View clinical trials related to Parkinson Disease.
Filter by:This study is a waitlisted randomized controlled trial. We aim to assess the level of compliance for those learning the intervention and to evaluate the impact of the practice on neuropsychological and somatic outcomes using validated scales. Enrollment into the study will be ongoing until we are able to get a sufficient sample size as described in the "Statistical Consideration" section. Upon enrollment and randomization, surveys will be administered to both the intervention and control groups at four time-points: baseline, T2, T3, and T4, each of which are 6 weeks apart. Compliance data will be collected weekly for 12 weeks for both groups.
The purpose of this research study is to determine whether istradefylline improves cognition in individuals with Parkinson disease with cognitive impairment.
Treatment with subcutaneous apomorphine will be initiated according to the usual procedures at each centre. Once the patient is included in the study, he/she will be followed for 24 months according to a schedule of visits corresponding to his/her follow-up care. The procedures outside of the patient's usual care are only more in-depth clinical assessments and examinations (interviews with a nurse, skin lesion assessment scale, quality of life scales, neurological and cognitive assessment scales). At each visit, the patient will be seen in consultation by a state-qualified nurse from the neurology department who will conduct - nursing interviews to assess tolerance and compliance with treatment. She will also look for data concerning the flow rate, the duration of the subcutaneous apomorphine pump and the injection methods (material used, rotation of injection sites, massages). - collection of adverse effects and changes in concomitant treatments. - assessment of skin complications (number, location, characteristics: size, pain, inflammation). For centres that do not have a nurse dedicated to monitoring these patients, the above procedure will be carried out by the neurologist. In all cases, the patient will receive a consultation (in the department or remotely) by the neurologist. The tests and scales performed at inclusion will be repeated at each six-monthly visit.
This observational trial aims to evaluate the effect of Rehabilitation on Postural Transfers (PTs) in subjects affected by Parkinson Disease. The PTs are evaluated by an inertial sensor (a device composed by an accelerometer, a gyroscope and a magnetometer) attached to the subjects. The data obtained by the inertial sensor are kinematic (e.g. acceleration and angular speed) and spatiotemporal parameters (e.g. time to completion and velocity). Additional clinical evaluations are carried out at the beginning and end of the rehabilitative intervention.
Parkinson's disease (PD) affects approximately 6.5 million people around the world and it is ranked as the second most common age-related neurodegenerative disease after Alzheimer disease. US have reported 800,000 PD patients in 2016, the highest number of reported PD patients in the world while UK has the lowest number of PD cases i.e. 100,000. With a rise of 2.3 million cases in 2026, an approximate annual growth rate of 2.52% is predicted globally. According to Pakistan Parkinson's society, approximately 450,000 Pakistanis were affected with PD. The age-specific prevalence of PD in Pakistan was found to be high in 70 to 79 years of age with males being more affected as compared to females. Parkinson's disease is a neurological condition, characterized by tremors, rigidity, and stiffness in the body, along with bradykinesia, walking and balance problems. Poor balance is one of the major and most disabling characteristics among Parkinson patients. Freezing of gait (FOG) and postural instability is one of the major cause of fall and loss of independence among PD patients whereas cognitive dysfunction is one of the common non-motor symptoms affecting 20 to 57% of PD patients. Among recent technological advancements in neurological physical therapy, virtual reality (VR) games have become an area of interest for researchers. Despite advances in the rehabilitation of PD, evidence regarding the effects of visual biofeedback therapy on Parkinson patients is still scarce. Only few studies have studied the effects of visual biofeedback therapy on balance in PD patients, but as per knowledge of the researcher there is no study published on effects of visual biofeedback therapy on FOG and cognition among Parkinson patients in Pakistan. Therefore, the present study is aimed to assess the effects of biofeedback balance training using a balance board on balance, FOG and cognition in patients with Parkinson disease.
Phase 1 study evaluating the safety of combined bilateral globus pallidus internus (GPi) and nucleus basalis of Meynert (NBM) stimulation in treating levodopa responsive motor symptoms of Parkinsonism and cognitive dysfunction, respectively, in patients with moderate to advanced Parkinson's disease having mild cognitive impairment.
Rehabilitation is crucial in the treatment of people with Parkinson's disease (PD) as it can ameliorate motor and non-motor impairments, improving their clinical profile and quality of life. Considering the complex biological processes occurring in PD brain, the identification of accessible and measurable biomarkers to monitor the events induced by intensive rehabilitation would help in i)testing rehabilitation effectiveness, ii)improving the design of clinical trials and iii)personalizing the rehabilitation strategies by the prediction of patients' responsiveness. The objective of this project is the validation of Raman analysis of saliva and salivary extracellular vesicles (EV) for the differential diagnosis of Parkinson's disease (PD) and atypical Parkinsonism. The proposed diagnostic method can be integrated in the preliminary assessment and monitoring of the patient by providing a quickly and repeatable measurable biomarker. In the end, this will bring tothe personalization of the rehabilitation path and provide an indication on the outcome of the rehabilitation treatment.
This research involves retrospective and prospective studies for clinical validation of a DystoniaNet deep learning platform for the diagnosis of isolated dystonia.
Individuals experiencing tremors face difficulty performing activities of daily living caused by involuntary oscillation of the muscles in the hands and arms. Current solutions to help suppress tremors include medication, surgery, assistive devices and lifestyle change. However, each of these has a drawback of its own including cost and unwanted side effects. Aside from the solutions listed, it has been shown that functional electrical stimulation(FES) is a possible solution to help suppress tremor. Additionally, FES can be combined with different technologies including accelerometers, gyroscopes and motion capture to develop a closed loop system for tremor suppression. However, this has drawbacks including signal interference and the need for multiple sensor to fully classify the tremor. Ultrasound imaging solves some of these issues because it can provide a direct visualization of hand muscles that contribute to tremor. This study will focus on detecting characterizing and differentiating tremors from voluntary hand motion using ultrasound imaging. The results obtained from this study will help design FES-based tremor-suppression techniques in the future. This study will target both subjects with different tremor disorders and able bodied subjects.
This study aims to determine whether direct brain stimulation of specific regions and ranges improves cognition in people with Parkinsons Disease (PD) who already have a deep brain stimulator implanted. Research activities consist of 32 subjects undergoing stimulation changes to their device and being administered neurocognitive tests to evaluate the changes. An fMRI scan will also be done at baseline and at weeks 15 and 27. All subjects will undergo the stimulation changes in a randomized double blind crossover study. Evaluation of stimulation changes will be assessed through analysis of neurocognitive data.