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Traumatic Brain Injury (TBI) Detection: Past, Present, and Future

Journal

BIOMEDICINES
Volume 10, Issue 10, Pages -

Publisher

MDPI
DOI: 10.3390/biomedicines10102472

Keywords

traumatic brain injury; neuroimaging; electroencephalography; preprocessing; artifacts removal; detection; artificial intelligence

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Traumatic brain injury (TBI) can result in serious long-term consequences, including Alzheimer's, Parkinson's, or disability. Mild TBI (mTBI) is the most common type, and early detection is crucial for successful treatment. While neuroimaging-based tests provide structural and functional mapping of the brain, they lack temporal resolution and may not detect mTBI. On the other hand, electroencephalogram (EEG) has good spatial and temporal resolution, but currently cannot confidently detect mTBI. This paper aims to review existing approaches and explain the shortcomings of EEG-based mTBI detection.
Traumatic brain injury (TBI) can produce temporary biochemical imbalance due to leaks through cell membranes or disruption of the axoplasmic flow due to the misalignment of intracellular neurofilaments. If untreated, TBI can lead to Alzheimer's, Parkinson's, or total disability. Mild TBI (mTBI) accounts for about about 90 percent of all TBI cases. The detection of TBI as soon as it happens is crucial for successful treatment management. Neuroimaging-based tests provide only a structural and functional mapping of the brain with poor temporal resolution. Such tests may not detect mTBI. On the other hand, the electroencephalogram (EEG) provides good spatial resolution and excellent temporal resolution of the brain activities beside its portability and low cost. The objective of this paper is to provide clinicians and scientists with a one-stop source of information to quickly learn about the different technologies used for TBI detection, their advantages and limitations. Our research led us to conclude that even though EEG-based TBI detection is potentially a powerful technology, it is currently not able to detect the presence of a mTBI with high confidence. The focus of the paper is to review existing approaches and provide the reason for the unsuccessful state of EEG-based detection of mTBI.

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