{"id":"W2040879679","doi":"10.1109/tnsre.2011.2162250","title":"An Analysis of the Accuracy of Wearable Sensors for Classifying the Causes of Falls in Humans","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Neural Systems and Rehabilitation Engineering","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":99,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Canadian Institutes of Health Research","keywords":"Accelerometer; Wearable computer; Physical medicine and rehabilitation; Poison control; Sensitivity (control systems); Medicine; Computer science; Ankle; Linear discriminant analysis; Artificial intelligence; Medical emergency; Engineering; Embedded system","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":[0.001518986,0.0004756521,0.0003257981,0.000749254,0.0001841621,0.0004744489,0.0002344553,0.0005784439,0.0005765195],"category_scores_gemma":[0.01173671,0.00016015,0.0003049306,0.0004279916,0.0002478706,0.0004549753,0.0002491187,0.0002167944,0.0004083515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001528507,"about_ca_system_score_gemma":0.0001078548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009118415,"about_ca_topic_score_gemma":0.001085376,"domain_scores_codex":[0.9990401,0.0002888486,0.0001125384,0.0001770092,0.0003291825,0.00005235241],"domain_scores_gemma":[0.9948501,0.002994763,0.0005211965,0.0004213832,0.001124771,0.00008770833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003030198,0.0004685493,0.599254,0.0003272055,0.0005016152,0.0001424819,0.0004644672,0.01083601,0.04272568,0.0002671986,0.0007816388,0.3412009],"study_design_scores_gemma":[0.00007701156,0.003387215,0.8632491,0.00008336693,0.0002812118,0.0008036851,0.0004190743,0.1105495,0.01955562,0.0006198765,0.0009232398,0.00005107055],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9848098,0.0007238738,0.01304615,0.00007857099,0.00003791308,0.00003086474,0.0002363772,0.00007103188,0.0009653479],"genre_scores_gemma":[0.9947544,0.0002407954,0.00449882,0.00002352496,0.00001972609,0.00001638799,0.0001817928,0.000006112833,0.0002583372],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001518986,"threshold_uncertainty_score":0.008033216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03330020254826666,"score_gpt":0.2571888882340294,"score_spread":0.2238886856857627,"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."}}