Motion Artifact Reduction in Electrocardiogram Signals Through a Redundant Denoising Independent Component Analysis Method for Wearable Health Care Monitoring Systems: Algorithm Development and Validation.
Fabian Andres CastañoChristian GisselAlher Mauricio Hernández ValdiviesoPublished in: JMIR medical informatics (2022)
Our novel ECG denoising method is a contribution to converting wearable devices into medical monitoring tools that can be used to support the remote diagnosis and monitoring of cardiovascular diseases. A more accurate signal substantially improves the diagnostic yield of wearable devices. A better yield improves the devices' cost-effectiveness and contributes to their widespread application.
Keyphrases
- heart rate
- healthcare
- cardiovascular disease
- convolutional neural network
- heart rate variability
- machine learning
- deep learning
- blood pressure
- magnetic resonance imaging
- type diabetes
- computed tomography
- magnetic resonance
- coronary artery disease
- social media
- health information
- cardiovascular risk factors
- image quality