SenseCare · Project

AI Platform That Reads Patient Emotions Through Sensors to Improve Dementia Care

healthTestedTRL 5

Imagine if a doctor could tell how a dementia patient is really feeling — not just from what they say, but from sensors picking up on their emotions and mental state in real time. That's what SenseCare built: a cloud system that collects data from multiple sensors, uses machine learning to understand a patient's emotional and cognitive condition, and feeds that insight back to caregivers. Think of it like a smart mood ring for healthcare, except it actually works and runs on serious AI. The goal is to catch problems earlier and give patients better, more personalized treatment.

By the numbers

€250 Billion

Projected annual cost of dementia care in Europe by 2030

€504,000

EU contribution to the project

Consortium partners across 4 countries

SMEs involved in the consortium

Complete use case test pilot releases with validation

Platform infrastructure software releases

The business problem

What needed solving

Dementia and cognitive impairment are among the fastest-growing healthcare costs in Europe, projected to reach over €250 Billion by 2030. Caregivers today rely on periodic check-ins and subjective observation to assess how patients are doing — they often miss emotional distress, confusion, or cognitive decline between visits. There is no standard way to continuously monitor a patient's emotional and mental state and feed that intelligence into treatment decisions.

The solution

What was built

The team built a cloud-based affective computing platform that processes and fuses data from multiple sensors to provide emotional and cognitive intelligence for healthcare systems. Concrete outputs include two releases of the platform infrastructure software, two validated use case test pilot releases (for dementia care and connected health), medical informatics applications with resource adaptors, and a dedicated psychology and affective computing portal for the research community.

Audience

Who needs this

Nursing home chains and dementia care facility operators looking for better patient monitoringDigital health startups building remote patient monitoring or telemedicine platformsWearable device manufacturers wanting to add clinical-grade emotional intelligence to their sensorsHospital IT departments evaluating AI-powered patient assessment toolsHealth insurance companies exploring predictive analytics for cognitive decline

Business applications

Who can put this to work

Elder Care & Assisted Living

mid-size

Target: Nursing home chains and dementia care facilities

If you are a nursing home operator dealing with the challenge of monitoring dementia patients around the clock — this project developed a cloud-based sensor platform that reads patients' emotional and cognitive states in real time. It was tested in two use case pilots focused on dementia care and connected health. With dementia care costs projected to exceed €250 Billion by 2030, early detection of distress or cognitive decline through this system could reduce emergency interventions and improve care quality.

Digital Health & Telemedicine

SME

Target: Connected health platform providers and remote patient monitoring companies

If you are a digital health company building remote monitoring solutions — this project created a cloud operating system that fuses multiple sensor data streams into emotional and cognitive intelligence. The platform went through two full release cycles with documented validation. Integrating affective computing into your existing telehealth product could differentiate you in the growing connected health market.

Medical Device & Wearables

SME

Target: Wearable sensor manufacturers targeting healthcare applications

If you are a wearable device maker looking to move beyond fitness tracking into clinical applications — this project built the AI middleware that turns raw sensor data into actionable patient insights. The consortium included 2 industry partners and 2 SMEs who helped validate the technology. Your hardware combined with this intelligence layer could open up the medical-grade monitoring market.

Frequently asked

Quick answers

What would it cost to license or adopt this technology?

The project was funded with €504,000 under the MSCA-RISE scheme, which focuses on staff exchange and knowledge transfer. Licensing terms would need to be negotiated directly with the consortium led by Munster Technological University. As an MSCA-RISE project, IP arrangements may be more flexible than large-scale industrial projects.

Can this work at industrial scale in real care facilities?

The platform was designed as a cloud-based system capable of processing multiple sensor data streams simultaneously, which suggests scalability was considered from the start. Two iterations of use case test pilots were completed and validated. However, scaling from pilot to facility-wide deployment would require additional engineering and compliance work.

Who owns the intellectual property?

IP is typically shared among consortium partners under Horizon 2020 rules, with the coordinator Munster Technological University likely holding key rights. The consortium included 2 SMEs and 2 industry partners across 4 countries, so joint ownership agreements are probable. Specific licensing terms would need to be discussed with the coordinator.

Does this comply with healthcare data regulations like GDPR?

The project processed sensitive health and emotional data, which falls under strict GDPR and health data regulations. Based on available project data, the platform was tested within EU-based pilot environments. Any commercial deployment would need to ensure full compliance with medical device regulations and health data privacy requirements.

How long would integration take with existing hospital systems?

The project delivered two releases of medical informatics applications designed to run on the SenseCare platform, with documented resource adaptors for integration. Based on the deliverable descriptions, the platform uses a service-based architecture that connects through adaptors. Integration timelines would depend on your existing infrastructure but the adaptor approach suggests modularity.

What kind of sensors does this actually work with?

The platform was designed to process and fuse multiple sensory data streams — the exact sensor types used in the pilots are not specified in the available project summaries. The architecture is described as sensor-agnostic, built to handle diverse inputs through its cloud processing layer. Specific sensor compatibility would need to be confirmed with the development team.

Is this still actively maintained or developed?

The project officially ended in December 2019. The consortium completed all planned deliverables including two platform releases and two pilot iterations. Whether the technology has been further developed since then would need to be confirmed with Munster Technological University or the industry partners involved.

Consortium

Who built it

The SenseCare consortium is a compact team of 5 partners from 4 countries (Ireland, Germany, Spain, UK), with a healthy 40% industry ratio — 2 industry players including 2 SMEs alongside 2 universities and 1 research organization. This mix means the technology was developed with real commercial input from day one, not just in an academic bubble. The coordinator is Munster Technological University in Ireland, a well-regarded institution for applied technology research. The relatively small €504,000 budget under the MSCA-RISE scheme means this was primarily a knowledge-exchange and capacity-building project rather than a full product development effort. For a business looking to adopt or build on this technology, the SME involvement is a positive signal that practical market needs were considered during development.

MUNSTER TECHNOLOGICAL UNIVERSITYCoordinator · IE
FTK-FORSCHUNGSINSTITUT FUR TELEKOMMUNIKATION UND KOOPERATION EVparticipant · DE
INMARK EUROPA SAparticipant · ES
GLOBIT-GLOBALE INFORMATIONSTECHNIKGMBHparticipant · DE
UNIVERSITY OF ULSTERparticipant · UK

How to reach the team

Munster Technological University, Ireland — reach out to the Computer Science or Health Informatics department

Order a report on this consortium See MUNSTER TECHNOLOGICAL UNIVERSITY profile →

Next steps

Talk to the team behind this work.

Want to explore how SenseCare's emotion-sensing AI could fit your care facility or health platform? SciTransfer can connect you directly with the research team and help evaluate fit for your specific use case.

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