{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003979746,0.0003637386,0.0004012629,0.0002688027,0.00007037416,0.0002210363,0.0002498833,0.0003509674,0.0003998938],"category_scores_gemma":[0.001146256,0.0001418465,0.0003227154,0.0002213144,0.0001233252,0.0004770592,0.0002665307,0.0002881248,0.0001256055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006662859,"about_ca_system_score_gemma":0.00007184492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002033114,"about_ca_topic_score_gemma":0.0003154231,"domain_scores_codex":[0.999826,0.0000539417,0.00001067829,0.00003287001,0.00006824718,0.000008207016],"domain_scores_gemma":[0.9996916,0.0001502449,0.00004184095,0.00003378352,0.00007220573,0.00001029779],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003651364,0.0001506955,0.003302899,0.0002043525,0.0001088784,0.000258767,0.0001675194,0.07902488,0.3588444,0.001915074,0.0007473615,0.55491],"study_design_scores_gemma":[0.000014497,0.0002162793,0.005552552,0.00001989903,0.00004418764,0.0004535806,0.00002579021,0.9280968,0.06313512,0.0006381955,0.001782156,0.00002096138],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1043654,0.0005018445,0.8941506,0.00007134108,0.00003518719,0.000022483,0.00002651728,0.00026024,0.0005662788],"genre_scores_gemma":[0.5448756,0.0007121799,0.4529375,0.00006694929,0.00004933787,0.00003610534,0.00009622987,0.00004457989,0.001181414],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0004012629,"threshold_uncertainty_score":0.002104759,"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."}}