{"id":"W3037936842","doi":"10.1109/jbhi.2020.3004319","title":"Towards User-Friendly Wearable Platforms for Monitoring Unconstrained Indoor and Outdoor Activities","year":2020,"lang":"en","type":"article","venue":"IEEE Journal of Biomedical and Health Informatics","topic":"Hand Gesture Recognition Systems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Gyroscope; Orientation (vector space); Computer science; Kinematics; Wearable computer; Kalman filter; Computer vision; Sensor fusion; Artificial intelligence; Inertial measurement unit; Angular velocity; Motion capture; Rotation (mathematics); Simulation; Motion (physics); Engineering; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001031778,0.0001171532,0.0003912561,0.0001273216,0.0001525197,0.0001491933,0.0002143872,0.00009089675,0.000001346982],"category_scores_gemma":[0.00008104801,0.00007949207,0.00005172943,0.0001753965,0.00008900758,0.0008679511,0.00004951598,0.0002496541,0.000001525491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000363289,"about_ca_system_score_gemma":0.0004494732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005322633,"about_ca_topic_score_gemma":7.236183e-7,"domain_scores_codex":[0.9982497,0.00001444657,0.0009889433,0.00006895474,0.0004089111,0.0002690774],"domain_scores_gemma":[0.9984307,0.000100593,0.0006185931,0.00006489758,0.000111529,0.0006736707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001101524,0.00008364386,0.001229486,0.00365638,0.0001345695,0.00001507702,0.0297064,0.000006266306,0.000164997,0.001102989,0.008333564,0.9554565],"study_design_scores_gemma":[0.03755631,0.03465033,0.007374663,0.0109737,0.000180539,0.006631762,0.06381646,0.1112402,0.01238556,0.008493177,0.7040088,0.00268847],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1103663,0.0006211008,0.8706675,0.01645542,0.001451202,0.0002957892,0.00002151236,0.00003560496,0.00008566325],"genre_scores_gemma":[0.8674317,0.0007717915,0.1283899,0.002280488,0.001090726,0.000007657808,0.00000104075,0.000008168427,0.00001857294],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.952768,"threshold_uncertainty_score":0.3241592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05590013227825318,"score_gpt":0.314825893272828,"score_spread":0.2589257609945748,"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."}}