Paper Info
Title
Clinical Application of Implantable Brain Machine Interfaces
Abstract
Implantable brain machine interfaces (BMI) enable severely disabled people high-performance real-time robot control and communication, utilizing high-quality intracranial neural signals. Electrocorticograms (ECoG) are useful for implantable BMIs because of not only their zero time-lag property but their high spatiotemporal resolution with long term stability also. Fully implantable devices for ECoG recording offer long-term home-use with 24/7 supports. This will help not only patients with restoring motor and communication control but also help their caregivers with reducing burdens of caregiving day and night. Until now, we established ECoG-based robot control and communication. High gamma activity (80-150 Hz) was a good decoding feature for ECoG-based real time decoding and control. Independent component analyses effectively extract neural information with dimensional reduction and contribute to improving decoding accuracy. Also, we are developing a 128-channel fully-implantable BMI device (WHERBS) for long-term home-use with 24/7 supports. We completed GLP tests and non-clinical long-term implantation. The next step is a clinical trial to confirm safety and efficacy of the implantable BMI.
Year
DOI
Venue
2018
10.1109/SMC.2018.00031
2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC)
Keywords
Field
DocType
brain machine interface,implantable device,electrocorticogram,clinical trial,high gamma activity
Robot control,Computer science,Brain–computer interface,Artificial intelligence,Decoding methods,Computer hardware,Machine learning
Conference
ISSN
ISBN
Citations 
1062-922X
978-1-5386-6651-7
0
PageRank 
References 
Authors
0.34
0
8
Name
Order
Citations
PageRank
Masayuki Hirata15413.79
Seiji Kameda2257.10
Jason Palmer300.34
Hiroshi Ando4399.20
Takafumi Suzuki5102.71
Yinlai Jiang61011.72
Hiroshi Yokoi738392.58
Yasuharu Koike835762.78