Related papers: Analyzing Nursing Assistant Attitudes Towards Empa…
As the aging population increases and the shortage of healthcare workers increases, the need to examine other means for caring for the aging population increases. One such means is the use of humanoid robots to care for social, emotional,…
Background: True cognitive longitudinal decline can be obscured by repeated testing, which is called practice effects (PEs). We developed a modeling framework that aligns participants by baseline and estimates visit-specific PEs…
This paper outlines the EMPATHIC Research & Innovation project, which aims to research, innovate, explore and validate new interaction paradigms and plat-forms for future generations of Personalized Virtual Coaches to assist elderly people…
Well-being is a dynamic construct that evolves over time and fluctuates within individuals, presenting challenges for accurate quantification. Reduced well-being is often linked to depression or anxiety disorders, which are characterised by…
The great behavioral heterogeneity observed between individuals with the same psychiatric disorder and even within one individual over time complicates both clinical practice and biomedical research. However, modern technologies are an…
We investigate the feasibility of inferring emotional states exclusively from physiological signals, thereby presenting a privacy-preserving alternative to conventional facial recognition techniques. We conduct a performance comparison of…
In human interactions, emotion recognition is crucial. For this reason, the topic of computer-vision approaches for automatic emotion recognition is currently being extensively researched. Processing multi-channel electroencephalogram (EEG)…
Dysphonia, a prevalent medical condition, leads to voice loss, hoarseness, or speech interruptions. To assess it, researchers have been investigating various machine learning techniques alongside traditional medical assessments.…
Quality estimation (QE)-the automatic assessment of translation quality-has recently become crucial across several stages of the translation pipeline, from data curation to training and decoding. While QE metrics have been optimized to…
The advent of Artificial Intelligence (AI) tools, such as Large Language Models, has introduced new possibilities for Qualitative Data Analysis (QDA), offering both opportunities and challenges. To help navigate the responsible integration…
Insufficient modeling of human preferences within the reward model is a major obstacle for leveraging human feedback to improve translation quality. Fortunately, quality estimation (QE), which predicts the quality of a given translation…
Artificial intelligence (AI) has significantly improved medical screening accuracy, particularly in cancer detection and risk assessment. However, traditional classification metrics often fail to account for imbalanced data, varying…
Measuring brain activity with electroencephalography (EEG) is mature enough to assess mental states. Combined with existing methods, such tool can be used to strengthen the understanding of user experience. We contribute a set of methods to…
This study demonstrates how anticipated and actual interactions shape the QE of SARs among older adults. The study consisted of two parts: an online survey to explore the anticipated interaction through video viewing of a SAR and an…
There has been a surge in the number and type of AI tools being tested and deployed within both national and local government in the UK, including within the social care sector. Given the many ongoing and planned future developments, the…
Mental health challenges are rising globally, while traditional support services face limited availability and high costs. Large language models offer potential for conversational support, but often lack personalization, empathy, and…
Quantitative Fitness Analysis (QFA) is a high-throughput experimental and computational methodology for measuring the growth of microbial populations. QFA screens can be used to compare the health of cell populations with and without a…
Quality Estimation (QE) is an important component in making Machine Translation (MT) useful in real-world applications, as it is aimed to inform the user on the quality of the MT output at test time. Existing approaches require large…
The paper asserts that emulating empathy in human-robot interaction is a key component to achieve satisfying social, trustworthy, and ethical robot interaction with older people. Following comments from older adult study participants, the…
Millions of users come to online peer counseling platforms to seek support. However, studies show that online peer support groups are not always as effective as expected, largely due to users' negative experiences with unhelpful counselors.…