{"id":"W4303982406","doi":"10.3390/s22197596","title":"Classification of EEG Using Adaptive SVM Classifier with CSP and Online Recursive Independent Component Analysis","year":2022,"lang":"en","type":"article","venue":"Sensors","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"Natural Sciences and Engineering Research Council of Canada; New Brunswick Innovation Foundation","keywords":"Independent component analysis; Support vector machine; Artificial intelligence; Classifier (UML); Computer science; Component (thermodynamics); Pattern recognition (psychology); Electroencephalography; Component analysis; Machine learning; Speech recognition; Psychology; Neuroscience","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008582343,0.0009273642,0.0008345032,0.001261005,0.0002353913,0.0006590217,0.0006461057,0.0007446003,0.001121949],"category_scores_gemma":[0.002048392,0.0001743845,0.0008626789,0.001216152,0.000204035,0.0006478531,0.0004622584,0.0007466801,0.0006141265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002408515,"about_ca_system_score_gemma":0.00060517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0023568,"about_ca_topic_score_gemma":0.001588674,"domain_scores_codex":[0.9993165,0.0001264587,0.00007715389,0.0001789985,0.0002041132,0.00009684338],"domain_scores_gemma":[0.9991727,0.0002397146,0.00006496886,0.00008004403,0.0004126066,0.00002992822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005705144,0.0003721323,0.004168435,0.0001473727,0.0001138583,0.0001554422,0.00005394405,0.04238718,0.04223813,0.001013707,0.004553583,0.9042256],"study_design_scores_gemma":[0.00002326873,0.0002052719,0.004399144,0.000009527962,0.00003041716,0.00009023496,0.00002671281,0.982444,0.0113817,0.0005098585,0.0008636206,0.00001626651],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1503167,0.0006942938,0.843181,0.0002167866,0.0002181204,0.0002840399,0.0005127597,0.002723076,0.001853239],"genre_scores_gemma":[0.6887751,0.0003487765,0.306172,0.00008271671,0.0001066165,0.0003777735,0.001617668,0.00009040886,0.002429037],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0023568,"threshold_uncertainty_score":0.004686236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06329387871427461,"score_gpt":0.288903879493987,"score_spread":0.2256100007797124,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}