Clinical trial NCT02711566: Robot-based Rehabilitation of Upper Limb Impairment in Multiple Sclerosis
Official title: Robot-based Assessment and Therapy in the Treatment of Upper Limb Impairment in Multiple Sclerosis: a Multi-center, Randomised Controlled Trial
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Multiple Sclerosis
Keywords: Rehabilitation
Robot-assisted therapy
Lead sponsor: Fondazione Don Carlo Gnocchi Onlus
Sponsor class: OTHER
Collaborators: name: University of Genova
name: Azienda Sanitaria Locale 3 Genovese
First posted: 2016-03-17
Enrollment: 41
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: TREATMENT

Brief summary: Robot-assisted therapy has proven effective in the neuromotor rehabilitation of eg stroke survivors. Robots can be programmed to interact with patients by guiding their movements, by monitoring their performance and by quantifying the type and degree of their impairment.

A distinctive element of multiple sclerosis is the involvement of a variety of functional systems, in a way that is highly subject-specific. This requires a personalization of treatment, and continuous adaptation to changes in condition. This points to a need for integrating patient assessment, definition of rehabilitation protocols, their administration and the assessment of their outcome.

The goal of this study is to assess, in persons with MS, the efficacy of a type of robot-assisted training that was specifically designed to counteract incoordination and muscle weakness (typical of MS), tailored to individual type and degree of impairment, when compared to simple movement training.

Detailed description: In recent years, the potential of robots in the treatment of persons with motor disabilities has raised considerable interest. These devices may interact with patients by assisting or perturbing their movements, may monitor their performance and even quantify their impairment. Clinical trials involving stroke survivors clearly demonstrated that robot-therapy results in improved motor control. More recently, robot-therapy has been applied to other pathologies. A pilot study carried out by the proponents suggested that Multiple Sclerosis (MS) subjects with predominantly cerebellar symptoms may indeed benefit from robot-therapy. MS subjects with different symptoms may benefit from robot therapy as well, but the variety of symptoms and degrees of impairment that is typical of MS suggests that robots may fully show their potential if therapy is tailored on the individual subjects.

In this study, the proponents aim at extending the results of the above mentioned pilot study to MS subjects with a wider variety of impairments. Based on previous studies on robot therapy with MS subjects and stroke survivors, the proponents will develop and test a robot training exercise that is specifically designed to deal with incoordination and/or muscle weakness. In a randomised controlled trial, the proponents will then assess the possible contribution of this form of robot-therapy to the rehabilitation of MS subjects.

A population of clinically definite MS subjects with different degrees of upper limb impairment was randomised into 2 groups: (i) Haptic training and (ii) Sensorimotor training.

Haptic training was based on a robot-assisted exercise protocol specifically designed to treat cerebellar and motor symptoms in persons with MS by counteracting, respectively, incoordination and muscle weakness. The exercise is based on a motor task - interaction with a virtual mass-spring system under the effect of a resistive load - that requires sophisticated coordination skills. Task difficulty (the time constant of the mass-spring system) and the magnitude of the resistive load (stiffness magnitude of the resistive spring) were automatically adjusted to the individual subjects' upper limb impairment.

In Sensorimotor training, the task is exactly the same, but the robot generates no forces. Hand and target position are displayed on the computer screen. This group allowed quantifying the specific contribution of robot assistance to sensorimotor recovery (if any). Both groups performed 8-10 therapy sessions (1 hour/each, 2-3 times per week). Treatment outcome was assessed in terms of the Nine-Hole Peg Test (9HPT) and the ARAT scores.

Eligibility criteria: Inclusion:

* definite Multiple sclerosis, stable phase of the disease
* no relapses or worsening \>1 in the Expanded Disability Status Scale in the last three months,
* Expanded Disability Status Scale\<7.5,
* Ashworth score at the upper limb lower than 2,
* Nine-Hole Peg Test between 30 s and 180 s

Exclusion:

* previous treatment with robot therapy,
* presence of severe nystagmus,
* visual acuity less than 4/10
* major orthopaedic or other disorders interfering with the protocol

Primary outcomes:
measure: Change of the 9 Hole Peg Test score
timeFrame: baseline and 4 weeks and baseline and 16 weeks
Secondary outcomes:
measure: Treatment change in percentage of responders at 9 Hole Peg Test score
timeFrame: baseline and 4 weeks and baseline and 16 weeks
measure: Absolute change of exercise performance
timeFrame: baseline and 4 weeks and baseline and 16 weeks
measure: Absolute change of task difficulty
timeFrame: baseline and 4 weeks and baseline and 16 weeks
Other outcomes:
Locations:
Study officials:
affiliation: ASL 3 Genovese
name: Claudio M Solaro, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Basteris A, De Luca A, Sanguineti V, Solaro C, Mueller M, Carpinella I, Cattaneo D, Bertoni R, Ferrarin M. A tailored exercise of manipulation of virtual tools to treat upper limb impairment in Multiple Sclerosis. IEEE Int Conf Rehabil Robot. 2011;2011:5975509. doi: 10.1109/ICORR.2011.5975509.
citation: Solaro C, Cattaneo D, Basteris A, Carpinella I, De Luca A, Mueller M, Bertoni R, Ferrarin M, Sanguineti V. Haptic vs sensorimotor training in the treatment of upper limb dysfunction in multiple sclerosis: A multi-center, randomised controlled trial. J Neurol Sci. 2020 May 15;412:116743. doi: 10.1016/j.jns.2020.116743. Epub 2020 Feb 19.