Affective brain–computer music interfacing

We aim to develop and evaluate an affective brain–computer music interface (aBCMI) for modulating the affective states of its users. Approach. An aBCMI is constructed to detect a userʼs current affective state and attempt to modulate it in order to achieve specific objectives (for example, making the user calmer or happier) by playing music which is generated according to a specific affective target by an algorithmic music composition system and a casebased reasoning system. The system is trained and tested in a longitudinal study on a population of eight healthy participants, with each participant returning for multiple sessions. Main results. The final online aBCMI is able to detect its users current affective states with classification accuracies of up to 65% (3 class, p < 0.01) and modulate its userʼs affective states significantly above chance level (p < 0.05). Significance. Our system represents one of the first demonstrations of an online aBCMI that is able to accurately detect and respond to userʼs affective states. Possible applications include use in music therapy and entertainmen

User emotional interaction processor: a tool to support the development of GUIs through physiological user monitoring

Ever since computers have entered humans' daily lives, the activity between the human and the digital ecosystems has increased. This increase encourages the development of smarter and more user-friendly human-computer interfaces. However, to test these interfaces, the means of interaction have been limited, for the most part restricted to the conventional interface, the "manual" interface, where physical input is required, where participants who test these interfaces use a keyboard, mouse, or a touch screen, and where communication between participants and designers is required. There is another method, which will be applied in this dissertation, which does not require physical input from the participants, which is called Affective Computing. This dissertation presents the development of a tool to support the development of graphical interfaces, based on the monitoring of psychological and physiological aspects of the user (emotions and attention), aiming to improve the experience of the end user, with the ultimate goal of improving the interface design. The development of this tool will be described. The results, provided by designers from an IT company, suggest that the tool is useful but that the optimized interface generated by it still has some flaws. These flaws are mainly related to the lack of consideration of a general context in the interface generation process.Desde que os computadores entraram na vida diária dos humanos, a atividade entre o ecossistema humano e o digital tem aumentado. Este aumento estimula o desenvolvimento de interfaces humano-computador mais inteligentes e apelativas ao utilizador. No entanto, para testar estas interfaces, os meios de interação têm sido limitados, em grande parte restritos à interface convencional, a interface "manual", onde é preciso "input" físico, onde os participantes que testam estas interface, usam um teclado, um rato ou um "touch screen", e onde a comunicação dos participantes com os designers é necessária. Existe outro método, que será aplicado nesta dissertação, que não necessita de "input" físico dos participantes, que se denomina de "Affective Computing". Esta dissertação apresenta o desenvolvimento de uma ferramenta de suporte ao desenvolvimento de interfaces gráficas, baseada na monitorização de aspetos psicológicos e fisiológicos do utilizador (emoções e atenção), visando melhorar a experiência do utilizador final, com o objetivo último de melhorar o design da interface. O desenvolvimento desta ferramenta será descrito. Os resultados, dados por designers de uma empresa de IT, sugerem que esta é útil, mas que a interface otimizada gerada pela mesma tem ainda algumas falhas. Estas falhas estão, principalmente, relacionadas com a ausência de consideração de um contexto geral no processo de geração da interface

Role of Emotions and Aesthetics in ICT Usage for Underserved Communities: A NeuroIS Investigation

Usability and efficiency has received lot of attention in terms of ICT usage and attitude however non instrumental factors like emotions and aesthetics and their impact on ICT usage attitude and performance has not been extensively tested. Further underserved communities are focused communities that have limitations in terms of formal and functional literacy and technology experience. Aesthetics have been shown to be an important predictor of usage but this has not been tested in underserved communities. Also positive emotions have been linked to greater ICT usage as well as aesthetic experience. Measurement of factors like emotions, aesthetic preferences and ICT usage has so far been restricted to questionnaires however we propose to use objective measures like brain imaging technique (EEG) to supplement existing methodologies. The current paper is a research in progress that addresses potential role of aesthetics and emotions for understanding aesthetic preferences and ICT usages in underserved communities

A novel Big Data analytics and intelligent technique to predict driver's intent

Modern age offers a great potential for automatically predicting the driver's intent through the increasing miniaturization of computing technologies, rapid advancements in communication technologies and continuous connectivity of heterogeneous smart objects. Inside the cabin and engine of modern cars, dedicated computer systems need to possess the ability to exploit the wealth of information generated by heterogeneous data sources with different contextual and conceptual representations. Processing and utilizing this diverse and voluminous data, involves many challenges concerning the design of the computational technique used to perform this task. In this paper, we investigate the various data sources available in the car and the surrounding environment, which can be utilized as inputs in order to predict driver's intent and behavior. As part of investigating these potential data sources, we conducted experiments on e-calendars for a large number of employees, and have reviewed a number of available geo referencing systems. Through the results of a statistical analysis and by computing location recognition accuracy results, we explored in detail the potential utilization of calendar location data to detect the driver's intentions. In order to exploit the numerous diverse data inputs available in modern vehicles, we investigate the suitability of different Computational Intelligence (CI) techniques, and propose a novel fuzzy computational modelling methodology. Finally, we outline the impact of applying advanced CI and Big Data analytics techniques in modern vehicles on the driver and society in general, and discuss ethical and legal issues arising from the deployment of intelligent self-learning cars

Applications of Affective Computing in Human-Robot Interaction: state-of-art and challenges for manufacturing

The introduction of collaborative robots aims to make production more flexible, promoting a greater interaction between humans and robots also from physical point of view. However, working closely with a robot may lead to the creation of stressful situations for the operator, which can negatively affect task performance. In Human-Robot Interaction (HRI), robots are expected to be socially intelligent, i.e., capable of understanding and reacting accordingly to human social and affective clues. This ability can be exploited implementing affective computing, which concerns the development of systems able to recognize, interpret, process, and simulate human affects. Social intelligence is essential for robots to establish a natural interaction with people in several contexts, including the manufacturing sector with the emergence of Industry 5.0. In order to take full advantage of the human-robot collaboration, the robotic system should be able to perceive the psycho-emotional and mental state of the operator through different sensing modalities (e.g., facial expressions, body language, voice, or physiological signals) and to adapt its behaviour accordingly. The development of socially intelligent collaborative robots in the manufacturing sector can lead to a symbiotic human-robot collaboration, arising several research challenges that still need to be addressed. The goals of this paper are the following: (i) providing an overview of affective computing implementation in HRI; (ii) analyzing the state-of-art on this topic in different application contexts (e.g., healthcare, service applications, and manufacturing); (iii) highlighting research challenges for the manufacturing sector

Low-cost methodologies and devices applied to measure, model and self-regulate emotions for Human-Computer Interaction

En aquesta tesi s'exploren les diferents metodologies d'anàlisi de l'experiència UX des d'una visió centrada en usuari. Aquestes metodologies clàssiques i fonamentades només permeten extreure dades cognitives, és a dir les dades que l'usuari és capaç de comunicar de manera conscient. L'objectiu de la tesi és proposar un model basat en l'extracció de dades biomètriques per complementar amb dades emotives (i formals) la informació cognitiva abans esmentada. Aquesta tesi no és només teòrica, ja que juntament amb el model proposat (i la seva evolució) es mostren les diferents proves, validacions i investigacions en què s'han aplicat, sovint en conjunt amb grups de recerca d'altres àrees amb èxit.En esta tesis se exploran las diferentes metodologías de análisis de la experiencia UX desde una visión centrada en usuario. Estas metodologías clásicas y fundamentadas solamente permiten extraer datos cognitivos, es decir los datos que el usuario es capaz de comunicar de manera consciente. El objetivo de la tesis es proponer un modelo basado en la extracción de datos biométricos para complementar con datos emotivos (y formales) la información cognitiva antes mencionada. Esta tesis no es solamente teórica, ya que junto con el modelo propuesto (y su evolución) se muestran las diferentes pruebas, validaciones e investigaciones en la que se han aplicado, a menudo en conjunto con grupos de investigación de otras áreas con éxito.In this thesis, the different methodologies for analyzing the UX experience are explored from a user-centered perspective. These classical and well-founded methodologies only allow the extraction of cognitive data, that is, the data that the user is capable of consciously communicating. The objective of this thesis is to propose a methodology that uses the extraction of biometric data to complement the aforementioned cognitive information with emotional (and formal) data. This thesis is not only theoretical, since the proposed model (and its evolution) is complemented with the different tests, validations and investigations in which they have been applied, often in conjunction with research groups from other areas with success

Incorporating Cognitive Neuroscience Techniques to Enhance User Experience Research Practices

User Experience (UX) involves every interaction that customers have with products, and it plays a crucial role in determining the success of a product in the market. While there are numerous methods available in literature for assessing UX, they often overlook the emotional aspect of the user\u27s experience. As a result, cognitive neuroscience methods are gaining popularity, but they have certain limitations such as difficulty in collecting neurophysiological data, potential for errors, and lengthy procedures. This article aims to examine the most effective research practices using cognitive neuroscience techniques and develop a standardized procedure for conducting UX research. To achieve this objective, the study conducts a comprehensive review of UX research that employs cognitive neuroscience methods published between 2017 and 2022