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New visualization model for large scale biosignals analysis
| Nome: | Descrição: | Tamanho: | Formato: | |
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| 9.5 MB | Adobe PDF |
Orientador(es)
Resumo(s)
Benefits of long-term monitoring have drawn considerable attention in healthcare.
Since the acquired data provides an important source of information to clinicians and
researchers, the choice for long-term monitoring studies has become frequent.
However, long-term monitoring can result in massive datasets, which makes the analysis
of the acquired biosignals a challenge. In this case, visualization, which is a key point
in signal analysis, presents several limitations and the annotations handling in which
some machine learning algorithms depend on, turn out to be a complex task.
In order to overcome these problems a novel web-based application for biosignals
visualization and annotation in a fast and user friendly way was developed. This was
possible through the study and implementation of a visualization model. The main process
of this model, the visualization process, comprised the constitution of the domain
problem, the abstraction design, the development of a multilevel visualization and the
study and choice of the visualization techniques that better communicate the information
carried by the data. In a second process, the visual encoding variables were the study target.
Finally, the improved interaction exploration techniques were implemented where
the annotation handling stands out.
Three case studies are presented and discussed and a usability study supports the
reliability of the implemented work.
Descrição
Palavras-chave
Long-term biosignals Big data Biosignals visualization Biosignals annotation Medical monitoring