{"id":"W4403372065","doi":"10.4017/gt.2024.23.s.886.opp","title":"Remote heart rate monitoring with contactless ambient technology using machine learning for aging population","year":2024,"lang":"en","type":"article","venue":"Gerontechnology","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Mitacs; Ontario Centre of Innovation","keywords":"Population; Computer science; Biomedical engineering; Medicine","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":[0.0004402677,0.0004015275,0.0005109532,0.0006032989,0.0001490312,0.000485947,0.0004113349,0.0003104663,0.0008958789],"category_scores_gemma":[0.001074292,0.0001192376,0.00032458,0.0004637612,0.0001304469,0.0004386902,0.0004154906,0.0003108997,0.0004277576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001276777,"about_ca_system_score_gemma":0.0001831695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008290834,"about_ca_topic_score_gemma":0.001225064,"domain_scores_codex":[0.999685,0.00009420089,0.00001769054,0.00009230455,0.00008724305,0.00002364562],"domain_scores_gemma":[0.9997391,0.00009077014,0.00004814609,0.00002658563,0.00007660974,0.00001880095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006642014,0.001290403,0.1287335,0.0006504229,0.0001868661,0.0003516795,0.0006165814,0.0168083,0.04394823,0.0007961703,0.003476378,0.8024773],"study_design_scores_gemma":[0.00008520925,0.00248382,0.270698,0.0002571177,0.000401105,0.001248506,0.0008116626,0.6805484,0.03115599,0.003385695,0.008798173,0.0001264869],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7718875,0.003332242,0.2150693,0.0004872204,0.0001690102,0.0002992665,0.0007279401,0.0008438593,0.007183596],"genre_scores_gemma":[0.9449816,0.00115197,0.05139379,0.0001176194,0.000101189,0.0001499534,0.0002953488,0.00001571084,0.001792877],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008958789,"threshold_uncertainty_score":0.002997041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01876576060990003,"score_gpt":0.2615838780992442,"score_spread":0.2428181174893442,"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."}}