Neurophysiological Marker of ADHD in Children

Neurophysiological Marker of Attention Deficit Hyperactivity Disorder in Children

This study investigated quantitative electroencephalography (QEEG) subtypes as auxiliary tools to assess Attention Deficit Hyperactivity Disorder (ADHD). Patient assessed using the Korean version of the Diagnostic Interview Schedule for Children Version IV and were assigned to one of three groups: ADHD, ADHD-Not Otherwise specified (NOS), and Neurotypical (NT). The investigators measure absolute and relative EEG power in 19 channels and conducted an auditory continuous performance test. The investigators analyzed QEEG according to the frequency range: delta (1-4 Hz), theta (4-8 Hz), slow alpha (8-10 Hz), fast alpha (10-13.5 Hz), and beta (13.5-30 Hz). The subjects were then grouped by Ward's method of cluster analysis using the squared Euclidian distance to measure dissimilarities.

Study Overview

• Status: Completed
• Conditions: Attention Deficit Hyperactivity Disorder; Psychiatric Diagnosis; Diagnosis, Psychiatric
• Intervention / Treatment: Diagnostic test: electroencephalography absolute delta power; Diagnostic test: electroencephalography relative delta power; Diagnostic test: electroencephalography absolute theta power; Diagnostic test: electroencephalography relative theta power; Diagnostic test: electroencephalography absolute slow alpha power; Diagnostic test: electroencephalography relative slow alpha power; Diagnostic test: electroencephalography absolute fast alpha power; Diagnostic test: electroencephalography relative fast alpha power; Diagnostic test: electroencephalography absolute beta power; Diagnostic test: electroencephalography relative beta power; Diagnostic test: Korean ADHD rating scale; Diagnostic test: Korean Version of Diagnostic Interview Schedule for Children Version IV

Detailed Description

Participants between 7 and 12 years of age diagnosed with ADHD according to the DSM-5 criteria were included in the study. The ADHD diagnosis was based on a Korean version of the Diagnostic Interview Schedule for Children Version IV (DISC-IV), which is a structured interview tool, and these diagnoses were confirmed by multiple child and adolescent psychiatrists. If participants did not meet the ADHD diagnostic criteria of DSM-IV and DISC-IV, they were assigned to the Neurotypical (NT) group. Based on the results of the DISC-IV test, participants were assigned to the ADHD or Non-Other Specified (NOS) group. Patients who met the diagnostic criteria of ADHD in DSM-IV, but whose score did not exceed six, and had a score of more than three in the attention deficit or hyperactivity/impactivity scale of DISC-IV were included in the NOS group. Children with a history of brain damage, neurological disorders, genetic disorders, substance dependence, epilepsy, or any other mental disorder were excluded from participation. Children with an IQ of 70 or lower according to the Korean-Wechsler Intelligence Scale for Children (Fourth Edition) or who were receiving drug treatment were also excluded from this study. The EEG recordings were performed using a SynAmps2 direct-current (DC) amplifier and a 10-20 layout 64-channel Quick-Cap electrode-placement system (Neuroscan Inc., NC, USA). The EEG data were digitally recorded from 19 gold cup electrodes placed according to the international 10-20 system. The impedances were maintained below 5 kΩ, and the sampling rate was 1000 Hz. The investigators use the linked mastoid reference and two additional bipolar electrodes to measure horizontal and vertical eye movements. During the recording, each participant laid in a dimly lit, electrically shielded, sound-attenuated room. Resting EEG recordings were recorded after three minutes with the participants' eyes closed.

• Study Type: Observational
• Enrollment (Actual): 140

Contacts and Locations

• Study Contact: Name: Jun Won Kim, M.D. Ph.D.; Phone Number: +82-53-630-4780; Email: f_affection@naver.com

Study Locations

• Korea, Republic of
  • Nam-gu
    • Daegu, Nam-gu, Korea, Republic of, 42471
      • Daegu Catholic University Medical Center

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 5 years to 10 years (Child)
• Accepts Healthy Volunteers: Yes

• Sampling Method: Probability Sample

Study Population

Patients who suspected attention-deficit/hyperactivity disorder conducted QEEG and diagnosed with DISC-IV

Description

Inclusion Criteria:

• Participants between 7 and 12 years of age diagnosed with ADHD according to the DSM-5 criteria were included in the study

Exclusion Criteria:

• Children with a history of brain damage, neurological disorders, genetic disorders, substance dependence, epilepsy, or any other mental disorder were excluded from participation.
• Children with an IQ of 70 or lower according to the Korean-Wechsler Intelligence Scale for Children (Fourth Edition) or who were receiving drug treatment were also excluded from this study

Study Plan

How is the study designed?

Design Details

• Observational Models: Case-Only
• Time Perspectives: Retrospective

Number of groups / cohorts

3

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
ADHD	Diagnostic test: electroencephalography absolute delta power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography relative delta power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography absolute theta power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography relative theta power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography absolute slow alpha power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography relative slow alpha power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography absolute fast alpha power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography relative fast alpha power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography absolute beta power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography relative beta power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: Korean ADHD rating scale; The KARS is a standardized screening tool for ADHD in Korean children and rating scale completed by the parents.; Diagnostic test: Korean Version of Diagnostic Interview Schedule for Children Version IV; The DISC-IV is a structured diagnostic tool that was developed for use in epidemiological studies in children and adolescents
NT NeuroTypical	Diagnostic test: electroencephalography absolute delta power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography relative delta power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography absolute theta power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography relative theta power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography absolute slow alpha power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography relative slow alpha power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography absolute fast alpha power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography relative fast alpha power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography absolute beta power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography relative beta power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: Korean ADHD rating scale; The KARS is a standardized screening tool for ADHD in Korean children and rating scale completed by the parents.; Diagnostic test: Korean Version of Diagnostic Interview Schedule for Children Version IV; The DISC-IV is a structured diagnostic tool that was developed for use in epidemiological studies in children and adolescents
ADHD NOS	Diagnostic test: electroencephalography absolute delta power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography relative delta power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography absolute theta power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography relative theta power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography absolute slow alpha power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography relative slow alpha power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography absolute fast alpha power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography relative fast alpha power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography absolute beta power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: electroencephalography relative beta power; We used MATLAB 7.0.1 (Math Works, Natick, MA, USA) and the EEGLAB toolbox to pre-process and analyze the EEG recordings. First, the EEG data were down-sampled to 250 Hz. Next, the EEG data were detrended and mean-subtracted to remove the DC component. A 1-Hz high-pass filter and a 60-Hz notch filter were applied to remove eye and electrical noise. Next, independent component analysis (ICA) was performed to remove the well-defined sources of artifacts. ICA has been shown to reliably isolate artifacts caused by eye and muscle movements and heart noise (23). Finally, clinical psychiatrists and EEG experts visually inspected the corrected EEGs. For the analysis, we selected more than two minutes of artifact-free EEG readings from the three-minute recordings; Diagnostic test: Korean ADHD rating scale; The KARS is a standardized screening tool for ADHD in Korean children and rating scale completed by the parents.; Diagnostic test: Korean Version of Diagnostic Interview Schedule for Children Version IV; The DISC-IV is a structured diagnostic tool that was developed for use in epidemiological studies in children and adolescents

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
QEEG topographical plots of the results of the statistical comparisons to normative values (z-scores) using Neuroguide software	The investigators measures QEEG on first outpatient clinic and conduct topography for mapping	through study completion, an average of 1 year

Collaborators and Investigators

• Sponsor: Daegu Catholic University Medical Center

Study record dates

Study Major Dates

• Study Start (Actual): August 8, 2018
• Primary Completion (Actual): February 28, 2021
• Study Completion (Actual): February 28, 2021

Study Registration Dates

• First Submitted: July 1, 2020
• First Submitted That Met QC Criteria: July 8, 2020
• First Posted (Actual): July 13, 2020

Study Record Updates

• Last Update Posted (Actual): February 20, 2024
• Last Update Submitted That Met QC Criteria: February 16, 2024
• Last Verified: February 1, 2024

More Information

Terms related to this study

• Keywords: ADHD; QEEG; Neurotypical
• Additional Relevant MeSH Terms: Pathologic Processes; Nervous System Diseases; Neurologic Manifestations; Dyskinesias; Attention Deficit and Disruptive Behavior Disorders; Neurodevelopmental Disorders; Disease; Mental Disorders; Attention Deficit Disorder with Hyperactivity; Hyperkinesis
• Other Study ID Numbers: CR-18-096

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Data will be shared on request for proper reason

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No