ViTA: Virtual Trainer for Aging

  • Pietro Leo
  • Grazia D’OnofrioEmail author
  • Daniele Sancarlo
  • Francesco Ricciardi
  • Michele De Petris
  • Francesco Giuliani
  • Giuseppe Ciarambino
  • Silvia Peschiera
  • Angelo Failla
  • Fabrizio Renzi
  • Antonio Greco
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 540)


ViTA (Virtual Training for Aging) is an experimental system that aims to strengthen the memory of the people who suffer the first symptoms of dementia and feel the risk of losing their ability to recall significant events in their lives due to the progression of the disease. ViTA exploits concepts of the reminiscence and behavioral therapies to improve cognitive, emotional and social functioning by supporting patients with dementia. Caregivers interact with ViTA to collect fragments of memory and organize them into a knowledge map in which each fragment is linked to the other through emotionally significant stories. A conversational interface allows the navigation of the knowledge map referring to each patient. Thanks to the Artificial Intelligence algorithms implemented in ViTA, patients can access the system to review their memories and stories, leveraging on a conversational interface based on speech and textual interaction modalities in addition to a more traditional interactive interface. ViTA will be tested and verified over the next months by a group of elderly people with early dementia symptoms at the Geriatrics Department and Long Term Care facilities of the Casa Sollievo della Sofferenza Research Hospital and it is implemented on top of the IBM Watson platform integrated with software tools derived by previous research experiences.


Dementia Memory loss Caregivers Quality of life Quality of care Isolation reduction 



The research described in this article has been developed thanks to the collaboration between the IBM Italia Foundation and the IRCCS Casa Sollievo della Sofferenza Research Hospital within the IBM Impact Grants Program.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Research & Business UnitIBMItalyItaly
  2. 2.Geriatric Unit, Department of Medical SciencesFondazione Casa Sollievo della SofferenzaSan Giovanni RotondoItaly
  3. 3.The BioRobotics InstituteScuola Superiore Sant’AnnaPontederaItaly
  4. 4.ICT, Innovation and Research UnitFondazione Casa Sollievo della SofferenzaSan Giovanni Rotondo, FoggiaItaly

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