CRII: SCH: RUI: Development of Hybrid EEG-fNIRS Neuroimaging Headband for Neurofeedback

About This Grant

This project aims to develop a neuroimaging headband for neurofeedback, which will be a non-invasive and drug-free approach to empower individuals for cognitive enhancement and assist clinicians in neurological disease diagnosis and treatment monitoring. The investigator will develop an electronic textile-based headband (sports sweatband-like) combining functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG) methods for brain imaging. Also, a mobile phone application (app) integrated with the headband will be developed for personalized neurofeedback training both at home and in hospital settings. The main challenges addressed here for accurate brain imaging in real-time are focused on developing highly sensitive and reliable hardware as well as advanced data processing algorithms (software) to extract relevant biomarkers for input into artificial intelligence (AI) models. Additionally, ensuring user-friendly phone app interfaces and effective personalized neurofeedback training protocols for users, especially in home-based settings, demands multidisciplinary innovation. This project aims to advance the development of an electronic textile-based headband capable of monitoring multiple biomarkers, such as fNIRS hemodynamic response and EEG along with signals from complementary sensors, while simultaneously conducting cognitive assessments in real-time. This research project will also address a critical limitation--variations in fNIRS signal quality due to skin tone differences. Thus, it will ensure equitable brain healthcare across racial and ethnic groups. By innovating wearable hybrid EEG-fNIRS neuroimaging headband technology and mobile app-based neurofeedback training, this research aims to contribute to early brain disease detection, monitoring, and personalized intervention strategies. This project aims to develop a neuroimaging headband for neurofeedback that will simultaneously monitor critical neural biomarkers, offering high-resolution brain imaging by merging EEG's temporal precision with fNIRS' spatial accuracy. Integration of auxiliary biosensors and head motion tracking using IMU in the headband will enhance biosignal processing algorithms' performance. This project will aim for the following innovations. (1) Electronic Textile-based Hybrid Brain Monitoring: the headband will be designed for user-friendliness and comfort analogous to a sports sweatband. It will integrate textile EEG electrodes using conductive threads and placeholders for fNIRS optodes (LEDs and detectors). (2) Bioinstrumentation: developing high-fidelity electronic circuits, optics, embedded systems and flexible PCB, it will fully integrate multi-channel continuous wave fNIRS, multichannel EEG and auxiliary sensors. (3) Neuro Biomarkers: the headband will enable the concurrent analysis of critical neuro biomarkers, such as changes in various features in oxy- and deoxyhemoglobin, and EEG frequency band power during neurofeedback training and neurocognitive assessments. This will allow the discovery of novel neuro biomarkers. (4) Adaptive fNIRS to Skin Tones: the headband will detect the wearer's skin tone and autonomously adjust the fNIRS hardware and algorithm in computing neural responses. (5) Mobile Phone App: the app will provide an intuitive and interactive platform for real-time personalized neurofeedback training by discovering novel neurocognitive assessment protocols, signal processing algorithms and AI models. Additionally, this project will facilitate STEM education by providing students with opportunities for hands-on learning. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.