From Group-Level Statistics to Single-Subject Prediction: Machine Learning Detection of Concussion in Retired Athletes-Reference-Cited by-同舟云学术

From Group-Level Statistics to Single-Subject Prediction: Machine Learning Detection of Concussion in Retired Athletes

Published:2019-07 Issue:7 Volume:27 Page:1492-1501
ISSN:1534-4320
Container-title:IEEE Transactions on Neural Systems and Rehabilitation Engineering
language:
Short-container-title:IEEE Trans. Neural Syst. Rehabil. Eng.

Author:

Boshra Rober^ORCID,Dhindsa Kiret^ORCID,Boursalie Omar^ORCID,Ruiter Kyle I.,Sonnadara Ranil^ORCID,Samavi Reza^ORCID,Doyle Thomas E.^ORCID,Reilly James P.^ORCID,Connolly John F.^ORCID

Funder

Canada Foundation for Innovation

Senator WilliamMcMaster Chair in Cognitive Neuroscience of Language

Natural Sciences and Engineering Research Council of Canada

Southern Ontario Smart Computing Innovation Platform

Ontario Ministry of Research and Innovation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation

Link

http://xplorestaging.ieee.org/ielx7/7333/8755894/08735773.pdf?arnumber=8735773

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1. Detecting mild traumatic brain injury for athletes using SSVEP classification: A case study;Biomedical Signal Processing and Control;2023-09

2. Years of play alter MRI measures of brain health in former Canadian Football League athletes: a pilot study;Journal of Concussion;2023-01

3. M3CV: A multi-subject, multi-session, and multi-task database for EEG-based biometrics challenge;NeuroImage;2022-12

4. M³CV:A Multi-subject, Multi-session, and Multi-task database for EEG-based Biometrics Challenge;2022-07-03

5. Towards defining biomarkers to evaluate concussions using virtual reality and a moving platform (BioVRSea);Scientific Reports;2022-05-30