HILDA - A Health Interaction Log Data Analysis Workflow to Aid Understanding of Usage Patterns and Behaviours

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)
148 Downloads (Pure)

Abstract

Health and wellbeing products and services for individuals are becoming increasingly popular as people realise the benefits provided by lifelogging or quantified-self platforms in such areas as exercise, diet management and mood. However, in addition to the data that users record using these platforms, all user interactions and events can be elusively logged to represent usage. Such user interaction or event logs provide rich and large datasets that can fuel applied artificial intelligence. As products and services based on these digital interaction technologies are taken up across public healthcare provision, should healthcare policy and practice take more cognisance of the opportunities and risks in gathering interaction data? Is ‘healthcare’ ignorant that there is knowledge in such data? Are there differences between event logging in healthcare and other areas such as commerce, media and industry? In order to realise benefits in analysing such data, methods that help ensure consistency, accuracy, data protection, as well as reproducibility of knowledge derived from log data need to be examined. This paper presents methods to explore usage log data and a process workflow followed by a presentation of two real world case studies. The workflow has been coined Health Interaction Log Data Analysis (HILDA) and focuses on data prospecting and machine learning stages to show the opportunities realisable in analysing interactional or event data automatically recorded by digital healthcare services.
Original languageEnglish
Title of host publicationUnknown Host Publication
EditorsFederico Bergenti, Stefania Monica, Paolo Petta
PublisherSociety for the Study of Artificial Intelligence and Simulation of Behaviour
Number of pages6
Publication statusAccepted/In press - 6 Feb 2018
EventThe 2nd Symposium on Social Interactions in Complex Intelligent Systems (SICIS) at Artificial Intelligence and Simulation of Behaviour Convention (AISB-2018) - Liverpool
Duration: 6 Feb 2018 → …

Other

OtherThe 2nd Symposium on Social Interactions in Complex Intelligent Systems (SICIS) at Artificial Intelligence and Simulation of Behaviour Convention (AISB-2018)
Period6/02/18 → …

Keywords

  • Health Interaction Log Data Analysis
  • User Logs
  • Event Log
  • Inter- action Log
  • Data Analytics
  • Machine Learning
  • Data Mining
  • Health Data Analytics
  • Pattern Analysis
  • Behaviour Understanding

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  • Cite this

    Mulvenna, M., Bond, R., Grigorash, A., O'Neill, S., & Ryan, A. (Accepted/In press). HILDA - A Health Interaction Log Data Analysis Workflow to Aid Understanding of Usage Patterns and Behaviours. In F. Bergenti, S. Monica, & P. Petta (Eds.), Unknown Host Publication Society for the Study of Artificial Intelligence and Simulation of Behaviour. http://uir.ulster.ac.uk/39911/2/Acceptance%20of%20paper%20at%20SICISAISB%202018.pdf