AUTHOR=Wiratman Winnugroho , Kobayashi Shunsuke , Chang Fang-Yu , Asano Kohei , Ugawa Yoshikazu 

TITLE=Assessment of Cognitive and Motor Skills in Parkinson's Disease by a Robotic Object Hitting Game

JOURNAL=Frontiers in Neurology

VOLUME=Volume 10 - 2019

YEAR=2019

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2019.00019

DOI=10.3389/fneur.2019.00019

ISSN=1664-2295

ABSTRACT=Parkinson’s disease (PD) patients suffer from various symptoms including extrapyramidal motor disturbances and cognitive impairments. Presumably, both cognitive and motor impairments are causing difficulties in daily life. However, PD patients have rarely been studied under realistic task situations that require high-level interaction of cognitive and motor skills. The aim of this study was to investigate contribution of cognitive and motor factors to performance of PD patients when they are placed under high cognitive and kinematic loads. Twenty-six PD patients and 14 control subjects participated in the study. PD patients performed a task to hit targets and avoid distractors in levodopa On and Off states. A robotic manipulandum device recorded the numbers of target and distractor hit and hand kinematics, including movement area and speed. Standard cognitive batteries and MDS-UPDRS motor scores were examined. Results showed that the PD patients hit significantly fewer targets and more distractors than controls (p < 0.05). In PD patients, average hand speed was slower, and the area of hand movement was smaller as compared with the control subjects (p < 0.001). Levodopa increased the average hand speed and movement area significantly (p < 0.01), but levodopa had insignificant effect on the number of correct target hit and erroneous distractor hit. The scores of cognitive batteries predicted performance of both target hit and distractor avoidance. Our result suggests a dynamic interaction between cognitive and kinematic skills while PD patients performed a virtual reality game. Single-dose levodopa enhanced kinematic capacity and global intelligence level predicted the game performance.