According to a United Nations’ report on World Population Aging (2015), the number of people in the world aged 60 or over is projected to grow to 2.1 billion by year 2050. Aging can come with various complexities and challenges, such as decline in physical, cognitive and mental health of a person. These changes affect a person’s everyday life, resulting in decreased social participation, lack of physical activity, and vulnerability to injury and disability, that can be exacerbated by the occurrence of various acute health events, such strokes, or long term illnesses.
The field of assistive technology amalgamates several multi-disciplinary areas including computer science, rehabilitation engineering, data mining, clinical studies, health care, and psychology. The idea of assistive technological solutions is to promote independent, active and healthy aging with a specific focus on older adults, and those living with mild cognitive impairments.
Collecting and mining health data using assistive technology devices is a challenging task. Leveraging Artificial Intelligence (AI) techniques and building novel machine learning (ML) models is essential to make advancements in the field of aging and technology. Building AI models on health data will facilitate independent assisted living, promote healthy and active lifestyle, and manage rehabilitation routines effectively. To reason about the collected data, to classify it and to detect abnormalities, new AI tools and methods are required.
With this workshop, we will bring together researchers from different sub-fields of AI, in general, agent based modelling and machine learning to identify and approach the ARIAL-related problems. We will also facilitate discussion, interaction, and comparison of approaches, methods, and ideas related to the domain of aging and technology.