{"id":"W2200528657","doi":"10.1109/iros.2015.7353969","title":"An user-independent gesture recognition method based on sEMG decomposition","year":2015,"lang":"en","type":"article","venue":"","topic":"Muscle activation and electromyography studies","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Gesture recognition; Artificial intelligence; Pattern recognition (psychology); Gesture; Speech recognition; Cluster analysis; Orthogonalization; Hidden Markov model; Algorithm","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":[0.0002980613,0.0006176223,0.0006266345,0.000679667,0.000155793,0.0002884257,0.0003694523,0.0004400641,0.002001434],"category_scores_gemma":[0.0006822476,0.0001801987,0.0004372679,0.000566509,0.0001855931,0.0005392079,0.0003634253,0.0004656266,0.0008918989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001071873,"about_ca_system_score_gemma":0.0003004015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007368378,"about_ca_topic_score_gemma":0.001703765,"domain_scores_codex":[0.9996966,0.0000427971,0.000025221,0.00008885245,0.0001258356,0.00002069874],"domain_scores_gemma":[0.9997831,0.00004618047,0.00002229737,0.00004256349,0.00008972994,0.00001612176],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001621978,0.00006295575,0.001076218,0.0001456784,0.00005543134,0.00008486323,0.00004414115,0.003586238,0.1921398,0.0008193135,0.001517125,0.8003061],"study_design_scores_gemma":[0.00007034191,0.0005271731,0.02668837,0.00004422596,0.0001124931,0.001923742,0.0000838059,0.7177843,0.2395684,0.002118663,0.01095558,0.0001229011],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02466113,0.0002122448,0.9721134,0.000049403,0.00006787311,0.00008599708,0.0001193095,0.001587313,0.001103246],"genre_scores_gemma":[0.376393,0.0004341433,0.6175946,0.0001219605,0.00006436804,0.00020126,0.0004553682,0.000132964,0.004602367],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002001434,"threshold_uncertainty_score":0.006695449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02622257693713321,"score_gpt":0.2872935225436168,"score_spread":0.2610709456064836,"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."}}