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
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.