Published February 21, 2020 | Version v1
Poster Open

Medical evaluation as gold standard to control iPrognosis application derived data for early Parkinson's disease detection

  • 1. Department of Neurology, Technical University Dresden, Dresden, Germany
  • 2. 3rd Department of Neurology, Aristotle University of Thessaloniki, Thessaloniki, Greece.
  • 3. King's College Hospital NHS Foundation Trust, London, United Kingdom
  • 4. Department of Electrical & Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece
  • 5. 3rd Department of Neurology, Aristotle University of Thessaloniki, Thessaloniki, Greece
  • 6. Fraunhofer IAIS, Schloß Birlinghoven, Sankt Augustin, Germany
  • 7. Faculdade de Motricidade Humana, Universidade de Lisboa, Lisbon, Portugal.
  • 8. Microsoft Innovation Center Greece, Athens, Greece
  • 9. Information Technologies Institute, CERTH, Thessaloniki, Greece
  • 10. Karolinska Institutet, Stockholm, Sweden.
  • 11. Faculdade de Motricidade Humana, Universidade de Lisboa, Lisbon, Portugal

Description

Smartphones have the ability of longitudinal, unobtrusive, remote real-life
recognition and monitoring of people's behavior and of specific behavioral pattern.
The i-PROGNOSIS approach is promosing as both, the iPrognosis App derived
behavioral pattern and the medical evaluation of Parkinson`s disease symptoms
by a movement disorders specialist as gold standard differentiate patients with
Parkinson`s disease and healthy controls.

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Poster_iPrognosis_MDS Nice 2019_FINAL.pdf

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Additional details

Funding

i-PROGNOSIS – Intelligent Parkinson eaRly detectiOn Guiding NOvel Supportive InterventionS 690494
European Commission