{"id":"W2954663339","doi":"10.1109/lra.2019.2924852","title":"Design and Control of a Multifunctional Ankle Exoskeleton Powered by Magnetorheological Actuators to Assist Walking, Jumping, and Landing","year":2019,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Prosthetics and Rehabilitation Robotics","field":"Engineering","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"Theratechnologies (Canada); Institut interdisciplinaire d'innovation technologique","funders":"","keywords":"Exoskeleton; Jumping; Magnetorheological fluid; Clutch; Torque; Actuator; Ankle; Powered exoskeleton; Simulation; Computer science; Engineering; Control theory (sociology); Automotive engineering; Control engineering; Damper; Artificial intelligence; Control (management); Physics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002113541,0.0003192456,0.0002430284,0.0001161938,0.0002012379,0.0002958161,0.0003735218,0.0002436337,0.00101656],"category_scores_gemma":[0.0001574801,0.0001285362,0.0001796228,0.00005369228,0.0002421622,0.000170092,0.0002814217,0.0001475018,0.0001504301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001065843,"about_ca_system_score_gemma":0.0002628265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000489847,"about_ca_topic_score_gemma":0.0007771467,"domain_scores_codex":[0.999908,0.00001166742,0.00000849151,0.00002963794,0.00003037718,0.00001183221],"domain_scores_gemma":[0.9999088,0.00001401626,0.00003224389,0.000009916141,0.00002153239,0.00001335772],"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":[0.0004122282,0.0002410401,0.0008876709,0.0003890226,0.00005569917,0.0006382721,0.0001894257,0.05133792,0.8810046,0.002201152,0.0009411579,0.06170186],"study_design_scores_gemma":[0.0002814617,0.003626754,0.007878846,0.0000465084,0.00008704887,0.0004845847,0.000114844,0.8784364,0.09937384,0.001090247,0.008532028,0.00004756756],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4320391,0.0004114007,0.5575202,0.0003450009,0.0001854843,0.000282272,0.00008557094,0.0008876439,0.008243307],"genre_scores_gemma":[0.9751822,0.00008475098,0.02221865,0.00003018182,0.00001127635,0.0001151509,0.00002090717,0.00001306617,0.002323734],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00101656,"threshold_uncertainty_score":0.003400743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005397410413065643,"score_gpt":0.1962229358067784,"score_spread":0.1908255253937127,"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."}}