{"title":"Real-Time Display of Dense Neuronal Activation Map Using Functional Near-Infrared Spectroscopy","authors":"M. A. Yaqub, U. Ghafoor, K. Hong","doi":"10.1109/ICRAI47710.2019.8967394","DOIUrl":null,"url":null,"abstract":"The risk of getting psychiatric disease or various kinds of dementia is rising as a significant problem in the aging society. Functional near-infrared spectroscopy (fNIRS) can measure the blood chromophores noninvasively for early diagnosis, and frequent examination, which are vital in case of brain degeneration. We present the development and functioning of our lab-developed fNIRS system. It provides a real-time display of variation in blood chromophores related to neuronal activation. It employs 128 dual-wavelength LEDs of 735 nm and 850 nm. The selection of these wavelengths allows computation of oxyhemoglobin (HbO) and deoxyhemoglobin (HbR). A single photosensor is used in the presented device. This system is developed using a modular approach where a single module can cover approximately 7 cm x 7 cm while multiple modules can be used to cover a wider area. The current configuration utilizes different source-detector separation to reach multiple depths between 2 cm and 3.5 cm. Short separation channels also exist in the design to provide the information of superficial layers. MOSFET based LED switching is implemented that allows sharp current switching for high-speed data acquisition. Windows-based software is developed for the display of fNIRS data in real time. Wi-Fi is used as the wireless medium of communication between the hardware and software. Phantom model, as well as human subject, was used for testing the device efficacy. The phantom results showed that by increasing the channel-separation, the signal intensity was reduced. Resting state human subject was also evaluated to compute and display the HbO in real time. A complete fNIRS sample comprising of 128 channels was recorded in 25 ms.","PeriodicalId":429384,"journal":{"name":"2019 International Conference on Robotics and Automation in Industry (ICRAI)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Robotics and Automation in Industry (ICRAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRAI47710.2019.8967394","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The risk of getting psychiatric disease or various kinds of dementia is rising as a significant problem in the aging society. Functional near-infrared spectroscopy (fNIRS) can measure the blood chromophores noninvasively for early diagnosis, and frequent examination, which are vital in case of brain degeneration. We present the development and functioning of our lab-developed fNIRS system. It provides a real-time display of variation in blood chromophores related to neuronal activation. It employs 128 dual-wavelength LEDs of 735 nm and 850 nm. The selection of these wavelengths allows computation of oxyhemoglobin (HbO) and deoxyhemoglobin (HbR). A single photosensor is used in the presented device. This system is developed using a modular approach where a single module can cover approximately 7 cm x 7 cm while multiple modules can be used to cover a wider area. The current configuration utilizes different source-detector separation to reach multiple depths between 2 cm and 3.5 cm. Short separation channels also exist in the design to provide the information of superficial layers. MOSFET based LED switching is implemented that allows sharp current switching for high-speed data acquisition. Windows-based software is developed for the display of fNIRS data in real time. Wi-Fi is used as the wireless medium of communication between the hardware and software. Phantom model, as well as human subject, was used for testing the device efficacy. The phantom results showed that by increasing the channel-separation, the signal intensity was reduced. Resting state human subject was also evaluated to compute and display the HbO in real time. A complete fNIRS sample comprising of 128 channels was recorded in 25 ms.