RT Journal Article
T1 Validity of a Fully-Immersive VR-Based Version of the Box and Blocks Test for Upper Limb Function Assessment in Parkinson's Disease
A1 Oña Simbaña, Edwin Daniel
A1 Jardón Huete, Alberto
A1 Cuesta Gómez, Alicia
A1 Sánchez-Herrera Baeza, Patricia
A1 Cano de la Cuerda, Roberto
A1 Balaguer Bernaldo de Quirós, Carlos
AB In recent decades, gaming technology has been accepted as a feasible method forcomplementing traditional clinical practice, especially in neurorehabilitation; however, the viability of using 3D Virtual Reality (VR) for the assessment of upper limb motor function has not been fully explored. For that purpose, we developed a VR-based version of the Box and Blocks Test (BBT), a clinical test for the assessment of manual dexterity, as an automated alternative to the classical procedure. Our VR-based BBT (VR-BBT) integrates the traditional BBT mechanics into gameplay using the Leap Motion Controller (LMC) to capture the user’s hand motion and the Oculus Rift headset to provide a fully immersive experience. This paper focuses on evaluating the validity of our VR-BBT to reliably measure the manual dexterity in a sample of patients with Parkinson’s Disease (PD). For this study, a group of twenty individuals in a mild to moderate stage of PD were recruited.Participants were asked to perform the physical BBT (once) and our proposed VR-BBT (twice) system,separately. Correlation analysis of collected data was carried out. Statistical analysis proved that the performance data collected by the VR-BBT significantly correlated with the conventional assessment of the BBT. The VR-BBT scores have shown a significant association with PD severity measured by the Hoehn and Yahr scale. This fact suggests that the VR-BBT could be used as a reliable indicator for health improvements in patients with PD. Finally, the VR-BBT system presented high usability and acceptability rated by clinicians and patients.
PB MDPI
SN 1424-8220
YR 2020
FD 2020-05-13
LK https://hdl.handle.net/10016/32862
UL https://hdl.handle.net/10016/32862
LA eng
NO This work was supported in part by the Spanish Ministry of Economy and Competitiveness via theROBOESPAS project (DPI2017-87562-C2-1-R), and in part by the RoboCity2030-DIH-CM, Madrid Robotics Digital Innovation Hub (S2018/NMT-4331), which is funded by the Programas de Actividades I+D Comunidad de Madrid and cofunded by the Structural Funds of the EU.
DS e-Archivo
RD 27 jul. 2024