measurement at a high speed while reducing the overall form factor of the system. The optical probe has two sets of source and detector, each contains four triple-wavelengths NIR LEDs and four silicon-photodiode detectors arranged at two different source-detector separations. The handheld system sends measured data to a server wirelessly in real-time. The server performs high-speed GPU-based ROI 3D fDOT image reconstruction and displays result at 3 frames-per-second. The image reconstruction algorithm solves the diffusion equation using the finite element method and utilizes two depth sensitive measurement sets. The experimental results of regional tissue imaging on eight participants have proven the working of the system.

Proceedings Article | 27 February 2019 Paper

3D-printed human-centered design of fNIRS optode for the portable neuroimaging

Manob Jyoti Saikia, Kunal Mankodiya

Proceedings Volume 10870, 108700Z (2019) https://doi.org/10.1117/12.2510955

KEYWORDS: Computer aided design, 3D printing, Sensors, Neuroimaging, Brain, Light emitting diodes, Electrodes, Signal processing, Signal to noise ratio, Photodiodes

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Functional Near-infrared Spectroscopy (fNIRS) is an optical brain imaging technology based on mapping blood oxygenation levels on the cortical surface of the brain. fNIRS has the potential to become a point-of-care brain monitoring system for localized brain measurements in various medical conditions including brain injury and concussion. Although fNIRS electronic circuit has been miniaturized significantly, one of the least elucidated elements of the portable fNIRS systems is the process for developing optodes (light sources and detectors) for the improvements in skin-optode coupling, signal-to-noise ratio (SNR), user’s comfort-level and motion artifact reduction. We have used modern design tools such as 3D printing and laser cutting to fabricate human-centered fNIRS optodes. Feedback was taken from participants of different groups throughout the iterative design process of data collection. Two types of fNIRS optodes were designed; one was based on forehead patch and the other was integrable into an electrode head cap. The optodes were connected to our developed portable fNIRS hardware. The noise characteristics of the optodes for the long-term brain imaging settings, while subjects were performing physical activities, was systemically studied in each of the iterations and designs. The final front-end hardware design was tested on eight subjects with varying head size, shape and skin tone. Experimental results of SNR and resistance to the motion artifacts show that 3D printing can be effective for the development of fNIRS optode. These fNIRS optodes prove to not only be easy to use and comfortable but also capable of acquiring the fNIRS signal with other brain monitoring modalities such as electroencephalography (EEG).

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