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ALAMEDA · Project

AI Toolkit That Personalizes Rehabilitation for Parkinson's, MS, and Stroke Patients

healthPilotedTRL 6
alamedaproject.eu

Imagine your doctor could predict how your brain disease will progress and adjust your rehab exercises in real time — like a GPS that reroutes when traffic changes. ALAMEDA built an AI system that does exactly that for people recovering from Parkinson's, Multiple Sclerosis, and Stroke. It uses wearable sensors and smart algorithms to track how patients respond to treatment, then recommends what to change before problems get worse. The system was tested in three real-world clinical pilots across Europe.

By the numbers
800 billion EUR/year
Cost of brain disorders in Europe
60%
Share of brain disorder costs that are direct costs
6,053,812 EUR
EU funding received
3
Real-world clinical pilots conducted
16
Consortium partners across 8 countries
5
SMEs in the consortium
The business problem

What needed solving

Brain diseases like Parkinson's, Multiple Sclerosis, and Stroke cost Europe an estimated 800 billion euros per year, with 60% of that going to direct treatment costs. Current rehabilitation programs follow generic protocols that don't adapt to individual patient progress, leading to slower recovery, wasted resources, and missed early warning signs of deterioration.

The solution

What was built

The project delivered the ALAMEDA AI Toolkit in two versions (1.0 and 2.0) — a working software system that uses machine learning, deep learning, and IoT sensor data to provide personalized prediction, prevention, and intervention for Parkinson's, MS, and Stroke rehabilitation. The toolkit was validated in 3 real-world clinical pilots.

Audience

Who needs this

Digital health companies building rehabilitation or remote monitoring platformsHealth insurers covering neurological rehabilitation costsHospital networks and rehabilitation clinics treating brain disease patientsElderly care facility operators managing Parkinson's and stroke patientsMedical device companies developing wearable neurological monitoring sensors
Business applications

Who can put this to work

Digital Health & MedTech
mid-size
Target: Medical software companies building rehabilitation or remote patient monitoring platforms

If you are a digital health company dealing with one-size-fits-all rehabilitation protocols that fail to adapt to individual patients — this project developed the ALAMEDA AI Toolkit, a working software system that uses machine learning and IoT sensor data to personalize treatment plans for brain disease patients. It was validated across 3 real-world pilots with 16 consortium partners, giving you a ready-made AI engine to integrate into your existing platform.

Insurance & Healthcare Payers
enterprise
Target: Health insurers and managed care organizations covering neurological rehabilitation

If you are a health insurer struggling with the rising costs of brain disease rehabilitation — estimated at 800 billion euros per year in Europe — this project built evidence-based AI tools that predict patient outcomes and optimize treatment intensity. By identifying which interventions work best for which patients, you can reduce unnecessary treatments and focus spending on what actually improves recovery.

Elderly Care & Assisted Living
any
Target: Care facility operators and home care service providers managing neurological patients

If you are an elderly care provider dealing with Parkinson's or stroke patients whose conditions change unpredictably between doctor visits — this project created connected sensor-based monitoring that tracks patient status continuously and alerts caregivers to deterioration early. The system was designed with active patient engagement in mind, making it practical for real care settings, not just research labs.

Frequently asked

Quick answers

What would it cost to license or integrate this technology?

The project was funded with EUR 6,053,812 in EU contribution across 16 partners. Licensing terms would need to be negotiated directly with the consortium coordinator. With 5 SMEs and 8 industry partners involved, there are likely multiple commercialization paths available.

Can this scale to handle thousands of patients across multiple facilities?

The ALAMEDA AI Toolkit went through two development iterations (v1.0 and v2.0), suggesting progressive refinement for real-world use. The system was designed around IoT and connected devices, which inherently support distributed deployment. However, scaling beyond the 3 pilot sites would require additional validation and infrastructure planning.

Who owns the intellectual property and how can we access it?

IP is shared among the 16 consortium partners across 8 countries, following standard EU Horizon 2020 rules. The coordinator is a Greek research institute (EREVNITIKO PANEPISTIMIAKO INSTITOUTO). Licensing discussions should start with the coordinator, but specific technology components may be owned by different partners.

Does this meet medical device regulations in Europe?

The project was designed around value-based health principles and clinical use cases. As a research project, the AI Toolkit would likely need additional regulatory steps (CE marking under MDR) before commercial deployment as a medical device. The 3 real-world pilots provide clinical evidence that would support a regulatory submission.

How long before this could be deployed in our organization?

The project closed in December 2023 with a working AI Toolkit v2.0. Integration timeline depends on your existing infrastructure — companies with IoT-enabled patient monitoring could move faster. Based on available project data, expect 12-18 months for regulatory clearance and integration work before commercial deployment.

Does it integrate with existing hospital IT systems and electronic health records?

ALAMEDA was built to work with both retrospective data sources and real-time IoT sensor data, suggesting compatibility considerations were part of the design. The consortium included medical software vendors, which increases the likelihood of standard healthcare IT integration. Specific integration protocols should be confirmed with the technical partners.

Consortium

Who built it

ALAMEDA's 16-partner consortium across 8 countries is well-balanced for commercialization: half the partners (8) come from industry, and 5 are SMEs — meaning smaller, agile companies with a direct interest in turning results into products. The mix of 4 universities and 3 research organizations provides the clinical and scientific credibility needed in healthcare, while the industry partners (including medical software vendors and healthcare market experts) ensure the technology was built with real-world deployment in mind. The geographic spread across Southern and Northern Europe (Greece, Spain, Italy, Norway, UK, Romania, Cyprus, Luxembourg) gives broad market access for future rollout.

How to reach the team

The coordinator is EREVNITIKO PANEPISTIMIAKO INSTITOUTO SYSTIMATON EPIKOINONION KAI YPOLOGISTON, a Greek research institute. Contact details can be found via the project website or CORDIS portal.

Order a report on this consortiumSee EREVNITIKO PANEPISTIMIAKO INSTITOUTO SYSTIMATON EPIKOINONION KAI YPOLOGISTON profile →
Next steps

Talk to the team behind this work.

Want an introduction to the ALAMEDA consortium? SciTransfer can connect you with the right technical or business partner for your specific use case. Contact us for a one-page technology brief.

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