Efficacy of a Robotic-assisted Gait Training in Addition to a Conventional Physical Therapy in Parkinson's Disease
- Conditions
- Parkinson's Disease
- Registration Number
- NCT02164162
- Lead Sponsor
- Habilita, Ospedale di Sarnico
- Brief Summary
In Parkinson's disease, gait disturbances represent one of the most disabling motor symptoms, frequently associated with an increased risk of falls, loss of independence and a negative impact on quality of life. In recent years, the interest in automated robotic devices for gait training for Parkinson's Disease patients has grown. With their consistent, symmetrical lower-limb trajectories, robotic devices provide many of the proprioceptive inputs that may increase cortical activation and improve motor function while minimizing the intervention of a therapist. So the main aim of this study will be to analyze, through a clinical and an instrumental evaluation, the effectiveness of a Lokomat gait training in subjects affected by Parkinson's disease in comparison to a ground conventional gait training.
- Detailed Description
In Parkinson's disease, gait disturbances represent one of the most disabling motor symptoms, frequently associated with an increased risk of falls, loss of independence and a negative impact on quality of life. Patients with Parkinson's Disease, display an abnormal gait pattern (reduced gait speed, shortened stride length, and a longer double-limb support phase) and they are typically unable to generate a proper stride length and to maintain a steady gait rhythm. Therefore, improving gait ability is a primary goal of physical therapy in patients with Parkinson's Disease. Conventional Physiotherapy aimed at enabling patients to maintain their maximum level of activity and independence is often prescribed, but treatments for gait give only limited benefits. Promising reports have suggested that external sensory cueing (acoustic, visual, verbal cues), through an attention mechanism, may help to increase the deficient internal cueing in Parkinson's Disease, thus improving gait pattern.Treadmill training, which induces a constant horizontal movement, generates a rhythmic input for locomotion, coordinating the upper and lower limbs, offering a useful retraining modality that complements conventional therapy. In the last decade some researchers focused on the use of partial body weight support systems on the ground or with the combination of treadmill training (Body weight support-treadmill). These systems, which improves the ability to stand in an upright position with a redistribution of forces on the trunk, thus disengaging the girdle and upper limbs, suggests a greater improvement in motor performance and walking ability compared with conventional phisiotherapy. In recent years, the interest in automated robotic devices for gait training for Parkinson's Disease patients has grown. With their consistent, symmetrical lower-limb trajectories, robotic devices provide many of the proprioceptive inputs that may increase cortical activation and improve motor function while minimizing the intervention of a therapist. Moreover, proprioceptive inputs may share mechanisms that are common to external cues, thus stimulating the cerebellar-premotor pathway to improve gait. Besides,the preprogrammed walking pattern corresponds to normal gait kinematics including: gait cycle timing, inter-limb and inter-joint coordination, appropriate limb loading, and afferent signaling. A recent randomized controlled trial that compared a comprehensive rehabilitative program vis-à-vis robot-assisted gait training has shown that the latter displays some advantages. A pilot, non-controlled study explored the effect of robot-assisted gait training on freezing of gait.Still, despite recent interest in automated locomotion training, there is still very little evidence to support the superiority of this technique over traditional gait training. A computerized gait analysis represents an useful aid to study gait disturbances. The analysis sets objectives and defines quantitative data about gait changes occurred in a patient, in relation to the progression of underlying disease or th effectiveness of treatments administered (medication, surgery or physical). So the main aim of this study will be to analyze, through a clinical and an instrumental evaluation, the effectiveness of a Lokomat gait training in subjects affected by Parkinson's disease in comparison to a ground conventional gait training
Recruitment & Eligibility
- Status
- UNKNOWN
- Sex
- All
- Target Recruitment
- 40
- Parkinson's disease stage 2 to 3 (calculated in the "on phase") on the Hoehn and Yahr scale
- independent walking
- clinical-pharmacological stabilization until three months before the beginning of the study.
- deficits of somatic sensation involving the legs
- vestibular disorders or paroxysmal vertigo
- other neurological, orthopedic or cardiovascular co-morbility
- severe posture abnormalities
- severe-moderate cognitive impairment (Minmental state ≤ 21)
- severe dyskinesia or "on-off"phases
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- PARALLEL
- Primary Outcome Measures
Name Time Method Timed 6 meter walking test 4 weeks Timed 6-meter walking test evaluate the gait speed. Individual walks without assistance 10 meters and the time is measured for the intermediate 6 meters to allow for acceleration and deceleration
- Secondary Outcome Measures
Name Time Method Tinetti Test 4 weeks to assess balance and gait ability and the falls risk
Barthel Index 4 weeks to assess the degree of disability
Movement Disorder Society-Unified Parkinson's Disease Rating Scale Disease rating scale motor sub-scores) 4 weeks a scale to assess the motor specific examination for Parkinson's Disease
Functional Independence Measure 4 weeks to assess daily activities functional autonomy
Parkinson's Disease Questionnaire -39 item 4 weeks to assess quality of life
Trial Locations
- Locations (1)
Casa di Cura Habilita
🇮🇹Ciserano, Bergamo, Italy
Casa di Cura Habilita🇮🇹Ciserano, Bergamo, ItalyPaola Sabattini, CoordinatorContact+390354815paolasabattini@habilita.itGiovanni Taveggia, MDPrincipal InvestigatorAnna Furnari, MDSub InvestigatorAnna FurnariSub Investigator