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X3S: A multi-modal approach to monitor and assess stress through human-computer interaction

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Resumo:Stress evaluation is nowadays gaining an increasing importance in a time in which inter-individual competition continuously pushes us to be better. Indeed, in the workplace, in the academia or in many other contexts there is increasing pressure for better performance, which pushes us forward but also wears us out. This phenomenon has been studied from many different angles, including psychology, medicine or occupational dynamics. In a medical or biological context, stress is a physical, mental, or emotional factor that causes bodily or mental tension, which can cause or influence the course of many medical conditions including psychological conditions such as depression and anxiety. In these cases, individuals are under an increasing demand for performance, driving them to be under constant pressure, and consequently to present variations in their levels of stress. To mitigate this condition, this paper proposes to add a new dimension in human–computer interaction through the development of a distributed multi-modal framework approach entitled X3S, which aims to monitor and assess the psychological stress of computer users during high-end tasks, in a non-intrusive and non-invasive way, through the access of soft sensors activity (e.g. task performance and human behaviour). This approach presents as its main innovative key the capacity to validate each stress model trained for each individual through the analysis of cortisol and stress assessment survey data. Overall, this paper discusses how groups of medical students can be monitored through their interactions with the computer. Its main aim is to provide a stress marker that can be effectively used in large numbers of users and without inconvenience
Autores principais:Gonçalves, Filipe Manuel
Outros Autores:Carneiro, Davide Rua; Pêgo, José M.; Novais, Paulo
Assunto:Human-computer Interaction Behavioural & Performance Patterns Machine Learning Stress Monitoring & Assessment Behavioural & performance patterns Stress monitoring & assessment Ciências Médicas::Medicina Básica Ciências Naturais::Ciências da Computação e da Informação
Ano:2018
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
Descrição
Resumo:Stress evaluation is nowadays gaining an increasing importance in a time in which inter-individual competition continuously pushes us to be better. Indeed, in the workplace, in the academia or in many other contexts there is increasing pressure for better performance, which pushes us forward but also wears us out. This phenomenon has been studied from many different angles, including psychology, medicine or occupational dynamics. In a medical or biological context, stress is a physical, mental, or emotional factor that causes bodily or mental tension, which can cause or influence the course of many medical conditions including psychological conditions such as depression and anxiety. In these cases, individuals are under an increasing demand for performance, driving them to be under constant pressure, and consequently to present variations in their levels of stress. To mitigate this condition, this paper proposes to add a new dimension in human–computer interaction through the development of a distributed multi-modal framework approach entitled X3S, which aims to monitor and assess the psychological stress of computer users during high-end tasks, in a non-intrusive and non-invasive way, through the access of soft sensors activity (e.g. task performance and human behaviour). This approach presents as its main innovative key the capacity to validate each stress model trained for each individual through the analysis of cortisol and stress assessment survey data. Overall, this paper discusses how groups of medical students can be monitored through their interactions with the computer. Its main aim is to provide a stress marker that can be effectively used in large numbers of users and without inconvenience

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