{"id":"W3029485558","doi":"10.24018/ejece.2020.4.2.208","title":"Extracting Heart Rate Variability: A Summary of Camera Based Photoplethysmograph","year":2020,"lang":"en","type":"article","venue":"European Journal of Electrical Engineering and Computer Science","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research","funders":"","keywords":"Photoplethysmogram; Heart rate; Heartbeat; Fainting; Heart rate variability; Computer science; Heart rate monitor; Artificial intelligence; Computer vision; Medicine; Internal medicine; Computer security; Blood pressure","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001292216,0.0001403841,0.0002429987,0.000210926,0.00004601029,0.00007100114,0.0003198273,0.00001464981,0.000001537731],"category_scores_gemma":[0.0002570651,0.000132119,0.00007880355,0.001046719,0.00006548553,0.0002462217,0.0000546046,0.0003819873,0.000001027299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003001175,"about_ca_system_score_gemma":0.00005741124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.928894e-7,"about_ca_topic_score_gemma":7.550215e-9,"domain_scores_codex":[0.9988227,0.00008241353,0.0003893985,0.0001695499,0.0002647405,0.0002712048],"domain_scores_gemma":[0.9991311,0.0002873421,0.00007950755,0.0001068123,0.0001145901,0.0002806405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001196146,0.00001773739,0.0009100061,0.00006855874,0.00001766775,0.00007667157,0.0001208684,0.1490712,0.8371111,0.00003965753,0.00005767936,0.01249687],"study_design_scores_gemma":[0.000443184,0.0005880406,0.008179458,0.0001659138,0.00001733669,0.0000831674,0.000003950508,0.8713903,0.1181764,0.000009186871,0.0006889844,0.0002540488],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3337925,0.0002745424,0.6653832,0.00006823753,0.0002824379,0.00004184833,6.081949e-7,0.00006464471,0.00009199878],"genre_scores_gemma":[0.9624077,0.00001706163,0.03721482,0.00007591057,0.0002630355,2.724778e-7,8.319355e-8,0.00002083862,2.767513e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7223191,"threshold_uncertainty_score":0.5387656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009354619944853995,"score_gpt":0.1886219431202915,"score_spread":0.1792673231754375,"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."}}