ABSTRACT
Parkinson's disease (PD) is a common neurological disorder, with bradykinesia being one of its cardinal features. Objective quantification of bradykinesia using computer vision has the potential to standardise decision-making, for patient treatment and clinical trials, while facilitating remote assessment. We utilised a dataset of part-3 MDS-UPDRS motor assessments, collected at four independent clinical and one research sites on two continents, to build computer-vision-based models capable of inferring the correct severity rating robustly and consistently across all identifiable subgroups of patients. These results contrast with previous work limited by small sample sizes and small numbers of sites. Our bradykinesia estimation corresponded well with clinician ratings (interclass correlation 0.74). This agreement was consistent across four clinical sites. This result demonstrates how such technology can be successfully deployed into existing clinical workflows, with consumer-grade smartphone or tablet devices, adding minimal equipment cost and time.
ABSTRACT
Spontaneous spinal cord infarction is significantly less common than cerebrovascular disease. Because of the tight anatomical distribution of pathways in the cord, small spinal cord infarcts usually give more obvious symptoms and signs than similar lesions in the brain. Large epidemiological stroke studies have generally not included spinal cord stroke and so the incidence of vascular syndromes in the spinal cord is unknown. Management and prevention strategies for spontaneous spinal cord infarcts stem from small case series and case reports. Patient outcomes from spinal cord infarction are better with prompt recognition, timely management and prevention of associated medical complications arising from paraplegia, tetraplegia, neurogenic bladder and bowel dysfunction. The process of rehabilitation following spinal cord infarction is an evolving area.
