TY - GEN
T1 - Directed neural connectivity changes in robot-assisted gait training
T2 - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
AU - Youssofzadeh, Vahab
AU - Zanotto, Damiano
AU - Stegall, Paul
AU - Naeem, Muhammad
AU - Wong-Lin, Kongfatt
AU - Agrawal, Sunil K.
AU - Prasad, Girijesh
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/11/2
Y1 - 2014/11/2
N2 - Now-a-days robotic exoskeletons are often used to help in gait training of stroke patients. However, such robotic systems have so far yielded only mixed results in benefiting the clinical population. Therefore, there is a need to investigate how gait learning and de-learning get characterised in brain signals and thus determine neural substrate to focus attention on, possibly, through an appropriate brain-computer interface (BCI). To this end, this paper reports the analysis of EEG data acquired from six healthy individuals undergoing robot-assisted gait training of a new gait pattern. Time-domain partial Granger causality (PGC) method was applied to estimate directed neural connectivity among relevant brain regions. To validate the results, a power spectral density (PSD) analysis was also performed. Results showed a strong causal interaction between lateral motor cortical areas. A frontoparietal connection was found in all robot-assisted training sessions. Following training, a causal 'top-down' cognitive control was evidenced, which may indicate plasticity in the connectivity in the respective brain regions.
AB - Now-a-days robotic exoskeletons are often used to help in gait training of stroke patients. However, such robotic systems have so far yielded only mixed results in benefiting the clinical population. Therefore, there is a need to investigate how gait learning and de-learning get characterised in brain signals and thus determine neural substrate to focus attention on, possibly, through an appropriate brain-computer interface (BCI). To this end, this paper reports the analysis of EEG data acquired from six healthy individuals undergoing robot-assisted gait training of a new gait pattern. Time-domain partial Granger causality (PGC) method was applied to estimate directed neural connectivity among relevant brain regions. To validate the results, a power spectral density (PSD) analysis was also performed. Results showed a strong causal interaction between lateral motor cortical areas. A frontoparietal connection was found in all robot-assisted training sessions. Following training, a causal 'top-down' cognitive control was evidenced, which may indicate plasticity in the connectivity in the respective brain regions.
UR - http://www.scopus.com/inward/record.url?scp=84929493202&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84929493202&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2014.6945083
DO - 10.1109/EMBC.2014.6945083
M3 - Conference contribution
C2 - 25571451
AN - SCOPUS:84929493202
T3 - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
SP - 6361
EP - 6364
BT - 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Y2 - 26 August 2014 through 30 August 2014
ER -