Case Study

AI-based food intake monitoring for Type 2 diabetes management

Evidenze Health Group (Grupo Pulso) partnered with LogMeal to integrate AI-driven food recognition technology into their digital diabetes coaching platform, enabling automated & precise dietary tracking for patients with Type 2 Diabetes.

Background & Objectives:

Type 2 Diabetes (T2D) is a major chronic condition globally, requiring strict control of carbohydrate intake and close dietary monitoring to maintain healthy blood glucose levels. Traditional self-reported food logging methods are often inaccurate, time-consuming, and ineffective for supporting high-quality clinical decisions.

To overcome these limitations, Evidenze Health Group (Grupo Pulso) partnered with LogMeal to integrate AI-driven food recognition technology into their digital diabetes coaching platform, enabling automated & precise dietary tracking for patients with Type 2 Diabetes.

Program Objectives:

Enable accurate, real-time monitoring of food intake based on personal data.
Provide automated carbohydrate and nutrient analysis to support glycemic control
Reduce the workload on healthcare professionals through automation
Improve patient engagement via intuitive photo-based tracking
Validate the solution in hospital settings in Spain and Turkey

Initial Assessment

Existing dietary tracking methods relied on manual entry, which proved burdensome and prone to error
Healthcare professionals required better-quality data to make precise dietary adjustments
The need for a digital solution that would be easy to adopt by patients and seamlessly integrate into clinical workflows
LogMeal was chosen for its advanced AI food recognition API and compatibility with mobile apps

Workflow:

Patients took photos of their meals using an integrated mobile app
LogMeal’s AI engine performed real-time recognition of:
Dishes and ingredients
Portion sizes and food groups

Professional Workflow:

Weekly reviews of patient intake reports
Focused monitoring of carbohydrates, glycemic load, and fat intake
Alerts were triggered when nutritional thresholds were exceeded
Professionals could dynamically adjust dietary recommendations based on real intake
Full nutritional breakdown (energy, carbs, protein, fat, 37 nutrients)
Data was instantly shared with professionals for analysis and support

Results and value of logmeal in the program

The integration of LogMeal AI significantly improved the efficiency and effectiveness of dietary management for T2D patients:

Higher accuracy than traditional self-reported methods
Access to real-time dietary data, improving clinical decision-making
Reduced time spent on manual analysis by dietitians and physicians
Enhanced personalization of dietary plans based on true consumption
Increased patient engagement with easy photo-based tracking
Validated in clinical environments in Spain and Turkey, confirming system reliability and usability in clinical practice.

Conclusion

This collaboration between Evidenze Health Group and LogMeal demonstrates how AI-powered food recognition can revolutionize chronic disease management, particularly in Type 2 Diabetes care, where dietary precision is essential.

By providing healthcare professionals with real-time, objective nutritional data, and offering patients an engaging, intuitive tool for meal tracking, the solution strengthens clinical care pathways and lays the foundation for broader deployment in digital health and disease prevention programs.

partners and collaborators

HEALTH & NUTRITION REFERRALS

Joan Escudero
Digital Health Director at Evidenze Group
Linkedin

“Food intake monitoring for people with diabetes type 2 according to personal data” Validated in hospitals in Spain and Turkey.