Galli, Manuela
(Electronics, Information and Bioengineering Department, Politecnico di Milano, 20133 Milan, Italy)
,
Pacifici, Ilaria
(Electronics, Information and Bioengineering Department, Politecnico di Milano, 20133 Milan, Italy)
,
Cimolin, Veronica
(Electronics, Information and Bioengineering Department, Politecnico di Milano, 20133 Milan, Italy)
,
Francesca De Pandis, Maria
(San Raffaele Cassino Hospital, Tosinvest Sanità)
,
Vagnini, Alessandro
(, Roma, Italy)
,
Pera, Domenica Le
(Electronics, Information and Bioengineering Department, Politecnico di Milano, 20133 Milan, Italy)
,
Sova, Ivan
(IRCCS “)
,
Albertini, Giorgio
(San Raffaele Pisana”)
,
Stocchi, Fabrizio
(, Tosinvest Sanità)
,
Franceschini, Marco
(, Roma, Italy)
The recovery of walking is a crucial aspect in rehabilitation of patients with Parkinson's disease (PD). The aim of this research was to quantify the effects of an end-effector robotic rehabilitation locomotion training in a group of PD patients using 3D gait analysis (GA). In particular, spatiotemp...
The recovery of walking is a crucial aspect in rehabilitation of patients with Parkinson's disease (PD). The aim of this research was to quantify the effects of an end-effector robotic rehabilitation locomotion training in a group of PD patients using 3D gait analysis (GA). In particular, spatiotemporal parameters and kinematics variables by means of synthetic indexes (Gait Profile Score, GPS, and its Gait Variable Scores GVSs) were computed from GA at baseline, before the treatment (T0), and at the end of the rehabilitative program (T1). At T1 statistically significant improvements were found particularly in terms of spatio-temporal parameters (velocity, step length and cadence). No changes were observed as for GPS, while a trend towards improvement was found in terms of GVSs of pelvis and hip on the frontal plane. From these results, the use of Gait analysis has allowed to provide quantitative data about the end-effector robotic rehabilitation evidencing those joints more sensible to the treatment. The robotic locomotion training seems to improve gait pattern in patients with PD and in particular, the effect is on spatio-temporal parameters.
The recovery of walking is a crucial aspect in rehabilitation of patients with Parkinson's disease (PD). The aim of this research was to quantify the effects of an end-effector robotic rehabilitation locomotion training in a group of PD patients using 3D gait analysis (GA). In particular, spatiotemporal parameters and kinematics variables by means of synthetic indexes (Gait Profile Score, GPS, and its Gait Variable Scores GVSs) were computed from GA at baseline, before the treatment (T0), and at the end of the rehabilitative program (T1). At T1 statistically significant improvements were found particularly in terms of spatio-temporal parameters (velocity, step length and cadence). No changes were observed as for GPS, while a trend towards improvement was found in terms of GVSs of pelvis and hip on the frontal plane. From these results, the use of Gait analysis has allowed to provide quantitative data about the end-effector robotic rehabilitation evidencing those joints more sensible to the treatment. The robotic locomotion training seems to improve gait pattern in patients with PD and in particular, the effect is on spatio-temporal parameters.
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