{"id":"W4327663266","doi":"10.1109/tcyb.2023.3253181","title":"Active Human-Following Control of an Exoskeleton Robot With Body Weight Support","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Prosthetics and Rehabilitation Robotics","field":"Engineering","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Major Science and Technology Projects in Anhui Province; National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Exoskeleton; Robot; Powered exoskeleton; Computer science; Artificial neural network; Electromyography; Artificial intelligence; Tracking (education); Human–robot interaction; Gait; Control (management); Simulation; Control theory (sociology); Engineering; Physical medicine and rehabilitation","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001066149,0.0001935041,0.0002474607,0.0002089623,0.0001031084,0.00001927338,0.0001357176,0.0001156548,0.00005279874],"category_scores_gemma":[0.000001980478,0.0001767737,0.0001227379,0.000361064,0.00007411283,0.00010502,6.562393e-7,0.0002350897,0.00004320962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005265382,"about_ca_system_score_gemma":0.00002836441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001213424,"about_ca_topic_score_gemma":0.00004745702,"domain_scores_codex":[0.9989402,0.00002932475,0.0002862924,0.0001904975,0.0002834199,0.0002702722],"domain_scores_gemma":[0.999375,0.00009749675,0.00004085842,0.0003070287,0.0000677674,0.0001118265],"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":[0.00003399217,0.0001623707,0.00003210856,0.0000533178,0.0001877168,0.00001617975,0.0008841924,0.9519634,0.04206558,0.0001753677,0.00004658304,0.00437917],"study_design_scores_gemma":[0.006460387,0.004044662,0.008890104,0.0002307603,0.000675003,0.00002469467,0.0009601255,0.5674279,0.4067973,0.0007976661,0.002292416,0.001399016],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5478306,0.00001224553,0.4491935,0.0001044499,0.0006571109,0.0004051593,0.00008582293,0.0005119785,0.001199128],"genre_scores_gemma":[0.9978802,0.00002756994,0.001580546,0.00002035006,0.00002673892,0.00003553496,0.00001427328,0.00006750072,0.0003472601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4500497,"threshold_uncertainty_score":0.7208621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008006277274682153,"score_gpt":0.2326568546744277,"score_spread":0.2246505773997455,"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."}}