Clinical and Instrumental Treatment's Predictors in Subjects With Neurological Diseases Using G-EO Robotic System


Don Carlo Gnocchi Onlus Foundation




Multiple Sclerosis
Parkinson Disease
Acquired Brain Injury


Device: Robotic Assisted Gait Training with G-EO system

Study type


Funder types




Details and patient eligibility


The aim of this work is to elaborate a statistical model to predict the effectiveness of robotic treatment in subjects with neurological diseases. The model will be used to understand which subjects are most responsive to this type of treatment

Full description

In recent years, robotic devices have been used to assist balance and gait rehabilitation of people with neurological disorders. In particular, the G-EO system (Reha Technology AG, Switzerland) is a robotic end-effector device guiding the movement of the feet. It is currently unclear which variables are the predictors of treatment success. Indeed, the effectiveness of the GEO treatment may depends on the characteristics of the treatment itself (instrumental parameters defined by the physiotherapist using the device) and on the characteristics of the subject receiving the treatment. Therefore, it is necessary to measure these clinical and instrumental characteristics to understand which are predictors of treatment effects. Parameters obtained from this assessment can be used to elaborate statistical models. In our study the statistical model will be defined as follows: The change in the primary outcome measure after the robotic treatment will be considered as dependent variable of the model. All the "secondary" clinical outcome measures will be measured only at T0 and will be considered in the model as independent variables, along with the participants characteristics (age, gender, disease, disease duration, falls number, numbers of comorbidity, type of hospitalization) and the treatment characteristics (sessions number, frequency, duration, step length, cadence, gait speed, body weight support, distance traveled). The results of the model will suggest which subjects are most responsive to this type of treatment and which variables can be considered as predictors of the treatment success.


260 estimated patients




18+ years old


No Healthy Volunteers

Inclusion criteria

  • Diagnosis of Multiple Sclerosis, Parkinson Disease, Stroke or acquired brain injury
  • Minimum number of sessions: 10 sessions with the GEO system
  • Minimum frequency of sessions: 2 per week
  • Age ≥ 18 years
  • Ability to walk for at least 10 meters, also with aid
  • Indication of robotic treatment in the therapeutic plan
  • Body size suitable for the robotic device
  • ability to maintain verticality for 7 minutes;
  • ability to maintain the sitting position without support for 30 seconds;

Exclusion criteria

  • severe limitations of articular range of motion;
  • medical problems compromising walking (e.g. fractures, pain, severe osteoporosis or severe spasticity);
  • Presence of skin lesions in the areas of contact with the device;
  • Presence of seizures that may be triggered by the use of the G-EO system.

Trial design

260 participants in 1 patient group

People with neurological disease according to inclusion criteria
People with neurological disease (Multiple Sclerosis, Parkinson Disease, Stroke and acquired brain injuries) will be recruited according to inclusion and exclusion criteria.
Device: Robotic Assisted Gait Training with G-EO system

Trial contacts and locations



Central trial contact

Davide Cattaneo, PhD; Thomass Bowman, PhD

Data sourced from

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