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Assessment of temporospatial and kinematic gait parameters using human pose estimation in patients with Parkinson's disease: A comparison between near-frontal and lateral views.
PLoS One
January 2025
Department of Biomedical and Robotics Engineering, Incheon National University, Incheon, Korea.
Gait disturbance is one of the most common symptoms in patients with Parkinson's disease (PD) that is closely associated with poor clinical outcomes. Recently, video-based human pose estimation (HPE) technology has attracted attention as a cheaper and simpler method for performing gait analysis than marker-based 3D motion capture systems. However, it remains unclear whether video-based HPE is a feasible method for measuring temporospatial and kinematic gait parameters in patients with PD and how this function varies with camera position.
View Article and Find Full Text PDFExploring Context Allows Us to Better Understand Physical Activity in People with and Without Parkinson's Who Have Fallen: A Mixed Methods Study.
Geriatrics (Basel)
January 2025
Department of Sport, Exercise & Rehabilitation, Northumbria University, Newcastle upon Tyne NE7 7XA, UK.
Falls are a frequent and serious problem for older adults, especially for those living with Parkinson's. The relationship between falls and physical activity is complex, and people often restrict activity following a fall. Exercise is an important aspect of reducing further risk of a fall and a key component of the management of Parkinson's.
View Article and Find Full Text PDFUsing resting-state functional magnetic resonance imaging and contrastive learning to explore changes in the Parkinson's disease brain network and correlations with gait impairment.
Quant Imaging Med Surg
January 2025
Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
Background: There are currently no deep learning models applying resting-state functional magnetic resonance imaging (rs-fMRI) data to distinguish patients with Parkinson's disease (PD) and healthy controls (HCs). Moreover, no study has correlated objective gait parameters with brain network alterations in patients with PD. We propose BrainNetCNN + CL, applying a convolutional neural network (CNN) and joint contrastive learning (CL) method to brain network analysis to classify patients with PD and HCs, and compare their performance with classical classification methods.
View Article and Find Full Text PDFThalamic functional connectivity on 7-Tesla magnetic resonance imaging and its relation to motor signs in early-stage Parkinson's disease.
Quant Imaging Med Surg
January 2025
School of Medicine, Nankai University, Tianjin, China.
Background: It is well known that dysfunction of thalamocortical circuity generates the motor signs that lead to distinct disease processes and prognoses in Parkinson's disease (PD). This study aimed to leverage ultrahigh-field magnetic resonance imaging (MRI) to identify the connectivity alterations of thalamocortical circuity and clarify their relation to motor signs in early PD.
Methods: Patients with early-stage PD (n=55) and healthy controls (HCs, n=56) were recruited from March 2022 to July 2023.
Relationship between freezing of gait in Parkinson disease and locus coeruleus dysfunction: a neuromelanin-sensitive magnetic resonance imaging study.
Quant Imaging Med Surg
January 2025
Emergency and Outpatient Department, China-Japan Union Hospital of Jilin University, Changchun, China.
Background: Preliminary scientific evidence suggests that freezing of gait (FoG) in patients with Parkinson disease (PD) is linked to noradrenergic dysfunction in the locus coeruleus (LC). However, definitive findings regarding the correlation between FoG occurrence and the LC are lacking. This study thus aimed to investigate the relationship between the FoG occurrence and LC degeneration in patients with PD by analyzing the signal characteristics of the LC in neuromelanin-sensitive magnetic resonance imaging (NM-MRI).
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