{"id":"W2097351823","doi":"10.1109/memea.2011.5966752","title":"Signal enhancement of wearable ECG monitoring sensors based on Ensemble Empirical Mode Decomposition","year":2011,"lang":"en","type":"article","venue":"","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Hilbert–Huang transform; Computer science; Noise (video); Wearable computer; Artificial intelligence; SIGNAL (programming language); Pattern recognition (psychology); Noise reduction; Speech recognition; Computer vision; Filter (signal processing); Embedded system","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":[0.0001425456,0.000113605,0.0002420192,0.0001362579,0.00005089819,0.000005150695,0.00004444259,0.00006231627,0.0004239693],"category_scores_gemma":[0.00001255555,0.00009273489,0.0001241714,0.0001503136,0.00002082344,0.00003400764,0.0000106394,0.0001132139,0.00005185847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007078313,"about_ca_system_score_gemma":0.00003748769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002210387,"about_ca_topic_score_gemma":0.000001311223,"domain_scores_codex":[0.9990227,0.00003515171,0.000236319,0.000201154,0.0002960245,0.0002086989],"domain_scores_gemma":[0.9994583,0.00004835424,0.00005940075,0.0002216025,0.00008947244,0.0001228883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000846012,0.001772929,0.2962245,0.0001397861,0.0002184832,0.00004977157,0.0005822609,0.002926118,0.6844145,0.00001586748,0.0003471096,0.01246262],"study_design_scores_gemma":[0.0005348556,0.0006524397,0.004403485,0.0002308117,0.0001167088,0.000001762533,0.000132018,0.07987528,0.9139125,0.00002780125,0.00002295137,0.00008935933],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9594842,0.00002467442,0.02268117,0.0001028693,0.0001054522,0.0000819796,7.81092e-7,0.00004944683,0.01746943],"genre_scores_gemma":[0.973215,0.00001674158,0.02499506,0.00005228262,0.0001370627,0.000008284685,0.000003352399,0.00001265567,0.001559603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2918211,"threshold_uncertainty_score":0.4642167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05605223308564973,"score_gpt":0.3727889166260285,"score_spread":0.3167366835403788,"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."}}