publication . Other literature type . Conference object . 2019

Towards unobtrusive Parkinson's disease detection via motor symptoms severity inference from multimodal smartphone-sensor data

Iakovakis, Dimitrios; Hadjidimitriou, Stelios; Charisis, Vasileios; Kyritsis, Konstantinos; Papadopoulos, Alexandros; Stadtschnitzer, Michael; Jaeger, Hagen; Dagklis, Ioannis; Bostantjopoulou, Sevasti; Katsarou, Zoe; ...
Open Access
  • Published: 01 Oct 2019
  • Publisher: Zenodo
Objective: To provide clinically-corroborated evidence of the Parkinson’s disease (PD) diagnostic potential of machine learning-based approaches for motor symptoms severity inference via multimodal data, passively captured during the natural use of smartphones. Background: PD symptoms can be mild in the early stages and they usually go unnoticed, leaving the disease undiagnosed for years [1]. Subtle motor manifestations may start five to six years prior to PD clinical diagnosis and thereafter progress quickly [2]. Motor impairment affects daily activities and can severely impact patients’ quality over the course of the disease. Information derived from mobile el...
Funded by
Intelligent Parkinson eaRly detectiOn Guiding NOvel Supportive InterventionS
  • Funder: European Commission (EC)
  • Project Code: 690494
  • Funding stream: H2020 | RIA
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Other literature type . 2019
Provider: Datacite
Conference object . 2019
Provider: ZENODO
Other literature type . 2019
Provider: Datacite
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