{"id":"W2773356145","doi":"10.1109/iros.2017.8202200","title":"Nonlinear model predictive control of an upper extremity rehabilitation robot using a two-dimensional human-robot interaction model","year":2017,"lang":"en","type":"article","venue":"","topic":"Stroke Rehabilitation and Recovery","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Canada Research Chairs","keywords":"Robot; Controller (irrigation); Model predictive control; Rehabilitation; Computer science; Human–robot interaction; Robot end effector; Nonlinear system; Simulation; Control theory (sociology); Control engineering; Artificial intelligence; Control (management); Engineering; Medicine; Physical therapy","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":[0.0003407097,0.0005457241,0.0005588127,0.0002071062,0.0003393099,0.0007712069,0.0005978688,0.0008231492,0.001793841],"category_scores_gemma":[0.0005517927,0.0003084407,0.000502886,0.0002006281,0.0005314045,0.0003097718,0.0005381492,0.0006438399,0.0003187268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005759252,"about_ca_system_score_gemma":0.0009365308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01724675,"about_ca_topic_score_gemma":0.008920291,"domain_scores_codex":[0.9998338,0.00004273726,0.000008286022,0.0000393535,0.00005752594,0.00001820148],"domain_scores_gemma":[0.9997475,0.0001232309,0.00003927767,0.0000145593,0.00006625929,0.000009159243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002577876,0.00001268388,0.0001144917,0.00004258968,0.000008118132,0.00003517455,0.00003163575,0.9937373,0.001819221,0.000942369,0.0001115697,0.003119039],"study_design_scores_gemma":[0.000005340255,0.00001888524,0.00006898784,0.000001987144,0.000002821609,0.000003279204,0.000002734993,0.9993963,0.0002561185,0.00009366198,0.0001480457,0.000001845511],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07347715,0.0003302335,0.9107234,0.0003035406,0.00007451844,0.0001507187,0.0001442269,0.0007031966,0.01409308],"genre_scores_gemma":[0.9592924,0.0002323198,0.03185543,0.00005554483,0.00001793212,0.0003737677,0.0001108373,0.00002709232,0.008034579],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01724675,"threshold_uncertainty_score":0.03429276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0433278745847724,"score_gpt":0.3639700829051707,"score_spread":0.3206422083203983,"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."}}