Background: Turns are often cited as a difficult task for individuals with Parkinson's disease and often lead to falls, however targeted exercise interventions may help to reduce this problem. This study examined the effects of a 10-week home-based exercise program focusing on turns which may be an exercise approach for improving mobility and reducing falls in individuals with Parkinson's disease.
Methods: Turning and stepping characteristics were recorded using Inertial Measurement Units while participants performed a 180° standing turn. Eye movements were measured using a BlueGain electrooculography system. Clinical outcomes were assessed using the Movement Disorders Society-Unified Parkinson's Disease Rating Scale, Functional axial rotation-physical score and the Falls Efficacy Scale International.
Findings: Twenty individuals with Parkinson's disease were matched by severity using the Modified Hoehn and Yahr scale and were randomly allocated to an exercise (n = 10) or control group (n = 10). Significant improvements were seen after 10 weeks in the exercise group only for; onset latency of body segments, step size, number of fast phase eye movements, the Movement Disorders Society-Unified Parkinson's Disease Rating Scale in motor and rigidity scores, Functional axial rotation-physical score and the Falls Efficacy Scale International.
Interpretation: These results indicate that the home-based exercise programme targeting turning characteristics had positive effects on turning performance and clinical outcomes associated with falls in individuals with Parkinson's disease. These preliminary results support the notion that targeted home-based exercises may provide an effective intervention in this population.
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http://dx.doi.org/10.1016/j.clinbiomech.2021.105469 | DOI Listing |
Sci Rep
January 2025
Department of Neurology, Neurological Institute, Taichung Veterans General Hospital, No. 1650, Taiwan Boulevard, Section 4, Taichung, 40705, Taiwan.
This study investigates whether incorporating olfactory dysfunction into motor subtypes of Parkinson's disease (PD) improves associations with clinical outcomes. PD is commonly divided into motor subtypes, such as postural instability and gait disturbance (PIGD) and tremor-dominant PD (TDPD), but non-motor symptoms like olfactory dysfunction remain underexplored. We assessed 157 participants with PD using the University of Pennsylvania Smell Identification Test (UPSIT), Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (M-UPDRS), Montreal Cognitive Assessment (MoCA), 39-item Parkinson's Disease Questionnaire Summary Index (PDQ-39 SI), and 99mTc-TRODAT-1 imaging.
View Article and Find Full Text PDFNeuroimage
January 2025
Faculty of Health Sciences, University of Macau, Macau SAR 999078, China; Centre for Cognitive and Brain Sciences, University of Macau, Macau SAR 999078, China. Electronic address:
Individuals in the prodromal phase of Parkinson's disease (PD) exhibit significant heterogeneity and can be divided into distinct subtypes based on clinical symptoms, pathological mechanisms, and brain network patterns. However, little has been done regarding the valid subtyping of prodromal PD, which hinders the early diagnosis of PD. Therefore, we aimed to identify the subtypes of prodromal PD using the brain radiomics-based network and examine the unique patterns linked to the clinical presentations of each subtype.
View Article and Find Full Text PDFNeuron
January 2025
Department of Genetics, Stanford University, Stanford, CA, USA; Glenn Center for the Biology of Aging, Stanford University, Stanford, CA, USA; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA. Electronic address:
Brain aging leads to a decline in cognitive function and a concomitant increase in the susceptibility to neurodegenerative diseases such as Alzheimer's and Parkinson's diseases. A key question is how changes within individual cells of the brain give rise to age-related dysfunction. Developments in single-cell "omics" technologies, such as single-cell transcriptomics, have facilitated high-dimensional profiling of individual cells.
View Article and Find Full Text PDFComput Med Imaging Graph
January 2025
University of Electronic Science and Technology of China, Chengdu, Sichuan, China. Electronic address:
In this study, we developed an Evidential Ensemble Neural Network based on Deep learning and Diffusion MRI, namely DDEvENet, for anatomical brain parcellation. The key innovation of DDEvENet is the design of an evidential deep learning framework to quantify predictive uncertainty at each voxel during a single inference. To do so, we design an evidence-based ensemble learning framework for uncertainty-aware parcellation to leverage the multiple dMRI parameters derived from diffusion MRI.
View Article and Find Full Text PDFPLoS One
January 2025
School of Sports Science, Harbin Normal University, Harbin, China.
Objective: To explore the impact of aerobic and resistance training on walking and balance abilities (UPDRS-III, Gait Velocity, Mini-BESTest, and TUG) in individuals with Parkinson's disease (PD).
Method: All articles published between the year of inception and July 2024 were obtained from PubMed, Embase, and Web of Science. Meta-analysis was conducted with RevMan 5.
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