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...
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Tehran University of Medical Sciences
2025-07-01
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| Series: | Frontiers in Biomedical Technologies |
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| Online Access: | https://fbt.tums.ac.ir/index.php/fbt/article/view/772 |
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| author | Pankaj Kumar Sahu Karan Jain |
| author_facet | Pankaj Kumar Sahu Karan Jain |
| author_sort | Pankaj Kumar Sahu |
| collection | DOAJ |
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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 20-fold validation 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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| format | Article |
| id | doaj-art-082f19b8fa88437fb9552450bbbc214f |
| institution | DOAJ |
| issn | 2345-5837 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Tehran University of Medical Sciences |
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| series | Frontiers in Biomedical Technologies |
| spelling | doaj-art-082f19b8fa88437fb9552450bbbc214f2025-08-20T02:58:34ZengTehran University of Medical SciencesFrontiers in Biomedical Technologies2345-58372025-07-0112310.18502/fbt.v12i3.19175Frontal Medial Theta-Based Intelligence System for Verifying Mild Traumatic Brain InjuryPankaj Kumar Sahu0Karan Jain1Dr BR Ambedkar National Institute of Technology Jalandhar, Punjab, India. 144011.Department of Instrumentation and Control Engineering, Dr. B. R. Ambedkar National Institute of Technology Jalandhar, Punjab, India 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 20-fold validation 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. https://fbt.tums.ac.ir/index.php/fbt/article/view/772Multi-Level Discrete Wavelet TransformationFrontal-Medial ThetaFrontal-Medial CortexSupplementary Motor AreaMedial-Sensory Motor CortexMild Traumatic Brain Injury |
| spellingShingle | Pankaj Kumar Sahu Karan Jain Frontal Medial Theta-Based Intelligence System for Verifying Mild Traumatic Brain Injury Frontiers in Biomedical Technologies Multi-Level Discrete Wavelet Transformation Frontal-Medial Theta Frontal-Medial Cortex Supplementary Motor Area Medial-Sensory Motor Cortex Mild Traumatic Brain Injury |
| title | Frontal Medial Theta-Based Intelligence System for Verifying Mild Traumatic Brain Injury |
| title_full | Frontal Medial Theta-Based Intelligence System for Verifying Mild Traumatic Brain Injury |
| title_fullStr | Frontal Medial Theta-Based Intelligence System for Verifying Mild Traumatic Brain Injury |
| title_full_unstemmed | Frontal Medial Theta-Based Intelligence System for Verifying Mild Traumatic Brain Injury |
| title_short | Frontal Medial Theta-Based Intelligence System for Verifying Mild Traumatic Brain Injury |
| title_sort | frontal medial theta based intelligence system for verifying mild traumatic brain injury |
| topic | Multi-Level Discrete Wavelet Transformation Frontal-Medial Theta Frontal-Medial Cortex Supplementary Motor Area Medial-Sensory Motor Cortex Mild Traumatic Brain Injury |
| url | https://fbt.tums.ac.ir/index.php/fbt/article/view/772 |
| work_keys_str_mv | AT pankajkumarsahu frontalmedialthetabasedintelligencesystemforverifyingmildtraumaticbraininjury AT karanjain frontalmedialthetabasedintelligencesystemforverifyingmildtraumaticbraininjury |