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| Name | Class |
|---|---|
| Ministry of Health, Italy | OTHER_GOV |
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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Experimental Group (EG) | Experimental | Participants assigned to Experimental Group (EG) will follow 20 sessions (3 times/week) of robotic-assisted treatment for upper limb rehabilitation using the Motore (Humanware S.r.l, Pisa, Italia ) robotic device in addition to the standard rehabilitation program. |
|
| Control Group (CG) | Active Comparator | Participants assigned to Control Group (CG) will follow 20 sessions (3 times/week) of conventional tratment for upper limb rehabilitation in addition to the standard rehabilitation program. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Experimental Group | Device | 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, flexion-extension. The software includes serious games for:
|
| Measure | Description | Time Frame |
|---|---|---|
| Box and Block Test (BBT) | Box and Blocks test, BBT, is used to measure a manual dexterity that requires repeatedly moving 1-inch blocks from one side of a box to another in 60 seconds. In Box and Blocks test there are test box with 150 blocks and a partition in the middle is placed lengthwise along the edge of a standard-height table. The test taker is instructed to quickly pick up one block at a time with his or her right or left hand. Then carry the box over the partitioned and drop it and it is important for the patient to know that each successful execution is one point and he or she carries two it will be counted as one. The number of blocks that the test taker successfully transferred will becomes the final score and the higher the score the better the gross manual dexterity of the test taker. | Day 0 (T0 - baseline), day 50 (T1 - After treatment). |
| Measure | Description | Time Frame |
|---|---|---|
| Action Research Arm Test (ARAT) | The Action Research Arm Test (ARAT) is a 19 item observational measure used by physical therapists and other health care professionals to assess upper extremity performance (coordination, dexterity and functioning) in stroke recovery, brain injury and multiple sclerosis populations. Items comprising the ARAT are categorized into four subscales (grasp, grip, pinch and gross movement) and arranged in order of decreasing difficulty, with the most difficult task examined first, followed by the least difficult task. Lyle proposed that this hierarchical ordering would improve efficiency of testing, as normal movement on the most difficult items would be indicative of successful performance on proceeding items. Task performance is rated on a 4-point scale, ranging from 0 (no movement) to 3 (movement performed normally). |
| Measure | Description | Time Frame |
|---|---|---|
| Montreal Cognitive Assessment (MoCA) | The MoCA is popular screening tool used to determine if cognitive impairment is present. It takes approximately ten minutes to complete. It evaluates visuospatial skills, attention, language, abstract reasoning, delayed recall, executive function, and orientation. The MoCA covers more domains than the MMSE and, as a consequence, has greater sensitivity and specificity. Cognitive assessments are fast, easy-to-use, and accurate ways to help diagnose, evaluate progress, and manage many kinds of cognitive impairments. The MoCA is useful in determining a patient's level of understanding and ability. |
Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Dr. Sanaz Pournajaf, DPT | Contact | +39 0652252405 | 32405 | sanaz.pournajfa@sanraffaele.it |
| Dr. Carrie Louise Thouant, OT | Contact | carrielouise.thouant@sanraffaele.it |
| Name | Affiliation | Role |
|---|---|---|
| Prof. Marco Franceschini, MD | IRCCS San Raffaele Roma | Study Chair |
| Prof. Marco Franceschini, MD | IRCCS San Raffaele Roma | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| San Raffaele Cassino | Not yet recruiting | Cassino | FR | 03043 | Italy |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 30879893 | Result | 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. | |
| 30584159 | Result | 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. |
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Individual participant data (IPD) will be shared upon request from the Principal Investigator, Study Chair, or Central Contact Person of this study.
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| ID | Term |
|---|---|
| D010300 | Parkinson Disease |
| ID | Term |
|---|---|
| D020734 | Parkinsonian Disorders |
| D001480 | Basal Ganglia Diseases |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
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| ID | Term |
|---|---|
| D035061 | Control Groups |
| ID | Term |
|---|---|
| D015340 | Epidemiologic Research Design |
| D004812 | Epidemiologic Methods |
| D008919 | Investigative Techniques |
| D012107 | Research Design |
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|
| control group | Other | 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 dexterity. |
|
| Day 0 (T0 - baseline), day 50 (T1 - After treatment). |
| Unified Parkinson's Disease Rating Scale (UPDRS) | Unified Parkinson's Disease Rating Scale (UPDRS) is a rating tool used to gauge the the severity and progression of Parkinson's disease in patients. The UPDRS scale consists of the following six segments:
Parts 1 to 3 are scored on a 0-4 rating scale. Part 4 is scored with yes and no ratings. Higher scores show increased severity. Then the administrator rates the patient on the H and Y Scale and the Schwab and England Activities of Daily Living Scale. | Day 0 (T0 - baseline), day 50 (T1 - After treatment). |
| Disabilities of the Arm, Shoulder and Hand (DASH) | The Disabilities of the Arm, Shoulder and Hand (DASH) questionnaire is a 30-item questionnaire that looks at the ability of a patient to perform certain upper extremity activities. This questionnaire is a self-report questionnaire that patients can rate difficulty and interference with daily life on a 5 point Likert scale. The DASH has been translated in many different languages and has demonstrated to be a valid and reliable questionnaire for a variety of upper extremity disorders. High score corresponds to high level of arm disability. | Day 0 (T0 - baseline), day 50 (T1 - After treatment), day 140 (FU1 - 3 months after treatment Follow-Up) |
| Client satisfaction questionnaire | The Client satisfaction questionnaire investigates the subject's overall satisfaction with participating in the study. It consists of six questions with a score ranging from 0 to 4. A high score corresponds to a high level of satisfaction from the subject. | Day 50 (T1 - After treatment). |
| System Usability Scale (SUS) | The System Usability Scale (SUS) is a simple, ten-item scale giving a global view of subjective assessments of usability. SUS is a Likert scale. It is often assumed that a Likert scale is simply one based on forced-choice questions, where a statement is made and the respondent then indicates the degree of agreement or disagreement with the statement on a 5 (or 7) point scale. However, the construction of a Likert scale is somewhat more subtle than this. Whilst Likert scales are presented in this form, the statements with which the respondent indicates agreement and disagreement have to be selected carefully. | Day 50 (T1 - After treatment). |
| Day 0 (T0 - baseline) |
| Nine Hole Peg Test | The Nine-Hole Peg Test (9HPT) is used to measure finger dexterity in patients with various neurological diagnoses. The administration of the test consists of instructing the patient to take the pegs from a container, one by one, and place them into the holes on the board, as quickly as possible, using only the hand being evaluated. Then, instruct the patient to remove the pegs from the holes, one by one, and replace them back into the container. The evaluator should start the stopwatch as soon as the patient touches the first peg. The evaluator should stop the stopwatch once the last peg is in the container. The scoring is calculated as number of seconds it takes for the patient to complete the test. An alternative scoring could be the number of pegs placed in 50 or 100 seconds can be recorded. In this case, results are expressed as the number of pegs placed per second. | Day 0 (T0 - baseline), day 50 (T1 - After treatment). |
| Trail Making Test | The Trail Making Test consists of two parts, A and B, each of which must be performed using a pencil. The examiner starts timing parts A and B as soon as they finish giving the instructions and the participant is given the start signal. The stopwatch should not be stopped until the participant has completed each part or the time limit for interruption has been reached. The score is calculated in this way: the time taken for completion must be recorded separately for Parts A and B. The maximum score for Part A is 100", while 101" indicates that the test was interrupted. The maximum score for Part B is 300", while 301" indicates that the test was interrupted. | Day 0 (T0 - baseline), day 50 (T1 - After treatment). |
| Sensors-based Pointing Task | The subject sits in front of a target panel (e.g., a touch-screen monitor 24") in order to perform a pointing task evaluation test. The distance between the subject and the center of the panel will be set according to each subject's arm length measured with the fist closed. During the pointing task trials, subjects are invited to reach, at his/her self-selected speed, one of the targets on the monitor, and then return to the initial point (e.g., the trigger-box button). Inertial sensors will be applied to the upper limb and trunk, surface electromyography sensors will be placed on the main muscle groups of the upper limb, and finally, a 128-channel EEG cap will be used. | Day 0 (T0 - baseline), day 50 (T1 - After treatment). |
| Strumental force evaluation assesment | A strength assessment is performed using a robotic device that measures the force exerted by the subject for each movement and the duration of maximum force maintenance. | Day 0 (T0 - baseline), day 50 (T1 - After treatment). |
| Strumental rom evaluation assesment | A ROM assessment is performed using a robotic device that measures projections along different directions, the trajectory, and the area covered by the subject for each movement. | Day 0 (T0 - baseline), day 50 (T1 - After treatment). |
| IRCCS San Raffaele Roma | Recruiting | Rome | Lazio | 00163 | Italy |
|
| 33894193 | Result | 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. |
| 18344392 | Result | 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. |
| 17913560 | Result | 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. |
| 23231827 | Result | 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. |
| 13174710 | Result | 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. |
| 4022305 | Result | 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. |
| 19043519 | Result | Jankovic J, Aguilar LG. Current approaches to the treatment of Parkinson's disease. Neuropsychiatr Dis Treat. 2008 Aug;4(4):743-57. doi: 10.2147/ndt.s2006. |
| 26210889 | Result | Peall KJ, Kuiper A, de Koning TJ, Tijssen MA. Non-motor symptoms in genetically defined dystonia: Homogenous groups require systematic assessment. Parkinsonism Relat Disord. 2015 Sep;21(9):1031-40. doi: 10.1016/j.parkreldis.2015.07.003. Epub 2015 Jul 17. |
| 23492553 | Result | Grazina R, Massano J. Physical exercise and Parkinson's disease: influence on symptoms, disease course and prevention. Rev Neurosci. 2013;24(2):139-52. doi: 10.1515/revneuro-2012-0087. |
| 31377382 | Result | Capecci M, Pournajaf S, Galafate D, Sale P, Le Pera D, Goffredo M, De Pandis MF, Andrenelli E, Pennacchioni M, Ceravolo MG, Franceschini M. Clinical effects of robot-assisted gait training and treadmill training for Parkinson's disease. A randomized controlled trial. Ann Phys Rehabil Med. 2019 Sep;62(5):303-312. doi: 10.1016/j.rehab.2019.06.016. Epub 2019 Aug 1. |
| Result | Keus SHJ, Munneke M, Graziano M, et al. European Physiotherapy Guideline for Parkinson's disease. s.l. : KNGF/ParkinsonNet, 2014. |
| 24769288 | Result | Vercruysse S, Gilat M, Shine JM, Heremans E, Lewis S, Nieuwboer A. Freezing beyond gait in Parkinson's disease: a review of current neurobehavioral evidence. Neurosci Biobehav Rev. 2014 Jun;43:213-27. doi: 10.1016/j.neubiorev.2014.04.010. Epub 2014 Apr 23. |
| 30269804 | Result | Molteni F, Gasperini G, Cannaviello G, Guanziroli E. Exoskeleton and End-Effector Robots for Upper and Lower Limbs Rehabilitation: Narrative Review. PM R. 2018 Sep;10(9 Suppl 2):S174-S188. doi: 10.1016/j.pmrj.2018.06.005. |
| D009422 | Nervous System Diseases |
| D009069 | Movement Disorders |
| D000080874 | Synucleinopathies |
| D019636 | Neurodegenerative Diseases |
| D008722 | Methods |