{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/180711359","title":"Baseline wander removal methods for ECG signals: A comparative study","arxiv_id":"1807.11359","date":"2018-07-30","proceeding":null,"authors":["Francisco Perdigon Romero","Liset Vazquez Romaguera","Carlos Román Vázquez-Seisdedos","Cícero Ferreira Fernandes Costa Filho","Marly Guimarães Fernandes Costa","João Evangelista Neto"],"abstract":"Cardiovascular diseases are the leading cause of death worldwide, accounting\nfor 17.3 million deaths per year. The electrocardiogram (ECG) is a non-invasive\ntechnique widely used for the detection of cardiac diseases. To increase\ndiagnostic sensitivity, ECG is acquired during exercise stress tests or in an\nambulatory way. Under these acquisition conditions, the ECG is strongly\naffected by some types of noise, mainly by baseline wander (BLW). In this work\nwere implemented nine methods widely used for the elimination of BLW, which\nare: interpolation using cubic splines, FIR filter, IIR filter, least mean\nsquare adaptive filtering, moving-average filter, independent component\nanalysis, interpolation and successive subtraction of median values in RR\ninterval, empirical mode decomposition and wavelet filtering. For the\nquantitative evaluation, the following similarity metrics were used: absolute\nmaximum distance, the sum of squares of distances and percentage\nroot-mean-square difference. Several experiments were performed using synthetic\nECG signals generated by ECGSYM software, real ECG signals from QT Database,\nartificial BLW generated by software and real BLW from the Noise Stress Test\nDatabase. The best results were obtained by the method based on FIR high-pass\nfilter with a cut-off frequency of 0.67 Hz.","url_abs":"http://arxiv.org/abs/1807.11359v2","url_pdf":"http://arxiv.org/pdf/1807.11359v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"180711359","repo_url":"https://github.com/fperdigon/ECG-BaseLineWander-Removal-Methods","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"180711359","repo_url":"https://github.com/fperdigon/DeepFilter","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"diagnostic","task_name":"Diagnostic"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}