Persuasive Computing Lab

Check out our latest publication with Josteve Adekanbi, Japheth Mumo, Gladwin Irudayaraj, Olumide Thomas Adeleke, Ibukun Okunade, Prof. Rita Orji, PhD and Oladapo Oyebode, PhD

This paper presents HyperCare, an AI-driven, personalized, and adaptive persuasive technology for continuous hypertension prevention and management. HyperCare integrates multimodal sensing of health determinants, including sleep patterns, activity level, body weight, blood glucose, and blood alcohol content, with explainable artificial intelligence and persuasive strategies to deliver personalized, evidence-based interventions in real time. The system uses a retrieval-augmented generation based explainable large language model to analyze health data and provide adaptive recommendations. Through an expert evaluation involving clinicians and simulated hypertension-risk scenarios, HyperCare received high ratings for clinical relevance, transparency and explainability, persuasion, ethics, and usability, demonstrating its potential for continuous and personalized hypertension prevention and management.

You can read the full paper here: https://lnkd.in/ercxQcBJ

Dalhousie University

Check out our latest publication with Olamiposi Olaiya, MSc, Gerry Chan & Prof. Rita Orji, PhD

This systematic review explores how Machine Learning (ML) is being combined with Augmented Reality (AR) and Virtual Reality (VR) in healthcare for disease diagnosis and treatment. We reviewed 43 studies published between 2014 and 2024 and found that the use of AR/VR-ML technologies has increased over time. Most studies focused on VR applications, commonly using Head-Mounted Displays and multiple ML algorithms together. Overall, AR/VR/ML systems show significant potential for supporting capabilities in diagnosing and treating many types of medical conditions; however, a large variability exists among the different studies due to differences in the design and evaluation of the studies.

You can read the full paper here: https://lnkd.in/eEUQq8Jj

Dalhousie University, Dalhousie Computer Science

Check out our latest publication with Grace Ataguba (PhD) and Prof. Rita Orji, PhD

This study reviews how AI helps people develop healthy eating habits (i.e., through personalization based on each person's needs) and adapt its recommendations based on how each individual eats. Most of the AI research used to develop these tools appears to be effective; however, very few studies have followed participants long term to assess the long-term effectiveness of these tools. Some ethical issues regarding privacy and transparency were raised as well, and there is a need for improved research design in the future.

You can read the full paper here: https://lnkd.in/epctrEzQ

Dalhousie University, Dalhousie Computer Science