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Publicação
Usabiliphy: Criação e Validação de um Dataset para Estudar a Relação entre a Usabilidade Percebida e Sinais Fisiológicos
| Nome: | Descrição: | Tamanho: | Formato: | |
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| 6.01 MB | Adobe PDF |
Orientador(es)
Resumo(s)
The techniques used to assess usability, user experience, emotions, etc., perceived by users
when using applications are predominantly based on questionnaires. Although these questionnaires yield solid results, they can become monotonous, tiresome, and even demanding, potentially triggering negative feelings in users and consequently affecting the reliability of the questionnaires.
One way to overcome these issues would be to infer usability, user experience, and perceived
emotions from users’ physiological signals while they use the applications. To achieve this inference, it is necessary to have reliable information that allows for a correlation between physiological signals and usability and user experience measures. This work represents a first step in
this direction, and our goal is to create a dataset composed of users’ physiological signals and the
results of standard questionnaires while they interact with interactive applications. To accomplish
this, we conducted two user experiments in which participants performed a set of tasks in interactive applications while we collected their physiological signals and their responses to standard
questionnaires.
At the end of the study, we validated the data through statistical analysis, which revealed that
there was no statistical differences between the two experiments. Based on this validation, we
constructed a dataset that includes physiological signals (electroencephalography, photoplethysmography, accelerometer, gyroscope) and scores from standard questionnaires (System Usability
Scale, User Experience Questionnaire Short, Single Ease Question, NASA Task Load Index, Usability Metric for User Experience Lite, Self-Assessment Manikin).
This dataset will enable future research to investigate the relationship between these two types
of data and subsequently create models to infer perceived usability from physiological signals,
eliminating the need for questionnaire completion, improving user testing sessions, and reducing
their duration.
Descrição
Tese de mestrado, Engenharia Informática , 2023, Universidade de Lisboa, Faculdade de Ciências
Palavras-chave
Usabilidade Sinais Fisiológicos Dataset Experiência de Utilização Emoções Teses de mestrado - 2023