Frontal Medial Theta-Based Intelligence System for Verifying Mild Traumatic Brain Injury

Purpose: The purpose of this study was to create an Intelligence System (IS) to analyze the Electroencephalogram (EEG) characteristics of patients with mild Traumatic Brain Injury (mTBI) and healthy volunteers. Generally, mTBI research demonstrates that patients suffer from Working Memory (WM). The frontal cortex is involved in the clinical physiology of mTBI and is crucial for delayed memory. Materials and Methods: The Frontal-Medial Theta (FMT) is one of the most critical factors in mTBI verification. The oscillatory strength of FMT (4-8Hz) over the Frontal-Medial Cortex (FMC) or Supplementary Motor Area (SMA) and the medial-Sensory Motor Cortex (mSMC) is associated with efficient WM performance. The designed IS accesses the FMT of mTBI and healthy subjects by FCz and Cz electrodes placed in FMC or SMA and mSMC, respectively. The Multi-level Discrete Wavelet Transformation (MDWT) of EEG (FCz and Cz) is suggested here to investigate the mTBI. The FMT rhythms of EEG of FCz and Cz channels are extracted through 3-level-DWT. Then, 1768 features [712 features of healthy subjects + 1056 features of mTBI patients] for both the FCz and Cz electrodes were calculated via their FMT using eight statistical feature computations. Results: The study found that the FMT strength of FCz and Cz electrodes is similar. The Bagging Classifier achieved 83.3333% accuracy with the 5% split for the FCz electrode. Conclusion: The strength of the FMT-FCz and FMT-Cz electrodes is approximately the same, and both are equally crucial to investigating mild Traumatic Brain Injury.

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Publication Details

Journal
Frontiers in biomedical technologies
Published
2025-07-20
DOI
https://doi.org/10.18502/fbt.v12i3.19175
Citations
1
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.84
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article

Frontal Medial Theta-Based Intelligence System for Verifying Mild Traumatic Brain Injury

Karan Jain, Pankaj Kumar Sahu
1 citations
Frontiers in biomedical technologies
Brain Tumor Detection and Classification
0.84
article

Frontal Medial Theta-Based Intelligence System for Verifying Mild Traumatic Brain Injury

Karan Jain, Pankaj Kumar Sahu
article en
1 citations

Abstract

Purpose: The purpose of this study was to create an Intelligence System (IS) to analyze the Electroencephalogram (EEG) characteristics of patients with mild Traumatic Brain Injury (mTBI) and healthy volunteers. Generally, mTBI research demonstrates that patients suffer from Working Memory (WM). The frontal cortex is involved in the clinical physiology of mTBI and is crucial for delayed memory. Materials and Methods: The Frontal-Medial Theta (FMT) is one of the most critical factors in mTBI verification. The oscillatory strength of FMT (4-8Hz) over the Frontal-Medial Cortex (FMC) or Supplementary Motor Area (SMA) and the medial-Sensory Motor Cortex (mSMC) is associated with efficient WM performance. The designed IS accesses the FMT of mTBI and healthy subjects by FCz and Cz electrodes placed in FMC or SMA and mSMC, respectively. The Multi-level Discrete Wavelet Transformation (MDWT) of EEG (FCz and Cz) is suggested here to investigate the mTBI. The FMT rhythms of EEG of FCz and Cz channels are extracted through 3-level-DWT. Then, 1768 features [712 features of healthy subjects + 1056 features of mTBI patients] for both the FCz and Cz electrodes were calculated via their FMT using eight statistical feature computations. Results: The study found that the FMT strength of FCz and Cz electrodes is similar. The Bagging Classifier achieved 83.3333% accuracy with the 5% split for the FCz electrode. Conclusion: The strength of the FMT-FCz and FMT-Cz electrodes is approximately the same, and both are equally crucial to investigating mild Traumatic Brain Injury.

Frontiers in biomedical technologies
Dr. B. R. Ambedkar National Institute of Technology Jalandhar (IN)
Openalex Percentile: Top 24%
Brain Tumor Detection and Classification
0.84
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Frontal Medial Theta-Based Intelligence System for Verifying Mild Traumatic Brain Injury — Karan Jain, Pankaj Kumar Sahu · Frontiers in biomedical technologies (2025) | TGRS Research Map | TGRS