Review of wearable technologies and machine learning methodologies for systematic detection of mild traumatic brain injuries.

diagnostics machine learning mild traumatic brain injury multimodal data physiological biomarkers signal processing wearable technologies

Journal

Journal of neural engineering
ISSN: 1741-2552
Titre abrégé: J Neural Eng
Pays: England
ID NLM: 101217933

Informations de publication

Date de publication:
19 08 2021
Historique:
received: 01 04 2021
accepted: 30 07 2021
pubmed: 31 7 2021
medline: 16 9 2021
entrez: 30 7 2021
Statut: epublish

Résumé

Mild traumatic brain injuries (mTBIs) are the most common type of brain injury. Timely diagnosis of mTBI is crucial in making 'go/no-go' decision in order to prevent repeated injury, avoid strenuous activities which may prolong recovery, and assure capabilities of high-level performance of the subject. If undiagnosed, mTBI may lead to various short- and long-term abnormalities, which include, but are not limited to impaired cognitive function, fatigue, depression, irritability, and headaches. Existing screening and diagnostic tools to detect acute and

Identifiants

pubmed: 34330120
doi: 10.1088/1741-2552/ac1982
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Creative Commons Attribution license.

Auteurs

William Schmid (W)

Department of Electrical and Computer Engineering and Neuroengineering Initiative (NEI), Rice University, Houston, TX 77005, United States of America.

Yingying Fan (Y)

Department of Electrical and Computer Engineering and Neuroengineering Initiative (NEI), Rice University, Houston, TX 77005, United States of America.

Taiyun Chi (T)

Department of Electrical and Computer Engineering and Neuroengineering Initiative (NEI), Rice University, Houston, TX 77005, United States of America.

Eugene Golanov (E)

Department of Neurosurgery, Houston Methodist Hospital, Houston, TX 77030, United States of America.

Angelique S Regnier-Golanov (AS)

Department of Neurosurgery, Houston Methodist Hospital, Houston, TX 77030, United States of America.

Ryan J Austerman (RJ)

Department of Neurosurgery, Houston Methodist Hospital, Houston, TX 77030, United States of America.

Kenneth Podell (K)

Department of Neurology, Houston Methodist Hospital, Houston, TX 77030, United States of America.

Paul Cherukuri (P)

Institute of Biosciences and Bioengineering (IBB), Rice University, Houston, TX 77005, United States of America.

Timothy Bentley (T)

Office of Naval Research, Arlington, VA 22203, United States of America.

Christopher T Steele (CT)

Military Operational Medicine Research Program, US Army Medical Research and Development Command, Fort Detrick, MD 21702, United States of America.

Sarah Schodrof (S)

Department of Athletics-Sports Medicine, Rice University, Houston, TX 77005, United States of America.

Behnaam Aazhang (B)

Department of Electrical and Computer Engineering and Neuroengineering Initiative (NEI), Rice University, Houston, TX 77005, United States of America.

Gavin W Britz (GW)

Department of Neurosurgery, Houston Methodist Hospital, Houston, TX 77030, United States of America.

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Classifications MeSH