A Framework for AI-enabled Proactive mHealth with Automated Decision-making for a User’s Context

Muhammad Sulaiman, Anne Håkansson, Randi Karlsen

2022

Abstract

Health promotion is to enable people to take control over their health. Digital health with mHealth empowers users to establish proactive health, ubiquitously. The users shall have increased control over their health to improve their life by being proactive. To develop proactive health with the principles of prediction, prevention, and ubiquitous health, artificial intelligence with mHealth can play a pivotal role. There are various challenges for establishing proactive mHealth. For example, the system must be adaptive and provide timely interventions by considering the uniqueness of the user. The context of the user is also highly relevant for proactive mHealth. The context provides parameters as input along with information to formulate the current state of the user. Automated decision-making is significant with user-level decision-making as it enables decisions to promote well-being by technological means without human involvement. This paper presents a design framework of AI-enabled proactive mHealth that includes automated decision-making with predictive analytics, Just-in-time adaptive interventions and a P5 approach to mHealth. The significance of user-level decision-making for automated decision-making is presented. Furthermore, the paper provides a holistic view of the user's context with profile and characteristics. The paper also discusses the need for multiple parameters as inputs, and the identification of sources e.g., wearables, sensors, and other resources, with the challenges in the implementation of the framework. Finally, a proof-of-concept based on the framework provides design and implementation steps, architecture, goals, and feedback process. The framework shall provide the basis for the further development of AI-enabled proactive mHealth.

Paper Citation

in Harvard Style

Sulaiman M., Håkansson A. and Karlsen R. (2022). A Framework for AI-enabled Proactive mHealth with Automated Decision-making for a User’s Context. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 5: HEALTHINF; ISBN 978-989-758-552-4, SciTePress, pages 111-124. DOI: 10.5220/0010843200003123

in Bibtex Style

@conference{healthinf22,
author={Muhammad Sulaiman and Anne Håkansson and Randi Karlsen},
title={A Framework for AI-enabled Proactive mHealth with Automated Decision-making for a User’s Context},
booktitle={Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 5: HEALTHINF},
year={2022},
pages={111-124},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010843200003123},
isbn={978-989-758-552-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 5: HEALTHINF
TI - A Framework for AI-enabled Proactive mHealth with Automated Decision-making for a User’s Context
SN - 978-989-758-552-4
AU - Sulaiman M.
AU - Håkansson A.
AU - Karlsen R.
PY - 2022
SP - 111
EP - 124
DO - 10.5220/0010843200003123
PB - SciTePress