{"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/ecg-signal-processing-and-feature-extraction","title":"ECG signal processing and feature extraction to validate feature significance for arrythmia detection","arxiv_id":null,"date":"2024-07-04","proceeding":"- 2024 7","authors":["John M. De Moura","Ana L. Espinoza","Maria A. Flores","Juan A. Zavaleta"],"abstract":"Arrhythmias, such as tachycardia and bradycardia, are prevalent in postoperative patients, especially within the first week after surgery. These conditions can lead to significant health risks, particularly in settings with inadequate monitoring resources, such as rural areas in Peru. This paper proposes an advanced approach to arrhythmia detection using ECG signal processing and feature extraction to feed artificial intelligence (AI) models. By optimizing training data and comparing ECG signal features, this method aims to enhance the accuracy and efficiency of arrhythmia identification, thereby improving patient monitoring and reducing associated health risks.","url_abs":"https://github.com/Firestorm12344/ISB-Grupo4/tree/main/Proyecto","url_pdf":"https://github.com/Firestorm12344/ISB-Grupo4/blob/main/Proyecto/Paper%20final%20-%20grupo%204.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":"ecg-signal-processing-and-feature-extraction","repo_url":"https://github.com/Firestorm12344/ISB-Grupo4/blob/main/Proyecto/C%C3%B3digo/Signal_Processing%20-%20v2.ipynb","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"arrhythmia-detection","task_name":"Arrhythmia Detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}