Digital-based personalized nutrition assistant system for diabetic inpatients

Abstract

Malnutrition is a significant concern among diabetic inpatients, as it can lead to complications and hinder the management of their condition. Therefore, there is a need to address the dietary needs of these individuals through personalized nutrition interventions. In recent years, the integration of technology in healthcare has opened new avenues for developing innovative solutions. Digital-based personalized nutrition systems offer a promising approach to tailor dietary recommendations according to individual requirements. This system utilizes various technologies, including meal recommendation systems and activity monitoring, to optimize nutritional intake and improve health outcomes. Objective Assess the prevalence of malnutrition and design a digital-based personalized nutrition system for diabetic inpatients. Methods The study collected data from two referral hospitals in Kigali City using a mixed-methods design. Quantitative data were analyzed using SPSS, while qualitative data helped identify system requirements and design considerations. Results The results indicated that 55.3% of the diabetic patients were malnourished, with 6% classified as severely malnourished, 49.3% as having mild to moderate malnutrition, and 44.7% as having normal nutritional status among the 300 patients included in the study. The developed meal recommender system considers local foods, physical activity levels, and glycemic index to provide tailored meal plans. Its strength lies in estimating users' physical activity levels and suggesting meals based on their calorie requirements. Conclusion The study highlights the importance of addressing malnutrition among diabetic inpatients and the potential benefits of a personalized nutrition assistant system in improving their dietary management.

Keywords: Diabetes mellitus, Glycemic Index, Malnutrition, Diabetic inpatients, Meal Recommender VIII