التفاصيل البيبلوغرافية
| العنوان: |
A Novel Method and Python Library for ECG Signal Quality Assessment |
| المؤلفون: |
Berger, Charles, Turbé, Hugues, Bjelogrlic, Mina, Lovis, Christian |
| المصدر: |
ISSN: 0926-9630 ; Studies in health technology and informatics. |
| سنة النشر: |
2024 |
| المجموعة: |
Université de Genève: Archive ouverte UNIGE |
| مصطلحات موضوعية: |
info:eu-repo/classification/ddc/616.0757, Electrocardiogram, Signal Quality Assessment (SQA), Time Series Dimension (TSD) |
| الوصف: |
Electrocardiogram (ECG) is one of the reference cardiovascular diagnostic exams. However, the ECG signal is very prone to being distorted through different sources of artifacts that can later interfere with the diagnostic. For this reason, signal quality assessment (SQA) methods that identify corrupted signals are critical to improve the robustness of automatic ECG diagnostic methods. This work presents a review and open-source implementation of different available indices for SQA as well as introducing an index that considers the ECG as a dynamical system. These indices are then used to develop machine learning models which evaluate the quality of the signals. The proposed index along the designed ML models are shown to improve SQA for ECG signals. |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
English |
| Relation: |
info:eu-repo/semantics/altIdentifier/pmid/39176928; unige:180413 |
| الاتاحة: |
https://archive-ouverte.unige.ch/unige:180413 |
| Rights: |
info:eu-repo/semantics/openAccess |
| رقم الانضمام: |
edsbas.718731ED |
| قاعدة البيانات: |
BASE |