Brain–Machine Interfaces Based on Computational Model

  • Yasuharu Koike
  • Hiroyuki Kambara
  • Natsue Yoshimura
  • Duk Shin


The research about brain computer interface or brain machine interface has been widely developed in this decade. Implant methods are already used for eye or ear as retinal implant or cochlear implant, these devices stimulate peripheral nerve. In this case, the stimulus site is peripheral and the information from each sensor is input signal of the brain. Brain Machine Interface measure or stimulate neuron in the brain directly and decode neuronal firings to generate information. It is impossible to measure all neuron activities from brain, because of enormous quantity of neurons and also the function is unknown. So anatomical knowledge, such as a cortical homunculus of the primary motor cortex and the primary somatosensory cortex, or neural scientific knowledge is used.

The process of movement from the primary motor cortex to muscle is forward direction, and the number of neurons are decrease in this process. The generation of muscle activities are straightforward. In the field of motor control, motor command generation is still open problem. There are many theories are proposed. In order to evaluate or verify these theories, the technique of BMI is also useful. In this chapter, we introduce musculo-skeletal model and computational model for movement, and also some examples of BMI/BCI.


Joint Angle Supplementary Motor Area Motor Command Primary Motor Cortex Joint Torque 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer 2011

Authors and Affiliations

  • Yasuharu Koike
    • 1
    • 2
  • Hiroyuki Kambara
    • 1
  • Natsue Yoshimura
    • 1
  • Duk Shin
    • 1
  1. 1.Tokyo Institute of TechnologyYokohamaJapan
  2. 2.JST CRESTKawaguchiJapan

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