Visualisation to explain personal health trends in smart homes.

Forbes, Glenn; Massie, Stewart; Craw, Susan

Abstract

An ambient sensor network is installed in Smart Homes to identify low-level events taking place by residents, which are then analysed to generate a profile of activities of daily living. These profiles are compared to both the resident's typical profile and to known 'risky' profiles to support recommendation of evidence-based interventions. Maintaining trust presents an XAI challenge because the recommendations are not easily interpretable. Trust in the system can be improved by making the decision-making process more transparent. We propose a visualisation workflow which presents the data in clear, colour-coded graphs.

Citation

FORBES, G., MASSIE, S. and CRAW, S. 2021. Visualisation to explain personal health trends in smart homes. Presented at 1st eXplainable artificial intelligence (XAI) in healthcare international workshop 2021 (XAI-Healthcare 2021), 16 June 2021, co-located with 19th Artificial intelligence in medicine (AIME) international conference 2021 (AIME 2021), 15-17 June 2021, [virtual conference]. Hosted on ArXiv [online], article 2109.15125. Available from: https://arxiv.org/abs/2109.15125

• Presentation Conference Type: Conference Paper (unpublished)
• Conference Name: 1st eXplainable artificial intelligence (XAI) in healthcare international workshop 2021 (XAI-Healthcare 2021), co-located with the 19th Artificial intelligence in medicine (AIME) international conference 2021 (AIME 2021)
• Start Date: Jun 16, 2021
• Deposit Date: Oct 11, 2021
• Publicly Available Date: Oct 11, 2021
• Peer Reviewed: Peer Reviewed
• Keywords: Visualisation; Healthcare; Smart home
• Public URL: https://rgu-repository.worktribe.com/output/1447500