{"id":"W3110741822","doi":"10.1109/bibe50027.2020.00136","title":"Remote Health Monitoring System for Bedbound Patients","year":2020,"lang":"en","type":"article","venue":"","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Real-time computing; Breathing; Support vector machine; Radar; Artificial intelligence; Waveform; Bedroom; Position (finance); Remote patient monitoring; Computer vision; Telecommunications; Engineering; Medicine","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":[0.0003119581,0.0005087381,0.0005248256,0.0004103205,0.0002286553,0.0004417975,0.0005482074,0.0006139448,0.01136589],"category_scores_gemma":[0.0007733484,0.0001175438,0.0002234336,0.0001980967,0.00009096741,0.0003609715,0.000569654,0.000448959,0.00381201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001479228,"about_ca_system_score_gemma":0.0001570249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003695366,"about_ca_topic_score_gemma":0.0003982114,"domain_scores_codex":[0.9997512,0.00006250133,0.00002082117,0.00007575164,0.00006631864,0.00002345958],"domain_scores_gemma":[0.9996231,0.0001162643,0.00004992167,0.00004938629,0.0001107478,0.00005058668],"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":[0.002115645,0.0004959705,0.03612398,0.0008776982,0.0001207148,0.002147807,0.0005174863,0.003815152,0.1250145,0.001636376,0.04343034,0.7837043],"study_design_scores_gemma":[0.001338938,0.00671943,0.2129311,0.0008033979,0.0007825808,0.01871428,0.001363681,0.3731253,0.1934449,0.005339973,0.1850813,0.0003551879],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3325471,0.007704461,0.5857435,0.003418918,0.001897147,0.0008686626,0.003711109,0.03200812,0.03210102],"genre_scores_gemma":[0.9159744,0.001334105,0.06188996,0.001540507,0.000662703,0.0004891848,0.001892572,0.0001751606,0.01604146],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01136589,"threshold_uncertainty_score":0.0380227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02734548262718932,"score_gpt":0.2395969959226341,"score_spread":0.2122515132954448,"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."}}