Title: "BCI Based Interaction Methods for Rehabilitation Robots"
Abstract: We are facing the increasingly serious problem of population aging and the
challenges of assessment, diagnosis, intervention and rehabilitation caused by the high
incidence of stroke and Alzheimer's disease, as well as the shortage of therapists.
Rehabilitation robots are expected to provide technical solutions to these problems and
provide rehabilitation services for patients, families and therapists, but the promotion and
application of rehabilitation robots also face many challenges. For example, efficient, reliable
and safe intelligent interaction and intelligent control are difficulties hindering development
and applications. Considering the acquisition and processing of multimodal biological signals,
brain-computer interface, intervention control and rehabilitation, this talk explores the
opportunities in related fields, as well as thoughts and prospects on the intelligent
development of rehabilitation robots in the future. Bio: Zeng-Guang Hou is a Professor and Deputy Director of the State Key Laboratory
of Management and Control for Complex Systems, Institute of Automation, Chinese Academy
of Sciences (CAS). He is a VP of Chinese Association of Automation (CAA), VP of the Asia
Pacific Neural Network Society (APNNS). Dr. Hou is a CAA/ IEEE Fellow. He also serves as an
AE of IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on
Cognitive and Developmental Systems, and an Editorial Board Member of Neural Networks.
Dr. Hou was a recipient of IEEE Transactions on Neural Networks Outstanding Paper Award
in 2013, and the National Natural Science Award of China in 2017, the Outstanding
Achievement Award of Asia Pacific Neural Network Society (APNNS) in 2017, and the Dennis
Gabor Award of International Neural Network Society (INNS) in 2023.
