Evaluating A VR-based Box and Blocks Test for Automatic Assessment of Manual Dexterity: A Preliminary Study in Parkinson’s Disease

Opportunities of using Virtual Reality (VR) techno-logy for the automation of clinical procedures in general, and for the assessment of motor function in particular, have not been fully explored in Parkinson’ disease (PD). For that purpose, a game-like version of the Box and Blocks Test (BBT) for automatic assessment of hand motor function in VR was built. This system uses the Leap Motion Controller (LMC) for hand tracking and the Oculus Rift for a fully immersive experience. In this paper, we focus on evaluating the capabilities of our VR-BBT to reliably measure the manual dexterity in a sample of PD patients. For this study, a group of nine individuals in mild to moderate stage of PD were recruited. Participants were asked to perform both the physical BBT and the VR-BBT systems. Correlation analysis of collected data was carried out comparing the BBT and VR-BBT assessments. The test-retest reliability was also explored for the scores gathered with the virtual tool. Statistical analysis proved that the performance data collected by the game-like system correlated with the validated measures of the physical BBT, with a strong test-retest reliability. This fact suggests that the virtual version of the BBT could be used as a valid and reliable indicator for health improvements.
Edwin Daniel Oña Simbaña
Alicia Cuesta Gomez
Jaime A. Garcia
William Raffe
Patricia Sanchez-Herrera
Roberto Cano de la Cuerda
Alberto Jardon
Presented At
7th International Conference on Serious Games and Applications for Health, IEEE SeGAH 2019
Conference Proceedings