Swing time as a predictive variable for Parkinson’s disease

ABSTRACT

Currently, Parkinson’s Disease (PD) is diagnosed based only on the clinical observation of a combination of symptoms, which can lead to late diagnosis, since some individuals may have the disease for 5 to 10 years before being diagnosed. The aim was to identify temporal kinematic variables of walking, capable of discriminating elderly people with and without PD. 40 individuals were divided into two groups: elderly group without PD (n=21) and with PD (n=19). Ten consecutive gait cycles were obtained during walking at a preferred speed and used for data analysis. A discriminative analysis was performed to determine a predictor model of gait changes, characteristic of PD and calculated based on the specificity and sensitivity of each variable analyzed, using temporal kinematic variables. The variable with discriminative value of sensitivity and specificity was the time of balance, which can be classified as the variable with most predictive potential of the presence or not of PD, and the cut of found for this variable was 0,48 seconds. The kinematic gait analysis allows to discriminate a group of individuals with PD from a group of healthy individuals with high sensitivity and specificity, through the time of balance that is lower in the group affected by the disease (cut of 0,48 seconds).

Keywords
Parkinson’s Disease; Gait; Kinematics; Early Diagnosis