• To conduct a systematic review of existing evidence in regard to AR interventions and digital tools for falls and balance physiotherapy, in order to identify factors that will optimise patient compliance and to adapt the eHealth solutions accordingly.
  • To evaluate existing data about the effect of standard of care in order to calculate economic costs and benefits.

  • To unify the existing research and clinical databases, identify gaps in data needed to address the needs of special populations, develop synthetic (reference) data to overcome this barrier and define the structure needed for AI/ML models.
  • Develop innovative and appropriate AI models from the complex multifactorial falls/balance disorders data and related socioeconomic costs that will automatically link to patient-specific, cost-effective interventions.
  • Develop AI-based predictive analytics for treatment outcomes, side effects and adverse events at baseline and throughout the entire duration of the intervention.


  • Develop and validate an economic model to calculate cost-effectiveness of treatment taking into account availability of resources in different healthcare settings as well as differences between healthcare systems in order to adapt technology accordingly.
  • Develop and conduct health professional’s profiling for optimal matching with patients targeting increased compliance.

  • Engage with stakeholders and representatives of the entire ecosystem (patients, clinicians, developers, health stakeholders) to define and analyse qualitatively user requirements in dedicated focus groups towards research co-creation during the entire project, to ensure engagement with the system (professional/patient) and compliance and adoption within the clinical pathways.
  • To validate AI-based DSS functionality in a rigorous way to establish its coherence, validity, usability and performance compared to standard of care.


The impact of TeleRehaB project will be based on:

  • Project’s pathways towards impact
  • Health care professionals employ safer and evidence-based clinical decision support systems for affordable treatment, including home-based care.
  • Health care professionals better predict patients’ (long-term) response, including adverse side effects of a specific personalised treatment.
  • Health care professionals employ safer and evidence-based clinical decision support systems for affordable treatment, including home-based care.
  • Health care professionals better predict patients’ (long-term) response, including adverse side effects of a specific personalised treatment.
  • Impact on the EU health care system.
  • Impact on regulations, EU government policy makers, the European Innovation Partnership on Active and Healthy Ageing (AHA) and personalized healthcare.
  • Ethical impact

    Psychological Impact.

  • Prediction of patient adherence.

  • Impact for patients with long Covid-19.

  • Measures to maximise impact – Dissemination, exploitation and communication.


WP1: Project management and coordination:

The main objectives of WP1 are to keep a well-organized communication between consortium partners, efficient financial administration of project resources, on time release of deliverables respecting project constraints and ensuring results quality, monitoring of partners activities and timely conflict resolution.

WP2: User-centric platform design:

The objective of this WP is to guide the development of the overall platform and its key user interface-interaction components using a user-centric design approach. This method from the field of human-computer interaction is based on analyses of user requirements, design, development and evaluation of prototypes in an iterative way.

WP3: Platform development:

The objectives of this WP are to develop different components of the platform, including the AR environments forbalance physiotherapy and cognitive games, the activity exercise monitoring at home, continuous monitoring inside and outside home, the cloud infrastructure and the primary user interface tools (i.e. expert dashboard, patient app).

WP4: AI-based DSS models and advanced analytics

This WP will cover AI models and ML algorithms for intelligent analytics that will provide the DSS functionality of the platform, including prognostic and risk assessment factors, compliance with AR technology, personalised intervention planning, exercise performance monitoring and scoring.

WP5: Clinical validation study:

In WP5 a comprehensive analysis of existing guidelines for balance rehabilitation on new cases including post- stroke, MCI and long Covid-19 patients will be performed. Additionally, the protocol for the clinical validation study will be finalised to obtain the ethical approvals and allow the actual study to begin patient recruitment.

WP6: Impact and socio-economic analysis

The objective is to produce an overall estimation of the socioeconomic direct impact in healthcare and indirect impact to develop the ICT sectors of AI-based approach in healthcare Europe or some countries of EU.

WP7: Legal and ethics:

Within WP7 the legal and ethical issues throughout the whole duration of the project will be monitored and updated every 12 months. Privacy and security issues will be covered here as well along with proper execution of internal processing of personal data.

WP8: Dissemination and communication activities, exploitation and sustainability

The objectives of this task are to perform the evidence based dissemination of all TeleRehaB DSS activities, provide a concrete plan for open innovation and the exploitation and sustainability plan of the platform.

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