{"id":"W3135667991","doi":"10.1088/1741-2552/abee51","title":"A multi-modal modified feedback self-paced BCI to control the gait of an avatar","year":2021,"lang":"en","type":"article","venue":"Journal of Neural Engineering","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université de Montréal","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Brain–computer interface; Motor imagery; Avatar; Computer science; Gait; Virtual reality; Modal; Physical medicine and rehabilitation; Artificial intelligence; Human–computer interaction; Electroencephalography; Psychology","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":[0.0002467273,0.0002840926,0.0001889503,0.0001831777,0.00009844557,0.0001317719,0.0002709453,0.0002176683,0.001567348],"category_scores_gemma":[0.0007172467,0.00008089887,0.0001292456,0.00007925865,0.00008275086,0.0000927187,0.0002099265,0.0001992872,0.0003147178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008998791,"about_ca_system_score_gemma":0.00008969499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006749025,"about_ca_topic_score_gemma":0.001063611,"domain_scores_codex":[0.9998789,0.00002789198,0.000009101443,0.00004134779,0.00003291036,0.000009955631],"domain_scores_gemma":[0.9997889,0.00005711704,0.00001980066,0.00002804104,0.00008228071,0.00002395398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001092713,0.0004651912,0.003851213,0.0002757736,0.00005095396,0.0003397234,0.000166682,0.002128195,0.7635672,0.0002168584,0.001519896,0.2263256],"study_design_scores_gemma":[0.0007354959,0.009799159,0.1391247,0.00007975008,0.0003160757,0.006880469,0.0001410029,0.3876751,0.4402816,0.0006773206,0.01418028,0.0001090305],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8336388,0.000523539,0.1604035,0.0001178133,0.0001656646,0.000350133,0.0002774691,0.001204177,0.003318941],"genre_scores_gemma":[0.9604449,0.00006175719,0.03727424,0.00006191394,0.00002014384,0.0001061707,0.000106859,0.00001815823,0.001905813],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001567348,"threshold_uncertainty_score":0.005243242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02456398147101431,"score_gpt":0.25788837891772,"score_spread":0.2333243974467057,"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."}}