Publication Date


Document Type


Committee Members

Ulas Sunar, Ph.D. (Advisor); Keiichiro Susuki, Ph.D. (Committee Member); Tarun Goswami, Ph.D. (Committee Member)

Degree Name

Master of Science in Biomedical Engineering (MSBME)


Neurovascular coupling is an important concept that indicates the direct link between neuronal electrical firing with the vascular hemodynamic changes. Functional Near Infrared Spectroscopy (fNIRS) can measure changes in cerebral vascular parameters of oxy-hemoglobin and deoxyhemoglobin concentrations and thus can provide neuronal activity through neurovascular coupling. Currently many commercial fNIRS devices are available, but they are limited by the number of channels (usually having only 8 detectors), which can limit the sensitivity, contrast, and resolution of imaging. High-density imaging can improve sensitivity, contrast, and resolution by providing many measurements and averaging the signals originating from the target cerebral focus area compared to background tissue. Here a multi-channel, low-cost, high-density imaging system based on scientific CMOS (Complementary Metal-Oxide-Semiconductor) detector will be presented. The CMOS camera is fiber-coupled such that on one end fibers are focused on the pixels on the CMOS camera, which allows individual pixels (or binned sub-pixels) to act as detectors, while the other end of the fibers can be positioned on a wearable optical probe. After the device details, I will show the device validation using a series of the dynamic flow phantom experiments mimicking the brain activation and finally human motor cortex experiments (finger tapping experiments). The results demonstrate that this system can obtain high-density data sets with higher contrast and resolution. This wearable, high-density optical neuroimaging technology is expected to find many applications including pediatric neuroimaging at clinics and assessing human cognitive performance.

Page Count


Department or Program

Department of Biomedical, Industrial & Human Factors Engineering

Year Degree Awarded


Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.