A Brain-Computer Interface Based Attention Training Program for Treating Attention Deficit Hyperactivity Disorder
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{"title"=>"A Brain-Computer Interface Based Attention Training Program for Treating Attention Deficit Hyperactivity Disorder", "type"=>"journal", "authors"=>[{"first_name"=>"Choon Guan", "last_name"=>"Lim", "scopus_author_id"=>"8264376900"}, {"first_name"=>"Tih Shih", "last_name"=>"Lee", "scopus_author_id"=>"8690334000"}, {"first_name"=>"Cuntai", "last_name"=>"Guan", "scopus_author_id"=>"7101632622"}, {"first_name"=>"Daniel Shuen Sheng", "last_name"=>"Fung", "scopus_author_id"=>"7103139903"}, {"first_name"=>"Yudong", "last_name"=>"Zhao", "scopus_author_id"=>"55440586100"}, {"first_name"=>"Stephanie Sze Wei", "last_name"=>"Teng", "scopus_author_id"=>"37079754800"}, {"first_name"=>"Haihong", "last_name"=>"Zhang", "scopus_author_id"=>"15623948900"}, {"first_name"=>"K. Ranga Rama", "last_name"=>"Krishnan", "scopus_author_id"=>"35377962400"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"23115630", "doi"=>"10.1371/journal.pone.0046692", "sgr"=>"84868121168", "isbn"=>"1932-6203", "scopus"=>"2-s2.0-84868121168", "issn"=>"19326203", "pui"=>"365952111"}, "id"=>"1a76e7ab-f766-30f2-9b36-b20ae9026e61", "abstract"=>"Attention deficit hyperactivity disorder (ADHD) symptoms can be difficult to treat. We previously reported that a 20-session brain-computer interface (BCI) attention training programme improved ADHD symptoms. Here, we investigated a new more intensive BCI-based attention training game system on 20 unmedicated ADHD children (16 males, 4 females) with significant inattentive symptoms (combined and inattentive ADHD subtypes). This new system monitored attention through a head band with dry EEG sensors, which was used to drive a feed forward game. The system was calibrated for each user by measuring the EEG parameters during a Stroop task. Treatment consisted of an 8-week training comprising 24 sessions followed by 3 once-monthly booster training sessions. Following intervention, both parent-rated inattentive and hyperactive-impulsive symptoms on the ADHD Rating Scale showed significant improvement. At week 8, the mean improvement was 24.6 (5.9) and 24.7 (5.6) respectively for inattentive symptoms and hyperactive-impulsive symptoms (both p,0.01). Cohen's d effect size for inattentive symptoms was large at 0.78 at week 8 and 0.84 at week 24 (post-boosters). Further analysis showed that the change in the EEG based BCI ADHD severity measure correlated with the change ADHD Rating Scale scores. The BCI-based attention training game system is a potential new treatment for ADHD. Investigators from the funding institute were involved in this project. They were the inventors of the brain-computer interface system and gaming software. They were involved during the trial in maintenance of the systems and in the writing of the manuscript.", "link"=>"http://www.mendeley.com/research/braincomputer-interface-based-attention-training-program-treating-attention-deficit-hyperactivity-di-1", "reader_count"=>142, "reader_count_by_academic_status"=>{"Unspecified"=>3, "Professor > Associate Professor"=>9, "Librarian"=>1, "Researcher"=>21, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>36, "Student > Postgraduate"=>5, "Student > Master"=>29, "Other"=>4, "Student > Bachelor"=>22, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1, "Professor"=>6}, "reader_count_by_user_role"=>{"Unspecified"=>3, "Professor > Associate Professor"=>9, "Librarian"=>1, "Researcher"=>21, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>36, "Student > Postgraduate"=>5, "Student > Master"=>29, "Other"=>4, "Student > Bachelor"=>22, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1, "Professor"=>6}, "reader_count_by_subject_area"=>{"Unspecified"=>7, "Agricultural and Biological Sciences"=>17, "Arts and Humanities"=>1, "Computer Science"=>27, "Engineering"=>27, "Nursing and Health Professions"=>1, "Medicine and Dentistry"=>10, "Design"=>2, "Neuroscience"=>8, "Pharmacology, Toxicology and Pharmaceutical Science"=>2, "Physics and Astronomy"=>1, "Psychology"=>34, "Social Sciences"=>5}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>10}, "Social Sciences"=>{"Social Sciences"=>5}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Psychology"=>{"Psychology"=>34}, "Unspecified"=>{"Unspecified"=>7}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>2}, "Arts and Humanities"=>{"Arts and Humanities"=>1}, "Design"=>{"Design"=>2}, "Engineering"=>{"Engineering"=>27}, "Neuroscience"=>{"Neuroscience"=>8}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>17}, "Computer Science"=>{"Computer Science"=>27}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}}, "reader_count_by_country"=>{"Republic of Singapore"=>3, "United States"=>2, "Brazil"=>1, "Slovakia"=>1, "France"=>1, "Switzerland"=>1, "Germany"=>1, "Spain"=>1}, "group_count"=>16}

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  • {"files"=>["https://ndownloader.figshare.com/files/554155"], "description"=>"*<p>The improvement compared to baseline scores in all domains was statistically significant.</p>", "links"=>[], "tags"=>["iv", "inattentive", "hyperactive-impulsive", "symptoms", "scores", "rated"], "article_id"=>224633, "categories"=>["Science Policy", "Mental Health", "Medicine", "Information And Computing Sciences", "Biotechnology", "Physiology", "Neuroscience"], "users"=>["Choon Guan Lim", "Tih Shih Lee", "Cuntai Guan", "Daniel Shuen Sheng Fung", "Yudong Zhao", "Stephanie Sze Wei Teng", "Haihong Zhang", "K. Ranga Rama Krishnan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0046692.t001", "stats"=>{"downloads"=>6, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_ADHD_rating_scale_IV_ARS_IV_inattentive_IA_hyperactive_impulsive_HI_and_combined_symptoms_COM_total_raw_scores_as_rated_by_parents_/224633", "title"=>"ADHD rating scale IV (ARS-IV) inattentive (IA), hyperactive-impulsive (HI) and combined symptoms (COM) total raw scores as rated by parents<sup>*</sup>.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-10-24 01:17:13"}
  • {"files"=>["https://ndownloader.figshare.com/files/295290", "https://ndownloader.figshare.com/files/295436"], "description"=>"<div><p>Attention deficit hyperactivity disorder (ADHD) symptoms can be difficult to treat. We previously reported that a 20-session brain-computer interface (BCI) attention training programme improved ADHD symptoms. Here, we investigated a new more intensive BCI-based attention training game system on 20 unmedicated ADHD children (16 males, 4 females) with significant inattentive symptoms (combined and inattentive ADHD subtypes). This new system monitored attention through a head band with dry EEG sensors, which was used to drive a feed forward game. The system was calibrated for each user by measuring the EEG parameters during a Stroop task. Treatment consisted of an 8-week training comprising 24 sessions followed by 3 once-monthly booster training sessions. Following intervention, both parent-rated inattentive and hyperactive-impulsive symptoms on the ADHD Rating Scale showed significant improvement. At week 8, the mean improvement was −4.6 (5.9) and −4.7 (5.6) respectively for inattentive symptoms and hyperactive-impulsive symptoms (both p<0.01). Cohen’s d effect size for inattentive symptoms was large at 0.78 at week 8 and 0.84 at week 24 (post-boosters). Further analysis showed that the change in the EEG based BCI ADHD severity measure correlated with the change ADHD Rating Scale scores. The BCI-based attention training game system is a potential new treatment for ADHD.</p> <h3>Trial Registration</h3><p>ClinicalTrials.gov <a href=\"http://clinicaltrials.gov/ct2/show/NCT01344044\">NCT01344044</a></p> </div>", "links"=>[], "tags"=>["brain-computer", "interface", "based", "treating", "hyperactivity", "disorder"], "article_id"=>118156, "categories"=>["Science Policy", "Mental Health", "Medicine", "Information And Computing Sciences", "Biotechnology", "Physiology", "Neuroscience"], "users"=>["Choon Guan Lim", "Tih Shih Lee", "Cuntai Guan", "Daniel Shuen Sheng Fung", "Yudong Zhao", "Stephanie Sze Wei Teng", "Haihong Zhang", "K. Ranga Rama Krishnan"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0046692.s001", "https://dx.doi.org/10.1371/journal.pone.0046692.s002"], "stats"=>{"downloads"=>10, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/A_Brain_Computer_Interface_Based_Attention_Training_Program_for_Treating_Attention_Deficit_Hyperactivity_Disorder__/118156", "title"=>"A Brain-Computer Interface Based Attention Training Program for Treating Attention Deficit Hyperactivity Disorder", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-10-24 02:15:56"}
  • {"files"=>["https://ndownloader.figshare.com/files/553619"], "description"=>"<p>CONSORT flow diagram.</p>", "links"=>[], "tags"=>["public health and epidemiology", "Mental health", "physiology", "neuroscience", "computer science", "science policy", "pediatrics and child health"], "article_id"=>224093, "categories"=>["Science Policy", "Mental Health", "Medicine", "Information And Computing Sciences", "Biotechnology", "Physiology", "Neuroscience"], "users"=>["Choon Guan Lim", "Tih Shih Lee", "Cuntai Guan", "Daniel Shuen Sheng Fung", "Yudong Zhao", "Stephanie Sze Wei Teng", "Haihong Zhang", "K. Ranga Rama Krishnan"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0046692.g001", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_CONSORT_flow_diagram_/224093", "title"=>"CONSORT flow diagram.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-10-24 01:08:13"}

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Relative Metric

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