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As the population of older adults increases, there is a growing need for support for them to age in place. This is exacerbated by the growing number of individuals struggling with cognitive decline and shrinking number of youth who provide…
Assistance in collaborative manipulation is often initiated by user instructions, making high-level reasoning request-driven. In fluent human teamwork, however, partners often infer the next helpful step from the observed outcome of an…
This paper presents a method for indexing human ac- tivities in videos captured from a wearable camera being worn by patients, for studies of progression of the dementia diseases. Our method aims to produce indexes to facilitate the…
Action understanding, encompassing action detection and anticipation, plays a crucial role in numerous practical applications. However, untrimmed videos are often characterized by substantial redundant information and noise. Moreover, in…
Our research focuses on analysing human activities according to a known behaviorist scenario, in case of noisy and high dimensional collected data. The data come from the monitoring of patients with dementia diseases by wearable cameras. We…
Assistive technologies for the visually impaired have evolved to facilitate interaction with a complex and dynamic world. In this paper, we introduce AIris, an AI-powered wearable device that provides environmental awareness and interaction…
The emergence of an ageing population is a significant public health concern. This has led to an increase in the number of people living with progressive neurodegenerative disorders like dementia. Consequently, the strain this is places on…
Data pre-processing is one of the most time consuming and relevant steps in a data analysis process (e.g., classification task). A given data pre-processing operator (e.g., transformation) can have positive, negative or zero impact on the…
The delivery of mental health interventions via ubiquitous devices has shown much promise. A conversational chatbot is a promising oracle for delivering appropriate just-in-time interventions. However, designing emotionally-aware agents,…
We aim to help users estimate the state of the world in tasks like robotic teleoperation and navigation with visual impairments, where users may have systematic biases that lead to suboptimal behavior: they might struggle to process…
Emotion prediction is the field of study to understand human emotions. Existing methods focus on modalities like text, audio, facial expressions, etc., which could be private to the user. Emotion can be derived from the subject's…
Objective: This research aims to develop a lifestyle intervention system, called MoveSense, that forecasts a patient's activity behavior to allow for early and personalized interventions in real-world clinical environments. Methods: We…
We present an online system for real time recognition of actions involving objects working in online mode. The system merges two streams of information processing running in parallel. One is carried out by a hierarchical self-organizing map…
Physiological sensors are gaining the attention of manufacturers and users. As denoted by devices such as smartwatches or the newly released Kinect 2 -- which can covertly measure heartbeats -- or by the popularity of smartphone apps that…
Wearables like smartwatches or wrist bands equipped with pervasive sensors enable us to monitor our physiological signals. In this study, we address the question whether they can help us to recognize our emotions in our everyday life for…
Evaluating recommender systems remains challenging due to the gap between offline metrics and real user behavior, as well as the scarcity of interaction data. Recent work explores large language model (LLM) agents as synthetic users, yet…
Humans are able to intuitively deduce actions that took place between two states in observations via deductive reasoning. This is because the brain operates on a bidirectional communication model, which has radically improved the accuracy…
In response to the social issue of the increasing number of elderly vulnerable groups going missing due to the aggravating aging population in China, our team has developed a wearable anti-loss device and intelligent early warning system…
Machine learning has shown successes for complex learning problems in which data/parameters can be multidimensional and too complex for a first-principles based analysis. Some applications that utilize machine learning require human…
The automatic, sensor-based assessment of challenging behavior of persons with dementia is an important task to support the selection of interventions. However, predicting behaviors like apathy and agitation is challenging due to the large…