Upper Limb Rehabilitation in People With Parkinson's Disease:

Official title

Effectiveness of a Robotic End-effector Device for Upper Limb Rehabilitation in People With Parkinson's Disease: a Multicenter Randomized Controlled Pilot Study

Overview

This study evaluates the effectiveness of upper limb rehabilitation using an end-effector robotic device with exercises designed to improve movements, strength, and coordination of the shoulder, elbow, and wrist in patients with Parkinson's disease who have mild to moderate disability, compared to conventional rehabilitation treatment. The study protocol will involve individuals diagnosed with PD according to the UK Parkinson's Disease Society Brain Bank criteria, who will be randomly assigned to one of the following groups: A - Experimental Group (EG) - robotic treatment for upper limb rehabilitation. B - Control Group (CG) - conventional treatment for upper limb rehabilitation. Secondary objectives include: \- Evaluating the effectiveness of an end-effector robotic system in terms of improving upper limb coordination and functionality through the ARAT test and the UPDRS. Identifying subgroups of participants who may benefit more from robotic therapy based on PD disease stage (Hoehn \& Yahr), age, and upper limb impairment. Analyzing the effects of robotic rehabilitation on quality of life. Assessing participants' compliance and satisfaction levels with the robotic system in terms of improving participation in upper limb rehabilitation.

Detailed description

Parkinson's disease (PD) is the second most common neurodegenerative disorder, affecting over 6 million individuals worldwide, with its prevalence having increased 2.5 times in the last 30 years, making it a leading cause of neurological disability. The hallmark of PD is a motor syndrome characterized by bradykinesia, resting tremor, and rigidity, alongside postural and gait alterations. Despite being considered a movement disorder, PD often presents non-motor symptoms like hyposmia, constipation, urinary dysfunction, orthostatic hypotension, cognitive impairments, mood depression, pain, and sleep disorders. Motor symptoms progressively impair daily activities and reduce quality of life, with difficulties in gait and swallowing worsening disability over time. Specifically, upper limb motor dysfunction is marked by reduced movement speed and impaired force modulation, leading to poor hand movement quality. Motor impairment in PD is inversely correlated with movement speed and directly correlated with task complexity.

PD progresses slowly, and while current treatments manage motor symptoms effectively in the early stages, their efficacy diminishes in advanced stages, with non-motor symptoms becoming more evident. Alongside pharmacotherapy, early and regular physical rehabilitation has shown benefits, improving motor function, posture control, balance, and strength while potentially delaying disease progression. The success of PD treatment depends on treatment quality, timing, and frequency. Conventional rehabilitation includes exercise, strategy training, and patient education, focusing on enhancing upper limb coordination, fluidity, and dexterity. Although some therapies improve motor function and non-motor symptoms, limited evidence exists regarding their impact on hand dexterity.

Robotic devices, leveraging neuroplasticity and motor learning principles, have been integrated into rehabilitation to maximize sensory input and provide targeted, task-specific stimuli to the central nervous system. Advances in technology have made robotic treatments more accessible, complementing traditional physiotherapy, particularly in upper limb neurorehabilitation.

Robotic-assisted therapy (RAT) has shown efficacy in stroke rehabilitation, improving upper limb function, spasticity, and daily living activities. However, research on robotic rehabilitation for PD has primarily focused on lower limbs and gait training (RAGT), demonstrating positive effects on motor function and balance, despite limited sample sizes and follow-up studies.

Regarding upper limb rehabilitation in PD, evidence is scarce. Some studies using virtual reality systems, like Oculus Rift 2 with Leap Motion Controller (OR2-LMC), have shown improvements in strength, fine and gross dexterity, and movement speed, although discrepancies between qualitative and quantitative results were noted. Picelli et al. (2014) found that robotic-assisted upper limb training improved sensorimotor functions, but the placebo effect cannot be ruled out, emphasizing the need for larger, randomized controlled trials comparing RAT to conventional rehabilitation.

More recently, Raciti L. et al. (2022) highlighted the efficacy of the Armeo exoskeleton in enhancing hand function, dexterity, and cognitive abilities, suggesting a promising avenue for PD rehabilitation (32).

Given the limited evidence on robotic rehabilitation for upper limb motor disorders in PD, this study aims to evaluate the effectiveness of an end-effector robotic device designed to improve shoulder, elbow, and wrist movements, strength, and coordination in individuals with mild to moderate PD, compared to conventional rehabilitation.

Interventions

• Device Experimental Group
  The EG will follow 20 sessions of robot-assisted therapy for the upper limb. Exercises will be performed using a handpiece to support the weight of the upper limb during therapy and to assist (or resist) movements according to the patient's needs. These modalities are presented to the patient through visual and motor feedback (force feedback). The exercises will focus on rehabilitating upper limb performance, for example: Elbow: flexion-extension; Shoulder: horizontal adduction/abduction, flex
• Other control group
  The CG will last 20 sessions (3 days/week) of conventional rehabilitative treatment without the use of technological devices for the upper limb. Each session will last 45 minutes. The motor exercises will focus on upper limb rehabilitation and will be performed with a therapist who will personalize the treatment based on the patient's characteristics and needs. Specifically, the upper limb treatment will include exercises for mobility (shoulder, elbow, wrist, and hand), coordination, and manual

Primary outcome measures

• Box and Block Test (BBT) [Time frame: Day 0 (T0 - baseline), day 50 (T1 - After treatment).]

Secondary outcome measures (5)

• Action Research Arm Test (ARAT) [Time frame: Day 0 (T0 - baseline), day 50 (T1 - After treatment).]
• Unified Parkinson's Disease Rating Scale (UPDRS) [Time frame: Day 0 (T0 - baseline), day 50 (T1 - After treatment).]
• Disabilities of the Arm, Shoulder and Hand (DASH) [Time frame: Day 0 (T0 - baseline), day 50 (T1 - After treatment), day 140 (FU1 - 3 months after treatment Follow-Up)]
• Client satisfaction questionnaire [Time frame: Day 50 (T1 - After treatment).]
• System Usability Scale (SUS) [Time frame: Day 50 (T1 - After treatment).]

Eligibility criteria

Inclusion criteria

• Age between 30 and 80 years;
• Diagnosis of Parkinson's disease according to the UK Parkinson's Disease Society Brain Bank criteria;
• Hoehn \& Yahr scale score between 2 and 3 in the "ON" phase;
• Montreal Cognitive Assessment (MoCA) screening test with a score ≥ 17.54;
• Stable pharmacological therapy for at least 4 weeks and throughout the treatment;
• Ability to understand and sign the informed consent for the study;
• Signed informed consent for the study;
• Ability to comply with the study procedures.

Exclusion criteria

• Unable to adhere to the exercise program due to poor compliance;
• Neurological disorders overlapping with Parkinson's disease, psychiatric complications, or personality disorders;
• Presence of osteoarticular and neuromuscular diseases that may impair upper limb mobility;
• Participants who have not signed the informed consent for the study.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation

Randomized

Model

Parallel assignment

Masking

Open label

Primary purpose

Treatment

Study locations

Italy · 2 centers

• San Raffaele Cassino — Cassino
• IRCCS San Raffaele Roma — Rome

Publications

• GBD 2016 Neurology Collaborators. Global, regional, and national burden of neurological disorders, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019 May;18(5):459-480. doi: 10.1016/S1474-4422(18)30499-X. Epub 2019 Mar 14. PMID 30879893
• Dorsey ER, Sherer T, Okun MS, Bloem BR. The Emerging Evidence of the Parkinson Pandemic. J Parkinsons Dis. 2018;8(s1):S3-S8. doi: 10.3233/JPD-181474. PMID 30584159
• Tolosa E, Garrido A, Scholz SW, Poewe W. Challenges in the diagnosis of Parkinson's disease. Lancet Neurol. 2021 May;20(5):385-397. doi: 10.1016/S1474-4422(21)00030-2. PMID 33894193
• Jankovic J. Parkinson's disease: clinical features and diagnosis. J Neurol Neurosurg Psychiatry. 2008 Apr;79(4):368-76. doi: 10.1136/jnnp.2007.131045. PMID 18344392
• Ponsen MM, Daffertshofer A, Wolters ECh, Beek PJ, Berendse HW. Impairment of complex upper limb motor function in de novo Parkinson's disease. Parkinsonism Relat Disord. 2008;14(3):199-204. doi: 10.1016/j.parkreldis.2007.07.019. Epub 2007 Oct 2. PMID 17913560
• Quinn L, Busse M, Dal Bello-Haas V. Management of upper extremity dysfunction in people with Parkinson disease and Huntington disease: facilitating outcomes across the disease lifespan. J Hand Ther. 2013 Apr-Jun;26(2):148-54; quiz 155. doi: 10.1016/j.jht.2012.11.001. Epub 2012 Dec 8. PMID 23231827
• FITTS PM. The information capacity of the human motor system in controlling the amplitude of movement. J Exp Psychol. 1954 Jun;47(6):381-91. No abstract available. PMID 13174710
• Sanes JN. Information processing deficits in Parkinson's disease during movement. Neuropsychologia. 1985;23(3):381-92. doi: 10.1016/0028-3932(85)90024-7. PMID 4022305

Identifiers

NCT: NCT06906679 · RP 12/23

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗