Project SeniorCare

Main focus: we will build and trial a 5G-enabled tele-health assistant that combines wearable biosignals, facial/voice emotion analysis and large-language-model (LLM) dialogue to deliver timely reminders, empathetic conversation and gamified cognitive exercises that help older adults live safely and independently.

Tele-health today is fragmented: reminder apps handle medication schedules, fall-detection cameras raise alarms, smartwatches stream heart-rate data, and a few social robots (e.g. ElliQ, Paro) offer scripted conversation. None of these solutions suggest emotion recognition with wearable biosignals and an adaptive LLM that can shift tone, suggest cognitive games, or call an emergency if needed. Even high-profile concepts such as Tesla’s Optimus humanoid robot are still prototype-only, far from affordable and not designed for geriatric care. Our project fills these gaps by delivering a single, integrated pipeline from sensor to secure 5G edge AI to empathetic dialogue and cognitive support.

Europe’s share of citizens 65+ will exceed 32 % by 2050. Shortages of long-term-care staff and rising loneliness demand scalable digital support. A multi-country pilot is essential to train and test algorithms in different languages, cultures and connectivity conditions.

By project end we deliver a prototype that: (1) monitors seniors health and heart rate variability; (2) recognises real-time emotions from face, voice and context; (3) adapts LLM dialogue tone accordingly for empathetic responses; (4) runs over low-latency 5G edge connection; (5) captures cognitive assessment metrics for clinician review. For Lithuania this opens an export-ready eHealth product line; Portugal embeds AI in SNS community care; Canada validates edge-health in remote regions; New Zealand gains an inclusive pilot for ageing-in-place programmes.

CELTIC-NEXT relevance: the work advances AI & Big-Data pillars (emotion analytics, LLM fine-tuning), Smart Cities & e-Health (remote monitoring), Security (GDPR-compliant edge encryption) and Green-ICT (reducing travel by remote check-ins).

Major visible results: a field-tested, 5G-enabled telehealth prototype ready for commercialisation, open-access emotion dataset for seniors, secure 5G/6G tele-health platform, four Q1-Q2 journal papers, four international-conference demos, one workshop, and inputs to HL7-FHIR and ISO / IEC 30141 (IoT Reference Architecture) for AI-based eldercare. Project results will be submitted to ISO TC 314 (Ageing Societies), IEEE P7000 (Ethical AI), 3GPP SA3 (5G health-data security) and HL7 workgroups for remote-patient monitoring. As for the future perspective, SMEs (Optitecha, Visual Thinking, Embedded Works, Gluu) will refine the prototype into marketable SaaS platforms and training services, while universities embed findings in curricula and follow-on Horizon or national grant proposals.