<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT04467658</url>
  </required_header>
  <id_info>
    <org_study_id>CR-18-096</org_study_id>
    <nct_id>NCT04467658</nct_id>
  </id_info>
  <brief_title>Neurophysiological Marker of ADHD in Children</brief_title>
  <official_title>Neurophysiological Marker of Attention Deficit Hyperactivity Disorder in Children</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Daegu Catholic University Medical Center</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Daegu Catholic University Medical Center</source>
  <oversight_info>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      This study investigated quantitative electroencephalography (QEEG) subtypes as auxiliary&#xD;
      tools to assess Attention Deficit Hyperactivity Disorder (ADHD). Patient assessed using the&#xD;
      Korean version of the Diagnostic Interview Schedule for Children Version IV and were assigned&#xD;
      to one of three groups: ADHD, ADHD-Not Otherwise specified (NOS), and Neurotypical (NT). The&#xD;
      investigators measure absolute and relative EEG power in 19 channels and conducted an&#xD;
      auditory continuous performance test. The investigators analyzed QEEG according to the&#xD;
      frequency range: delta (1-4 Hz), theta (4-8 Hz), slow alpha (8-10 Hz), fast alpha (10-13.5&#xD;
      Hz), and beta (13.5-30 Hz). The subjects were then grouped by Ward's method of cluster&#xD;
      analysis using the squared Euclidian distance to measure dissimilarities.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Participants between 7 and 12 years of age diagnosed with ADHD according to the DSM-5&#xD;
      criteria were included in the study. The ADHD diagnosis was based on a Korean version of the&#xD;
      Diagnostic Interview Schedule for Children Version IV (DISC-IV), which is a structured&#xD;
      interview tool, and these diagnoses were confirmed by multiple child and adolescent&#xD;
      psychiatrists. If participants did not meet the ADHD diagnostic criteria of DSM-IV and&#xD;
      DISC-IV, they were assigned to the Neurotypical (NT) group. Based on the results of the&#xD;
      DISC-IV test, participants were assigned to the ADHD or Non-Other Specified (NOS) group.&#xD;
      Patients who met the diagnostic criteria of ADHD in DSM-IV, but whose score did not exceed&#xD;
      six, and had a score of more than three in the attention deficit or hyperactivity/impactivity&#xD;
      scale of DISC-IV were included in the NOS group. Children with a history of brain damage,&#xD;
      neurological disorders, genetic disorders, substance dependence, epilepsy, or any other&#xD;
      mental disorder were excluded from participation. Children with an IQ of 70 or lower&#xD;
      according to the Korean-Wechsler Intelligence Scale for Children (Fourth Edition) or who were&#xD;
      receiving drug treatment were also excluded from this study. The EEG recordings were&#xD;
      performed using a SynAmps2 direct-current (DC) amplifier and a 10-20 layout 64-channel&#xD;
      Quick-Cap electrode-placement system (Neuroscan Inc., NC, USA). The EEG data were digitally&#xD;
      recorded from 19 gold cup electrodes placed according to the international 10-20 system. The&#xD;
      impedances were maintained below 5 kΩ, and the sampling rate was 1000 Hz. The investigators&#xD;
      use the linked mastoid reference and two additional bipolar electrodes to measure horizontal&#xD;
      and vertical eye movements. During the recording, each participant laid in a dimly lit,&#xD;
      electrically shielded, sound-attenuated room. Resting EEG recordings were recorded after&#xD;
      three minutes with the participants' eyes closed.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Recruiting</last_known_status>
  <start_date type="Actual">August 8, 2018</start_date>
  <completion_date type="Anticipated">February 28, 2021</completion_date>
  <primary_completion_date type="Anticipated">February 28, 2021</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Case-Only</observational_model>
    <time_perspective>Retrospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>QEEG topographical plots of the results of the statistical comparisons to normative values (z-scores) using Neuroguide software</measure>
    <time_frame>through study completion, an average of 1 year</time_frame>
    <description>The investigators measures QEEG on first outpatient clinic and conduct topography for mapping</description>
  </primary_outcome>
  <number_of_groups>3</number_of_groups>
  <enrollment type="Anticipated">140</enrollment>
  <condition>Attention Deficit Hyperactivity Disorder</condition>
  <condition>Psychiatric Diagnosis</condition>
  <condition>Diagnosis, Psychiatric</condition>
  <arm_group>
    <arm_group_label>ADHD</arm_group_label>
  </arm_group>
  <arm_group>
    <arm_group_label>NT NeuroTypical</arm_group_label>
  </arm_group>
  <arm_group>
    <arm_group_label>ADHD NOS</arm_group_label>
  </arm_group>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>electroencephalography absolute delta power</intervention_name>
    <description>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</description>
    <arm_group_label>ADHD</arm_group_label>
    <arm_group_label>ADHD NOS</arm_group_label>
    <arm_group_label>NT NeuroTypical</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>electroencephalography relative delta power</intervention_name>
    <description>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</description>
    <arm_group_label>ADHD</arm_group_label>
    <arm_group_label>ADHD NOS</arm_group_label>
    <arm_group_label>NT NeuroTypical</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>electroencephalography absolute theta power</intervention_name>
    <description>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</description>
    <arm_group_label>ADHD</arm_group_label>
    <arm_group_label>ADHD NOS</arm_group_label>
    <arm_group_label>NT NeuroTypical</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>electroencephalography relative theta power</intervention_name>
    <description>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</description>
    <arm_group_label>ADHD</arm_group_label>
    <arm_group_label>ADHD NOS</arm_group_label>
    <arm_group_label>NT NeuroTypical</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>electroencephalography absolute slow alpha power</intervention_name>
    <description>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</description>
    <arm_group_label>ADHD</arm_group_label>
    <arm_group_label>ADHD NOS</arm_group_label>
    <arm_group_label>NT NeuroTypical</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>electroencephalography relative slow alpha power</intervention_name>
    <description>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</description>
    <arm_group_label>ADHD</arm_group_label>
    <arm_group_label>ADHD NOS</arm_group_label>
    <arm_group_label>NT NeuroTypical</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>electroencephalography absolute fast alpha power</intervention_name>
    <description>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</description>
    <arm_group_label>ADHD</arm_group_label>
    <arm_group_label>ADHD NOS</arm_group_label>
    <arm_group_label>NT NeuroTypical</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>electroencephalography relative fast alpha power</intervention_name>
    <description>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</description>
    <arm_group_label>ADHD</arm_group_label>
    <arm_group_label>ADHD NOS</arm_group_label>
    <arm_group_label>NT NeuroTypical</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>electroencephalography absolute beta power</intervention_name>
    <description>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</description>
    <arm_group_label>ADHD</arm_group_label>
    <arm_group_label>ADHD NOS</arm_group_label>
    <arm_group_label>NT NeuroTypical</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>electroencephalography relative beta power</intervention_name>
    <description>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</description>
    <arm_group_label>ADHD</arm_group_label>
    <arm_group_label>ADHD NOS</arm_group_label>
    <arm_group_label>NT NeuroTypical</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>Korean ADHD rating scale</intervention_name>
    <description>The KARS is a standardized screening tool for ADHD in Korean children and rating scale completed by the parents.</description>
    <arm_group_label>ADHD</arm_group_label>
    <arm_group_label>ADHD NOS</arm_group_label>
    <arm_group_label>NT NeuroTypical</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>Korean Version of Diagnostic Interview Schedule for Children Version IV</intervention_name>
    <description>The DISC-IV is a structured diagnostic tool that was developed for use in epidemiological studies in children and adolescents</description>
    <arm_group_label>ADHD</arm_group_label>
    <arm_group_label>ADHD NOS</arm_group_label>
    <arm_group_label>NT NeuroTypical</arm_group_label>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        Patients who suspected attention-deficit/hyperactivity disorder conducted QEEG and&#xD;
        diagnosed with DISC-IV&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Participants between 7 and 12 years of age diagnosed with ADHD according to the DSM-5&#xD;
             criteria were included in the study&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Children with a history of brain damage, neurological disorders, genetic disorders,&#xD;
             substance dependence, epilepsy, or any other mental disorder were excluded from&#xD;
             participation.&#xD;
&#xD;
          -  Children with an IQ of 70 or lower according to the Korean-Wechsler Intelligence Scale&#xD;
             for Children (Fourth Edition) or who were receiving drug treatment were also excluded&#xD;
             from this study&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>7 Years</minimum_age>
    <maximum_age>12 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_contact>
    <last_name>Jun Won Kim, M.D. Ph.D.</last_name>
    <phone>+82-53-630-4780</phone>
    <email>f_affection@naver.com</email>
  </overall_contact>
  <location>
    <facility>
      <name>Daegu Catholic University Medical Center</name>
      <address>
        <city>Daegu</city>
        <state>Nam-gu</state>
        <zip>42471</zip>
        <country>Korea, Republic of</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Jun Won Kim, M.D. Ph.D.</last_name>
    </contact>
  </location>
  <location_countries>
    <country>Korea, Republic of</country>
  </location_countries>
  <verification_date>July 2020</verification_date>
  <study_first_submitted>July 1, 2020</study_first_submitted>
  <study_first_submitted_qc>July 8, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">July 13, 2020</study_first_posted>
  <last_update_submitted>July 8, 2020</last_update_submitted>
  <last_update_submitted_qc>July 8, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">July 13, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Daegu Catholic University Medical Center</investigator_affiliation>
    <investigator_full_name>Junwon Kim</investigator_full_name>
    <investigator_title>Clinical professor</investigator_title>
  </responsible_party>
  <keyword>ADHD</keyword>
  <keyword>QEEG</keyword>
  <keyword>Neurotypical</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Hyperkinesis</mesh_term>
    <mesh_term>Disease</mesh_term>
    <mesh_term>Attention Deficit Disorder with Hyperactivity</mesh_term>
    <mesh_term>Mental Disorders</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
    <ipd_description>Data will be shared on request for proper reason</ipd_description>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT04467658
org study id: CR-18-096
nct id: NCT04467658
lead sponsor: 
is fda regulated drug: No
is fda regulated device: No
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.
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.
observational model: Case-Only
time perspective: Retrospective
measure: QEEG topographical plots of the results of the statistical comparisons to normative values (z-scores) using Neuroguide software
time frame: through study completion, an average of 1 year
description: The investigators measures QEEG on first outpatient clinic and conduct topography for mapping
arm group label: ADHD
arm group label: NT NeuroTypical
arm group label: ADHD NOS
intervention type: Diagnostic Test
intervention name: electroencephalography absolute delta power
description: 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
arm group label: ADHD
arm group label: ADHD NOS
arm group label: NT NeuroTypical
intervention type: Diagnostic Test
intervention name: electroencephalography relative delta power
description: 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
arm group label: ADHD
arm group label: ADHD NOS
arm group label: NT NeuroTypical
intervention type: Diagnostic Test
intervention name: electroencephalography absolute theta power
description: 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
arm group label: ADHD
arm group label: ADHD NOS
arm group label: NT NeuroTypical
intervention type: Diagnostic Test
intervention name: electroencephalography relative theta power
description: 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
arm group label: ADHD
arm group label: ADHD NOS
arm group label: NT NeuroTypical
intervention type: Diagnostic Test
intervention name: electroencephalography absolute slow alpha power
description: 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
arm group label: ADHD
arm group label: ADHD NOS
arm group label: NT NeuroTypical
intervention type: Diagnostic Test
intervention name: electroencephalography relative slow alpha power
description: 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
arm group label: ADHD
arm group label: ADHD NOS
arm group label: NT NeuroTypical
intervention type: Diagnostic Test
intervention name: electroencephalography absolute fast alpha power
description: 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
arm group label: ADHD
arm group label: ADHD NOS
arm group label: NT NeuroTypical
intervention type: Diagnostic Test
intervention name: electroencephalography relative fast alpha power
description: 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
arm group label: ADHD
arm group label: ADHD NOS
arm group label: NT NeuroTypical
intervention type: Diagnostic Test
intervention name: electroencephalography absolute beta power
description: 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
arm group label: ADHD
arm group label: ADHD NOS
arm group label: NT NeuroTypical
intervention type: Diagnostic Test
intervention name: electroencephalography relative beta power
description: 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
arm group label: ADHD
arm group label: ADHD NOS
arm group label: NT NeuroTypical
intervention type: Diagnostic Test
intervention name: Korean ADHD rating scale
description: The KARS is a standardized screening tool for ADHD in Korean children and rating scale completed by the parents.
arm group label: ADHD
arm group label: ADHD NOS
arm group label: NT NeuroTypical
intervention type: Diagnostic Test
intervention name: Korean Version of Diagnostic Interview Schedule for Children Version IV
description: The DISC-IV is a structured diagnostic tool that was developed for use in epidemiological studies in children and adolescents
arm group label: ADHD
arm group label: ADHD NOS
arm group label: NT NeuroTypical
study pop: 
sampling method: Probability Sample
criteria: 
gender: All
minimum age: 7 Years
maximum age: 12 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Jun Won Kim, M.D. Ph.D.
phone: +82-53-630-4780
email: f_affection@naver.com
facility: 
status: Recruiting
contact: 
country: Korea, Republic of
responsible party type: Principal Investigator
investigator affiliation: Daegu Catholic University Medical Center
investigator full name: Junwon Kim
investigator title: Clinical professor
mesh term: Hyperkinesis
mesh term: Disease
mesh term: Attention Deficit Disorder with Hyperactivity
mesh term: Mental Disorders
sharing ipd: No
ipd description: Data will be shared on request for proper reason