Digital-Based Personalized Nutrition Assistant System for Diabetic Inpatients

Abstract

Background

Malnutrition is a pressing issue for diabetic inpatients, complicating their treatment. Personalized nutritional interventions are essential to meet their dietary needs. Leveraging healthcare technology, digital-based personalized nutrition systems offer a solution. These systems use meal recommendation and activity monitoring to optimize nutrition and health outcomes.

Objectives

The study's objective was to assess and design the system’s requirements and develop a digital-based personalized nutrition system for diabetic inpatients.

Methods

Qualitative methods involve in-depth interviews to extract the information needed for designing the architecture and clinical requirements using the Harries Benedict equation It focused on two referral hospitals in Kigali, Agile development was used with the phases encompassed planning, requirements analysis, design, building, and testing.

Results

A meal recommender system was created, considering sugar levels, local foods, physical activity, and glycemic index to offer customized plans based on calorie needs, to maintain stable blood glucose and reduce sudden spikes. Most of the participants affirm this system as personalized meal recommendations, food trigger identification, and potential cost savings from the prototype system for diabetic inpatients.

Conclusion

Addressing malnutrition in diabetic inpatients is crucial, and personalized nutrition systems show promise in enhancing their dietary management.