Sleep classification using Consumer Sleep Technologies and AI: A review of the current landscape.

Classifying sleep stages in real-time represents considerable potential, for instance in enabling interactive noise masking in noisy environments when persons are in a state of light sleep or to support clinical staff in analyzing sleep patterns etc. However, the current gold standard for classifying sleep stages, Polysomnography (PSG), is too cumbersome to apply outside controlled hospital settings and requires manual as well as highly specialized knowledge to classify sleep stages. Using data from Consumer Sleep Technologies (CSTs) to inform machine learning algorithms represent a promising opportunity for automating the process of classifying sleep stages, also in settings outside the confinements of clinical expert settings. This study reviews 27 papers that use CSTs in combination with Artificial Intelligence (AI) models to classify sleep stages. AI models and their performance are described and compared to synthesize current state of the art in sleep stage classification with CSTs. Furthermore, gaps in the current approaches are shown and how these AI models could be improved in the near-future. Lastly, the challenges of designing interactions for users that are asleep are highlighted pointing towards avenues of more interactive sleep interventions based on AI-infused CSTs solutions.

Breadth, depth and visibility: a design guide for information architectures aimed at elderly users.

This study extends previous research by exploring the quality of the interaction experienced by a group of elderly participants interacting with a healthcare portal when applying a touch screen remote control. This is compared to a standard remote control with physical buttons.

Touch, and you will gaze: elderly and youngers' use of remote controls in interacting with a healthcare portal.

This study extends previous research by exploring the quality of the interaction experienced by a group of elderly participants interacting with a healthcare portal when applying a touch screen remote control. This is compared to a standard remote control with physical buttons.