Investigation of attention deficit hyperactivity disorder (ADHD) sub-types in children via EEG frequency domain
Ramazan Aldemir1, Esra Demirci2, Huseyin Per3
1a Department of Biomedical Device Technologies , Kayseri Vocational College, Erciyes University , Kayseri , Turkey.
Insights
Electroencephalography (EEG) analysis reveals distinct frequency domain changes in children with attention deficit hyperactivity disorder (ADHD). These EEG patterns can help differentiate ADHD subtypes, offering a potential diagnostic tool.
Area of Science:
- Neuroscience
- Pediatric Neurology
- Biomedical Engineering
Background:
- Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder.
- Understanding the neurophysiological underpinnings of ADHD, particularly in children, is crucial for effective diagnosis and management.
- Electroencephalography (EEG) offers a non-invasive method to study brain activity.
Purpose of the Study:
- To investigate alterations in the frequency domain of EEG signals in children diagnosed with ADHD.
- To compare EEG spectral characteristics between ADHD patients (overall and by subtype) and typically developing controls.
- To explore the potential of EEG analysis as a diagnostic aid for ADHD subtypes.
Main Methods:
- The study included 40 children aged 7-12 years, divided into ADHD (n=20), ADHD-Inattentive (ADHD-I, n=10), ADHD-Combined (ADHD-C, n=10), and control (n=20) groups.
- EEG data was analyzed in the frequency domain using Matlab software.
- Spectral analysis focused on mean power and relative-mean power in delta, theta, alpha, and beta frequency bands.
Main Results:
- Children with ADHD and its subtypes (ADHD-I, ADHD-C) exhibited higher mean power in the delta and theta frequency bands compared to controls.
- No significant differences in alpha and beta band power were observed between ADHD groups and controls.
- Significant increases in the delta/beta ratio were found between ADHD-I and control groups.
- Statistical significance in delta/beta and theta/delta ratios was observed between ADHD-C and control groups.
Conclusions:
- EEG spectral analysis demonstrates quantifiable differences in brain activity patterns associated with ADHD.
- Specific EEG frequency band alterations and ratios show potential for distinguishing between ADHD subtypes.
- EEG analysis may serve as a valuable complementary method for identifying and differentiating ADHD subgroups.
Aim Of The Study:
To investigate the frequency domain effects and changes in electroencephalography (EEG) signals in children diagnosed with attention deficit hyperactivity disorder (ADHD).
Patients And Methods:
The study contains 40 children. All children were between the ages of 7 and 12 years. Participants were classified into four groups which were ADHD (n=20), ADHD-I (ADHD-Inattentive type) (n=10), ADHD-C (ADHD-Combined type) (n=10), and control (n=20) groups. In this study, the frequency domain of EEG signals for ADHD, subtypes and control groups were analyzed and compared using Matlab software. The mean age of the ADHD children's group was 8.7 years and the control group 9.1 years.
Results:
Spectral analysis of mean power (μV2) and relative-mean power (%) was carried out for four different frequency bands: delta (0--4 Hz), theta (4--8 Hz), alpha (8--13 Hz) and beta (13--32 Hz). The ADHD and subtypes of ADHD-I, and ADHD-C groups had higher average power value of delta and theta band than that of control group. However, this is not the case for alpha and beta bands. Increases in delta/beta ratio and statistical significance were found only between ADHD-I and control group, and in delta/beta, theta/delta ratio statistical significance values were found to exist between ADHD-C and control group.
Conclusion:
EEG analyzes can be used as an alternative method when ADHD subgroups are identified.
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