View clinical trials related to Bradykinesia.
Filter by:The goal of this clinical trial is to examine effects of training involving rhythmic auditory stimulation (RAS) on upper-limb movements and functions in patients with Parkinson's disease (PD). Patients will be randomly divided into two groups: the RAS group and the no-RAS group. Patients will receive training with or without the aid of RAS based on their groups. The training task is to use the right hand to take beads from one bowl to another bowl. The box and block test and the Jebsen hand function test will be used before and after training (i.e., pretest and posttest respectively) to assess patients' upper-limb speed and function. Researchers will compare scores of the box and block test and the Jebsen hand function test between the two groups at pretest and posttest to determine effects of RAS.
Bradykinesia is a key parkinsonian feature yet subjectively assessed by the MDS-UPDRS score, making reproducible measurements and follow-up challenging. In a Movement Disorder Unit, the investigators acquired a large database of videos showing parkinsonian patients performing Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III protocols. Using a Deep Learning approach on these videos, the investigators aimed to develop a tool to compute an objective score of bradykinesia from the three upper limb tests described in the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III.
Investigate the safety and tolerability of umbilical cord-derived allogeneic mesenchymal stem cells to treat patients with Bradykinesia.
The clinical utility of deep brain stimulation (DBS) for the treatment of movement disorders such as Parkinson's disease has been well established; however, there is a great disparity in outcomes among DBS recipients due to varied postoperative management, particularly concerning the choosing of an optimal set of programming parameters from the thousands of possible combinations. This study will evaluate the use of motion sensor based assessments to develop a functional map and algorithms to automatically determine a set of programming parameters that maximize symptomatic benefits while minimizing side effects and battery consumption.