{"id":"W4417439046","doi":"10.1109/rbme.2025.3639404","title":"Readout Techniques and Offset Compensation Strategies for Biomedical Resistive MEMS Sensors: A Comprehensive Review","year":2025,"lang":"en","type":"review","venue":"IEEE Reviews in Biomedical Engineering","topic":"Sensor Technology and Measurement Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Sherbrooke; Institut interdisciplinaire d'innovation technologique; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Capacitive sensing; Resistive touchscreen; Microelectromechanical systems; Offset (computer science); Compensation (psychology); Voltage; Noise (video); Microsystem","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00191648,0.0007064248,0.003623036,0.0009898201,0.0000736432,0.00007196976,0.001027163,0.0008201027,0.00000265781],"category_scores_gemma":[0.0007626035,0.0005521527,0.0004279783,0.001636604,0.0002150787,0.0001928874,0.0001022616,0.0007760508,0.00001231742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002298604,"about_ca_system_score_gemma":0.0003244698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000102585,"about_ca_topic_score_gemma":0.000001244615,"domain_scores_codex":[0.9957123,0.0003399865,0.001975247,0.000985942,0.0004498831,0.0005366057],"domain_scores_gemma":[0.9972717,0.001007772,0.0005513647,0.0008659108,0.0001212909,0.0001819685],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001239129,0.00003883465,5.395e-8,0.22133,0.00006310376,0.00003342926,0.00002014285,2.084927e-7,0.0000292603,0.002069204,0.005082496,0.771332],"study_design_scores_gemma":[0.0001462173,0.0000632453,1.453231e-7,0.2475421,0.0001684962,0.0001220061,0.000004560387,0.0002371215,0.000007527919,0.00006235829,0.7512892,0.0003570037],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[2.038801e-7,0.9207081,0.07345146,0.0002688619,0.000835751,0.004252417,0.00004025683,0.0003877197,0.00005528814],"genre_scores_gemma":[0.000001419379,0.9817188,0.01627695,0.0001127779,0.0002109688,0.001510805,0.0001050069,0.00003004708,0.00003322742],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7709751,"threshold_uncertainty_score":0.999693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06557470395128907,"score_gpt":0.3452134282876921,"score_spread":0.279638724336403,"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."}}