{"id":"W7105837562","doi":"10.2196/76084","title":"Advancements in Wearable Sensor Technologies for Health Monitoring in Terms of Clinical Applications, Rehabilitation, and Disease Risk Assessment: Systematic Review","year":2025,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wearable computer; mHealth; Wearable technology; Scalability; Focus (optics); Disease; Rehabilitation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004062085,0.0001336812,0.0008930698,0.0003121675,0.0001342439,0.00003025718,0.0002151222,0.00006313671,1.57862e-7],"category_scores_gemma":[0.001179786,0.0001228451,0.00004507307,0.0006509021,0.00006010885,0.000298215,0.00009325843,0.0002310111,5.137478e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001685658,"about_ca_system_score_gemma":0.0005858242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009232374,"about_ca_topic_score_gemma":0.00005146891,"domain_scores_codex":[0.9966965,0.0006354854,0.001666088,0.0005230687,0.0001726113,0.0003062779],"domain_scores_gemma":[0.9968273,0.001540812,0.000840976,0.0005211425,0.00009341892,0.0001763426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"observational","study_design_scores_codex":[0.00002817688,0.0002499592,0.4206103,0.4591448,0.000008500056,3.633064e-7,0.0001555792,0.000001686155,3.985133e-7,0.002401475,0.00008286842,0.1173158],"study_design_scores_gemma":[0.003414861,0.0006820192,0.7910373,0.1739241,0.00007092337,0.000003307016,0.001024149,0.006588254,0.000002103745,0.02208138,0.0008335516,0.0003380833],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1401459,0.2695606,0.4115117,0.116119,0.001072076,0.06039131,0.0002641016,0.0007134777,0.00022182],"genre_scores_gemma":[0.9276273,0.04827835,0.01897126,0.0006673642,0.00001644788,0.004402402,0.00000460497,0.000008109548,0.00002419946],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7874814,"threshold_uncertainty_score":0.5009478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05494547998276667,"score_gpt":0.4693594770365782,"score_spread":0.4144139970538115,"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."}}