Supervised classification of bradykinesia in Parkinson's disease from smartphone videos by Stefan Williams, Samuel D Relton, Hui Fang, Jane Alty, Rami Qahwaji, Christopher D Graham, David C Wong

“…Dimensionality reduction was undertaken using principal component analysis before input to classification models (Naive Bayes, Logistic Regression, Support Vector Machine) to predict no/slight bradykinesia (UPDRS = 0-1) or mild/moderate/severe bradykinesia (UPDRS = 2-4), and presence or absence of Parkinson’s diagnosis. …”
Get full text

Consumer packaging: the development of normative data for able-bodied and disabled people by Tomas Berns

“…The consumers used in the study included male and female able-bodied subjects, some of whom were elderly; and the disabled, who suffered from arthritis, Parkinson's disease, cerebral palsy, multiple sclerosis, or one-handed function (hemiplegics or amputees). …”
Get full text