A carregar...
Publicação
Taxonomy and Real-Time Classification of Artifacts During Biosignal Acquisition
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 17.77 MB | Adobe PDF |
Orientador(es)
Resumo(s)
This article investigates electrocardiogram (ECG) acquisition artifacts often occurring in experiments due to human negligence or environmental influences, such as electrode detachment, misuse of electrodes, and unanticipated magnetic field interference, which are not easily noticeable by humans or software during acquisition. Such artifacts usually result in useless and irreparable signals; therefore, it would be a great help to research if the problems are detected during the acquisition process to alert experimenters instantly. We put forward a taxonomy of real-time artifacts during ECG acquisition, provide the simulation methods of each category, collect and share a 10-subject data corpus, and investigate machine learning (ML) solutions with a proposal of appropriate handcrafted features that reach an offline recognition rate of 90.89% in a five-best-output person-independent (PI) leave-one-out cross-validation (LOOCV). We also preliminarily validate the real-time applicability of our approach.
Descrição
Publisher Copyright: © 2001-2012 IEEE. This work involved human subjects or animals in its research. Approval of all ethical and experimental procedures and protocols was granted by the Ethics Committee, College of Biomedical Engineering and Instrument Science, Zhejiang University
Palavras-chave
Artifact biosignal electrocardiogram (ECG) electrocardiography pattern recognition real-time system signal quality Instrumentation Electrical and Electronic Engineering