PFI:BIC - Unobtrusive Neurotechnology and Immersive Human-Computer Interface for Enhanced Learning
PFI:BIC - Unobtrusive Neurotechnology and Immersive Human-Computer Interface for Enhanced Learning
批准号:
1719130
负责人:
Gert Cauwenberghs
金额:
$100.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-08-01 至 2021-07-31
中文摘要
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英文摘要
The increasing prevalence of learning disorders, attention deficits, and lackluster appetite for reading across all walks of life, and particularly among school-age children, poses severe problems to humanity and, in the long run, burdens social and economic development. This Partnership for Innovation Building Innovation Capacity (PFI:BIC) collaborative project tackles the impending threats to humanity of illiteracy and faltering education heads-on by creating a new smart-service human-computer interface (HCI) neurotechnology platform as a highly effective, user-friendly, and fun-to-use tool aiding learning and stimulating cognitive development at home and in the classroom. The immersive HCI neurotechnology will allow directly measuring progress at the cognitive level and providing real-time feedback to guide the user in learning to read more effectively. The project is highly Science, Technology, Engineering and Mathematics (STEM) intensive both in its activities and in the targeted benefits of the developed technology, which extends directly to learning science and mathematics by probing cognitive performance of children while they solve puzzles. The development of unobtrusive neurotechnology further addresses a critical need for practical integrated and modular brain-computer interface (BCI) solutions in HCI promoting widespread consumer and clinical use in the marketplace. The partnership provides opportunities for students to gain practical experience in innovation in the marketplace through internships with the industrial partners.The central aim is to develop and leverage new HCI technology as a learning coach and personal cognitive development assistant that facilitates learning to read and acquiring other critical skills in cognitive development. The immersive yet unobtrusive HCI technology testbed will comprise a dry-electrode electroencephalography (EEG) BCI, a tablet with touchscreen and integrated camera, and a suite of signal processing algorithms running in the cloud, for monitoring brain and gaze activity in children learning to read, and providing real-time neurofeedback on progress in cognitive performance to promote enhanced learning. The partnership will transition scientific advances of a previous NSF-sponsored UCSD project (NSF EFRI-M3C, ENG-1137279) in studying the distributed dynamics of human motor control, to development of neurofeedback training paradigms for learning enhancement, and to practical deployment on the unobtrusive immersive testbed implemented using Cognionics dry-electrode EEG wireless BCI neurotechnology and Syntrogi real-time cloud-based signal processing software pipelines. The potential for human empowerment by the technology will be demonstrated by evaluating effectiveness in enhancing learning capabilities and cognitive performance in simulated classroom settings and other targeted learning environments.The lead institution for the project is University of California San Diego (UCSD), with investigators from the Institute for Neural Computation and Department of Bioengineering. The industrial partners in the effort are Syntrogi Inc. (dba Qusp, small business, San Diego CA) and Cognionics, Inc. (small business, San Diego, CA). The project also engages broader context partners Drs. Andrea Chiba and Leanne Chukoskie from the UCSD Temporal Dynamics of Learning Center, Dr. Barbara Moss from San Diego State University Department of Psychology, and Dr. Zewelanji N. Serpell from Virginia Commonwealth University Department of Psychology, in the human case studies and the assessment of the developed HCI technology in diverse learning environments.
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DOI:
10.1016/j.neuroimage.2022.118873
发表时间:
2022-01-21
期刊:
NEUROIMAGE
影响因子:
5.7
作者:
[Hsu, Sheng-Hsiou, Lin, Yayu, Makeig, Scott]
通讯作者:
Makeig, Scott
DOI:
10.1109/tcsii.2021.3124253
发表时间:
2021-12-01
期刊:
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
影响因子:
4.4
作者:
[Van, Lan-Da, Tu, You-Cheng, Jung, Tzyy-Ping]
通讯作者:
Jung, Tzyy-Ping
Attention State Classification with In-Ear EEG
通过入耳式脑电图进行注意力状态分类
DOI:
10.1109/biocas49922.2021.9644973
发表时间:
2021
期刊:
Biomedical Circuits and Systems Conference
影响因子:
--
作者:
[Paul, A.]
通讯作者:
Paul, A.
Integrated In-Ear Device for Auditory Health Assessment
用于听觉健康评估的集成入耳式设备
DOI:
10.1109/embc.2019.8856455
发表时间:
2019
期刊:
2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society
影响因子:
--
作者:
[Paul, Akshay, Akinin, Abraham, Lee, Min S., Kleffner, Matthew, Deiss, Stephen R., Cauwenberghs, Gert]
通讯作者:
Cauwenberghs, Gert
DOI:
10.1109/tbme.2018.2868759
发表时间:
2019-04
期刊:
IEEE Transactions on Biomedical Engineering
影响因子:
4.6
作者:
[.. Siddharth-Siddharth-123964367;Aashish N. Patel;T. Jung;T. Sejnowski]
通讯作者:
.. Siddharth-Siddharth-123964367;Aashish N. Patel;T. Jung;T. Sejnowski
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