This paper is in the following e-collection/theme issue:

Advanced Data Analytics in eHealth (203) Wearable Devices and Sensors (1110) 2016 Special Iss "Optimization, Data Mining, and Statistical Management of Bio-data in Medical Industry Informatization" (2) New Technologies (106) Methods and Instruments in Medical Informatics (185)

Published on in Vol 10, No 11 (2022): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40826, first published .
Motion Artifact Reduction in Electrocardiogram Signals Through a Redundant Denoising Independent Component Analysis Method for Wearable Health Care Monitoring Systems: Algorithm Development and Validation

Motion Artifact Reduction in Electrocardiogram Signals Through a Redundant Denoising Independent Component Analysis Method for Wearable Health Care Monitoring Systems: Algorithm Development and Validation

Motion Artifact Reduction in Electrocardiogram Signals Through a Redundant Denoising Independent Component Analysis Method for Wearable Health Care Monitoring Systems: Algorithm Development and Validation

Authors of this article:

Fabian Andres Castaño Usuga1 Author Orcid Image ;   Christian Gissel2 Author Orcid Image ;   Alher Mauricio Hernández1 Author Orcid Image
Article Authors Cited by (5) Tweetations (3) Metrics

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  3. Castaño Usuga F. Evaluation and Sensitivity Analysis of the FitzHugh–Nagumo Model Parameters for Studying Electrical Signals Generated by Different Biological Tissues. Computer Physics Communications 2025:109738 View
  4. Khan A, Ban S, Yeo W, Kim J. A comparative study of flexible electrode design on the performance of flexible wearable electronics. Frontiers in Nanotechnology 2025;7 View
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