TY - JOUR
T1 - The Effects of a Virtual Reality Rehabilitation Task on Elderly Subjects
T2 - An Experimental Study Using Multimodal Data
AU - Qu, Jing
AU - Cui, Lizhen
AU - Guo, Wei
AU - Ren, Xipei
AU - Bu, Lingguo
N1 - Publisher Copyright:
© 2022 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
PY - 2022
Y1 - 2022
N2 - Ageing populations are becoming a global issue. Against this background, the assessment and treatment of geriatric conditions have become increasingly important. This study draws on the multisensory integration of virtual reality (VR) devices in the field of rehabilitation to assess brain function in young and old people. The study is based on multimodal data generated by combining high temporal resolution electroencephalogram (EEG) and subjective scales and behavioural indicators reflecting motor abilities. The phase locking value (PLV) was chosen as an indicator of functional connectivity (FC), and six brain regions, namely LPFC, RPFC, LOL, ROL, LMC and RMC, were analysed. The results showed a significant difference in the alpha band on comparing the resting and task states in the younger group. A significant difference between the two states in the alpha and beta bands was observed when comparing task states in the younger and older groups. Meanwhile, this study affirms that advancing age significantly affects human locomotor performance and also has a correlation with cognitive level. The study proposes a novel accurate and valid assessment method that offers new possibilities for assessing and rehabilitating geriatric diseases. Thus, this method has the potential to contribute to the field of rehabilitation medicine. copy 2001-2011 IEEE.
AB - Ageing populations are becoming a global issue. Against this background, the assessment and treatment of geriatric conditions have become increasingly important. This study draws on the multisensory integration of virtual reality (VR) devices in the field of rehabilitation to assess brain function in young and old people. The study is based on multimodal data generated by combining high temporal resolution electroencephalogram (EEG) and subjective scales and behavioural indicators reflecting motor abilities. The phase locking value (PLV) was chosen as an indicator of functional connectivity (FC), and six brain regions, namely LPFC, RPFC, LOL, ROL, LMC and RMC, were analysed. The results showed a significant difference in the alpha band on comparing the resting and task states in the younger group. A significant difference between the two states in the alpha and beta bands was observed when comparing task states in the younger and older groups. Meanwhile, this study affirms that advancing age significantly affects human locomotor performance and also has a correlation with cognitive level. The study proposes a novel accurate and valid assessment method that offers new possibilities for assessing and rehabilitating geriatric diseases. Thus, this method has the potential to contribute to the field of rehabilitation medicine. copy 2001-2011 IEEE.
KW - EEG
KW - multimodal data
KW - rehabilitation assessment
KW - virtual reality
UR - https://www.scopus.com/pages/publications/85132781796
U2 - 10.1109/TNSRE.2022.3183686
DO - 10.1109/TNSRE.2022.3183686
M3 - Article
C2 - 35709115
AN - SCOPUS:85132781796
SN - 1534-4320
VL - 30
SP - 1684
EP - 1692
JO - IEEE Transactions on Neural Systems and Rehabilitation Engineering
JF - IEEE Transactions on Neural Systems and Rehabilitation Engineering
ER -
