Novel energy balance tracking to support personalised AI health coaching: a real-world evaluation of the ENHANCE framework
Abstract
BACKGROUND: Energy balance (EB) is the key determinant of fat gain, yet accurate EB tracking is difficult outside laboratory settings. Traditional methods are burdensome (e.g. food-logs) or lack daily resolution (e.g. body weight monitoring), limiting suitability for integration with free-living AI-powered health coaching. OBJECTIVE: To introduce ENHANCE-a novel framework prioritising interpretability and temporal accuracy-and demonstrate its use as a low-burden, accurate method for tracking EB using smart devices and minimal self-report, suitable for AI coaching. METHODS: This 4-week observational study spanned the Christmas to New Year 2024/25 festive period. Participants submitted daily blinded body weight measurements via Wi-Fi scales and EB-related questions via a mobile app, taking
Fields of Study & Subjects
Machine Learning in Healthcare
Mental Health Research Topics
Digital Mental Health Interventions
Publication details
- Journal / source
- International Journal of Obesity
- Publisher
- Springer Science and Business Media LLC
- Volume
- 50
- Issue
- 8
- Pages
- 1846–1851
- Publication date
- 12 May 2026
- Language
- EN