Background: Current diagnosis and monitoring of Parkinson's disease (PD) is based on subjective clinical assessments. Objective measures of motor functioning could support clinical acumen. Computer vision (CV) technology is a promising contactless technique but requires further validation.
Aim: To investigate the performance of CV analysis of clinic-based videos of finger-tapping. Our goals were (i) to distinguish PD from healthy controls (HC), when compared to human raters, (ii) to measure the severity of bradykinesia, and (iii) detect ON/OFF medication state.
Methods: Videos of thirty-one persons with PD and forty-nine HC were collected during clinical outpatient visits. Videos were analysed using CV to produce speed, amplitude, rhythm and composite bradykinesia measures. All videos were independently rated by three raters using the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and Modified Bradykinesia Rating Scale (MBRS). Twenty video pairs were conducted in ON and OFF states. Classification accuracy for PD/HC state and ON/OFF state were measured using the Area under Receiver Operating characteristic curve and a confusion matrix. CV and clinical measures were correlated using Spearman coefficients.
Results: CV classified disease state with higher accuracy than clinical raters (91 % sensitivity; 97 % specificity). CV measures of bradykinesia correlated significantly with clinical ratings: R = 0.740 for MDS-UPDRS, 0.715 for MBRS speed, 0.714 for amplitude and 0.504 for rhythm. CV classified ON/OFF state as accurately as clinical raters.
Discussion: CV can provide a valid, objective and contactless bradykinesia assessment based on clinically collected videos, which offers promise as a new clinical outcome, including in remote settings.
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http://dx.doi.org/10.1016/j.jns.2024.123271 | DOI Listing |
Rev Neurol (Paris)
December 2024
Department of Neurology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland.
Introduction: Neuropsychiatric symptoms are highly prevalent in Parkinson's disease (PD) and significantly affect the quality of life of patients and their significant others. The aim of this work is to describe typical neuropsychiatric symptoms and their treatment.
Methods: This is a narrative opinion paper, illustrated by a fictional case report.
Neurobiol Dis
December 2024
Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine Hannover, Bünteweg 17, 30559 Hannover, Germany. Electronic address:
Increasing evidence points to infectious diseases as contributor to the pathogenesis of neurodegeneration in Parkinson's disease (PD), probably driven by a peripheral and CNS inflammatory response together with alpha-synuclein (aSyn) pathology. Pro-inflammatory lipopolysaccharide (LPS) endotoxin is suggested as a risk factor, and LPS shedding gram-negative bacteria are more prevalent in the gut-microbiome of PD patients. Here, we investigated whether LPS could contribute to the neurodegenerative disease progression via neuroinflammation, especially under conditions of aSyn pathology.
View Article and Find Full Text PDFBrain Res
December 2024
Department of Pharmacology, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, São Paulo, Brazil.
Numerous studies have explored the role of cannabinoids in neurological conditions, chronic pain and neurodegenerative diseases. Restoring autophagy has been proposed as a potential target for the treatment of neurodegenerative diseases. In our study, we used a neuroblastoma cell line that overexpresses wild-type α-synuclein to investigate the effects of cannabidiol on autophagy modulation and reduction in the level of cytosolic α-synuclein.
View Article and Find Full Text PDFComput Biol Med
December 2024
School of Engineering, RMIT University, Victoria, Australia. Electronic address:
Background: Changes in voice are a symptom of Parkinson's disease and used to assess the progression of the condition. However, natural differences in the voices of people can make this challenging. Computerized binary speech classification can identify people with PD (PwPD), but its multiclass application to detect the severity of the disease remains difficult.
View Article and Find Full Text PDFActa Neuropathol Commun
December 2024
Department of Physiology & Biophysics, Case Western Reserve University School of Medicine, Cleveland, OH, 44106, USA.
Mitochondrial dysfunction and α-synuclein (αSyn) aggregation are key contributors to Parkinson's Disease (PD). While genetic and environmental risk factors, including mutations in mitochondrial-associated genes, are implicated in PD, the precise mechanisms linking mitochondrial defects to αSyn pathology remain incompletely understood, hindering the development of effective therapeutic interventions. Here, we identify the loss of branched chain ketoacid dehydrogenase kinase (BCKDK) as a mitochondrial risk factor that exacerbates αSyn pathology by disrupting Complex I function.
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