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EU FP7-ICT-2011-7 (grant number 288516)


Sinziana Mazilu
Michael Hardegger

This project is supervised by Prof. Gerhard Tröster.

Closed-loop system for personalized and at-home rehabilitation of people with Parkinson's Disease

People with Parkinson’s disease (PD) suffer from motor and cognitive impairments that severely impact mobility, fall risk, and multiple key aspects of functional independence.

Until recently, treatment goals focused almost exclusively on symptom relief, but exciting recent work by CuPiD partners and others has demonstrated that motor learning and rehabilitation principles can be effective even in the presence of PD. It is critical to make these rehab-like therapies accessible to patients in their home-setting since they need continuous training, as PD is a chronic neurodegenerative disease.

In CuPiD we develop an ICT-enabled solution to the rehabilitation of patients with PD in their home setting, tailoring the solution to target mobility, cognitive function and debilitating PD symptoms such as freezing of gait.

Our Objective: Wearable Technologies for Freezing of Gait Rehabilitation

Within CuPiD we develop a new system for a rehabilitation program that will be carried out in the at home environment and will be aimed to alleviate Freezing of Gait (FoG) in patients with Parkinson's Disease (PD). We work on the following components of the target system:

  • A wearable freezing of gait assistant component. This component devised around a smartphone and wearable sensors detects the freezing of gait and provides user feedback designed to encourage the recovery of functional gait. 
  • A key research component is to shift from freeze detection to freezing of gait prediction, by capitalizing on recent findings linking changes in physiological and motor  parameters to upcoming onset of freeze.
  • An indoor location tracking system, that supports location-aware FoG assistance in home environments. Our approach is based on Simultaneous Localization And Mapping (SLAM), which supports fully stand-alone, wearable tracking, without the need for pre-installed infrastructure and prior maps. Therefore, the system is ideally suited for deployment in home-assistance scenarios.

All components form part of a larger tele-rehabilitation program at home, which is evaluated in a 12 month clinical evaluation.

Other contributors


CuPiD Official Website


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