Prediction of Alzheimer's disease in patients using features of pupil light reflex to chromatic stimuli

Abstract

A diagnostic procedure to predict the probability of diagnosing a patient with Alzheimer's Disease (AD) was developed using features of pupil light reflex (PLR) waveforms. 15 features of PLRs for three colours of light pulses at two levels of brightness were measured. Participants were 12 AD patients and 7 control group subjects. A logistic regression analysis was introduced to identify AD patients using two factor scores of features of PLR. The prediction performance of combinations of factor scores for features of PLRs were then evaluated using a test of fitness. An MCMC technique was introduced to estimate the parameters of the regression functions. The model provides a distribution of the probability of diagnosis of AD patients and control group subjects.