PAL · Project

Robot Companion Helps Children with Diabetes Learn Self-Management Before Adolescence

healthTestedTRL 5

Imagine a friendly robot buddy that sits with a child who has Type 1 diabetes and helps them learn how to manage their condition — like a patient tutor that never gets tired. The robot works alongside a phone app and educational games to teach kids aged 7 to 14 about their diet, insulin, and daily routines, so by the time they hit their teenage years, they can handle it themselves. It also gives parents and doctors a dashboard to track progress without hovering over the child. The idea is to shift responsibility gradually from caregiver to child, making diabetes management feel less like a chore and more like a shared adventure.

By the numbers

7-14

Target age range of children with Type 1 diabetes

EUR 4,515,460

EU funding for development and testing

Partners in the development consortium

Countries involved in testing (DE, IT, NL, UK)

Total project deliverables produced

Demo deliverables with evaluated prototypes

The business problem

What needed solving

Children with Type 1 diabetes need to learn complex self-management skills — tracking blood sugar, adjusting insulin, managing diet — before they hit adolescence, when adherence typically drops sharply. Current mobile health apps provide fragmented support and fail to deliver the prolonged, personalized guidance that builds lasting habits. The result is increased risk of serious complications and reduced life expectancy for patients who never master their regimen.

The solution

What was built

The project built a social robot and its mobile avatar that act as a child's companion for diabetes self-management, connected to a common knowledge-base and reasoning engine. It includes a diabetes diary, educational quizzes, sorting games, an Authoring & Control tool for health professionals, and a Monitor & Inform tool for parents — all evaluated through 4 demo prototypes and longitudinal field experiments.

Audience

Who needs this

Pediatric diabetes clinics looking to improve patient self-management outcomesDigital health companies developing chronic disease management platforms for childrenHealth insurers seeking evidence-based interventions to reduce long-term diabetes complication costsEducational robotics companies wanting to enter the healthcare marketHospital innovation departments exploring AI-assisted patient education

Business applications

Who can put this to work

Pediatric Healthcare

enterprise

Target: Children's hospitals and diabetes clinics

If you are a pediatric diabetes clinic struggling with patient adherence among children aged 7 to 14 — this project developed a social robot and avatar system with educational quizzes, a diabetes diary, and sorting games that help children build self-management habits. The system was tested with prototypes across 4 countries with 12 partners, and includes an Authoring & Control tool so your clinicians can customize the experience per patient.

Digital Health Technology

SME

Target: Health app developers and medtech companies

If you are a digital health company building chronic disease management tools — this project created a knowledge-base and reasoning engine that connects a social robot, a mobile avatar, and multiple health apps into one integrated system. With 40 deliverables including evaluated prototypes for diabetes regimen adherence, this offers a proven architecture you could license or adapt for other pediatric chronic conditions beyond diabetes.

Health Insurance

enterprise

Target: Health insurers with pediatric chronic disease programs

If you are a health insurer looking to reduce long-term complication costs for young Type 1 diabetes patients — this project demonstrated that early self-management training for children aged 7 to 14 can help establish adequate shared patient-caregiver responsibility before adolescence. Backed by EUR 4,515,460 in EU funding and longitudinal field experiments, the PAL system offers an evidence-based intervention that could lower your claims from diabetes complications.

Frequently asked

Quick answers

What would it cost to implement or license this technology?

The PAL system was developed with EUR 4,515,460 in EU funding across 12 partners over 4 years. Licensing or implementation costs would need to be negotiated directly with the coordinator (TNO in the Netherlands). Based on available project data, no commercial pricing has been published.

Can this scale beyond a research setting to real clinics?

The project conducted longitudinal field experiments to assess behavioral change benefits on patients' health conditions. With 4 demo deliverables showing evaluated prototypes, the system has been tested in structured environments. However, scaling to routine clinical use would likely require further product development and regulatory clearance for medical devices.

Who owns the intellectual property and can I license it?

The project was coordinated by TNO (Netherlands Organisation for Applied Scientific Research), a major Dutch research organization. IP rights are typically shared among the 12 consortium partners according to their grant agreement. Licensing inquiries should be directed to TNO as the lead partner.

Does this work only for diabetes or can it be adapted to other conditions?

The PAL system was designed specifically for Type 1 diabetes in children aged 7 to 14. However, the underlying architecture — a social robot connected to a knowledge-base with educational apps — is described as extendable. The reasoning mechanism and co-design methodology could potentially be adapted for other pediatric chronic conditions requiring self-management.

What evidence exists that this actually improves health outcomes?

The project planned longitudinal field experiments to assess benefits of behavioral change on patients' health conditions and the impact on caregivers. Four demo deliverables confirm that prototypes were built and evaluated, covering diabetes regimen adherence, shared child-caregiver responsibility, and knowledge awareness. Specific clinical outcome numbers are not available in the public project data.

Is the robot hardware commercially available?

Based on available project data, the PAL system uses a social robot alongside a mobile avatar and health applications. The project focused on the software intelligence, knowledge-base, and reasoning mechanism rather than manufacturing custom hardware. The specific robot platform used would need to be confirmed with the consortium.

Consortium

Who built it

The PAL consortium brings together 12 partners from 4 countries (Germany, Italy, Netherlands, UK), led by TNO — one of Europe's largest applied research organizations. The mix includes 3 research institutes, 2 universities, and 2 industry partners (both SMEs), with 5 other organizations likely including hospitals and patient associations. The 17% industry ratio is low, which is typical for health research projects and suggests the technology is still closer to research than to market. For a business looking to commercialize this, the strong research backbone (TNO, universities) means solid science, but you would need to bring your own go-to-market capability.

NEDERLANDSE ORGANISATIE VOOR TOEGEPAST NATUURWETENSCHAPPELIJK ONDERZOEK TNOCoordinator · NL
IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINEparticipant · UK
DEUTSCHES FORSCHUNGSZENTRUM FUR KUNSTLICHE INTELLIGENZ GMBHparticipant · DE
FONDAZIONE CENTRO SAN RAFFAELEparticipant · IT
OSPEDALE SAN RAFFAELE SRLthirdparty · IT
TECHNISCHE UNIVERSITEIT DELFTparticipant · NL

How to reach the team

TNO (Netherlands Organisation for Applied Scientific Research) is the coordinator. Contact their health innovation department for licensing or partnership inquiries.

Order a report on this consortium See NEDERLANDSE ORGANISATIE VOOR TOEGEPAST NATUURWETENSCHAPPELIJK ONDERZOEK TNO profile →

Next steps

Talk to the team behind this work.

Want an introduction to the PAL research team? SciTransfer can connect you with the right people at TNO and help you evaluate this technology for your specific use case.

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