Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/13834
Título: New visualization model for large scale biosignals analysis
Autor: Cavaco, Catarina Alexandra da Quinta Silva
Orientador: Gamboa, Hugo
Matias, Ricardo
Palavras-chave: Long-term biosignals
Big data
Biosignals visualization
Biosignals annotation
Medical monitoring
Data de Defesa: Set-2014
Resumo: 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.
URI: http://hdl.handle.net/10362/13834
Designação: Dissertação
Aparece nas colecções:FCT: DF - Dissertações de Mestrado

Ficheiros deste registo:
Ficheiro Descrição TamanhoFormato 
Cavaco_2014.pdf9,73 MBAdobe PDFVer/Abrir

FacebookTwitterDeliciousLinkedInDiggGoogle BookmarksMySpace
Formato BibTex MendeleyEndnote 

Todos os registos no repositório estão protegidos por leis de copyright, com todos os direitos reservados.