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Individual differences in brain activity hinder the online application of electroencephalogram (EEG)-based brain computer interface (BCI) systems. To overcome this limitation, this study proposes an online adaptation algorithm for unseen…
In contrast to many other domains, recommender systems in health services may benefit particularly from the incorporation of health domain knowledge, as it helps to provide meaningful and personalised recommendations catering to the…
In this project, and through an understanding of neuronal system communication, A novel model serves as an assistive technology for locked-in people suffering from Motor neuronal disease (MND) is proposed. Work was done upon the potential…
Virtual health counselors offer the potential to provide users with information and counseling in complex areas such as disease management and health education. However, ensuring user engagement is challenging, particularly when the volume…
The human brain provides a range of functions such as expressing emotions, controlling the rate of breathing, etc., and its study has attracted the interest of scientists for many years. As machine learning models become more sophisticated,…
Digital life, a form of life generated by computer programs or artificial intelligence systems, it possesses self-awareness, thinking abilities, emotions, and subjective consciousness. Achieving it involves complex neural networks,…
Personalization is the process of fitting a model to patient data, a critical step towards application of multi-physics computational models in clinical practice. Designing robust personalization algorithms is often a tedious,…
Increasingly, human behavior is captured on mobile devices, leading to an increased interest in automated human activity recognition. However, existing datasets typically consist of scripted movements. Our long-term goal is to perform…
This paper presents a design of agent-based intelligent HCI (iHCI) system using collaborative information for MR to improve user experience and information security based on context-aware computing. In order to implement target awareness…
In many mobile health interventions, treatments should only be delivered in a particular context, for example when a user is currently stressed, walking or sedentary. Even in an optimal context, concerns about user burden can restrict which…
Artificial intelligence chatbots are the vanguard in technology-based intervention to change people's behavior. To develop intervention chatbots, the first step is to understand natural language conversation strategies in human…
Interactive AI systems, such as recommendation engines and virtual assistants, commonly use static user profiles and predefined rules to personalize interactions. However, these methods often fail to capture the dynamic nature of user…
The traditional user-centered design process can hardly keep up with the ever faster technical development and increasingly diverse user preferences. As a solution, we propose to augment the tried-and-tested approach of conducting user…
With the continuous development of machine learning technology, major e-commerce platforms have launched recommendation systems based on it to serve a large number of customers with different needs more efficiently. Compared with…
Mental health challenges among young adults, are on the rise, necessitating effective solutions such as digital mental health interventions (DMHIs). Despite their promise, DMHIs face significant adoption barriers, including low initial…
With continuous glucose monitoring (CGM), data-driven models on blood glucose prediction have been shown to be effective in related work. However, such (CGM) systems are not always available, e.g., for a patient at home. In this work, we…
AI-driven precision oncology has the transformative potential to reshape cancer treatment by leveraging the power of AI models to analyze the interaction between complex patient characteristics and their corresponding treatment outcomes.…
Developments in Brain Computer Interfaces (BCIs) are empowering those with severe physical afflictions through their use in assistive systems. Common methods of achieving this is via Motor Imagery (MI), which maps brain signals to code for…
Obesity is a critical healthcare issue affecting the United States. The least risky treatments available for obesity are behavioral interventions meant to promote diet and exercise. Often these interventions contain a mobile component that…
Evaluating different training interventions to determine which produce the best learning outcomes is one of the main challenges faced by instructional designers. Typically, these designers use A/B experiments to evaluate each intervention;…