Cargando…
Supervised SVM Transfer Learning for Modality-Specific Artefact Detection in ECG
The electrocardiogram (ECG) is an important diagnostic tool for identifying cardiac problems. Nowadays, new ways to record ECG signals outside of the hospital are being investigated. A promising technique is capacitively coupled ECG (ccECG), which allows ECG signals to be recorded through insulating...
Autores principales: | Moeyersons, Jonathan, Morales, John, Villa, Amalia, Castro, Ivan, Testelmans, Dries, Buyse, Bertien, Van Hoof, Chris, Willems, Rik, Van Huffel, Sabine, Varon, Carolina |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7833429/ https://www.ncbi.nlm.nih.gov/pubmed/33477888 http://dx.doi.org/10.3390/s21020662 |
Ejemplares similares
-
Artefact detection and quality assessment of ambulatory ECG signals
por: Moeyersons, Jonathan, et al.
Publicado: (2019) -
Artefact Detection in Impedance Pneumography Signals: A Machine Learning Approach
por: Moeyersons, Jonathan, et al.
Publicado: (2021) -
Linear and Non-linear Quantification of the Respiratory Sinus Arrhythmia Using Support Vector Machines
por: Morales, John, et al.
Publicado: (2021) -
Capacitively-Coupled ECG and Respiration for Sleep–Wake Prediction and Risk Detection in Sleep Apnea Patients
por: Huysmans, Dorien, et al.
Publicado: (2021) -
Benchmarking Transfer Entropy Methods for the Study of Linear and Nonlinear Cardio-Respiratory Interactions
por: Rozo, Andrea, et al.
Publicado: (2021)