Measurement of Brain Activity Using Optical and Electrical Methods
203
using learning algorithms can potentially increase the success rate of the
experiment. It is important to notice that bioelectrical signals from the brain
were not used. The use of bioelectrical signals could increase the accuracy
of the test.
10.7 Conclusion
In this chapter, a hybrid sensor that can collect both bioelectrical and optical data from the same spot on the scalp was developed and evaluated in
order to measure brain activity. Data analysis during and after the experiments showed that the bioelectrical data collected by the hybrid sensor
were very similar to the data collected by an ordinary disposable electrode.
Similarly, the optical data collected by the hybrid sensor were similar to the
data collected using a standard functioning near-infrared imaging device.
Our next step is to use this new technology to accurately register the user’s
movement intentions and use these data to accurately control assistive devices.
References
Hayashi, T., Kawamoto, H., and Sankai, Y. 2005. Control method of RobotSuit HAL
working as operator’s muscle using biological and dynamical information. IEEE/
RSJ International Conference on Intelligent Robots and Systems, Edmonton,
Canada, August 2–6, 2005.
Johnson, C. and Guy, A. 1972. Nonionizing electromagnetic wave effect in biological
matherials and systems. Proceedings of the IEEE, 60(6): 692–718.
Kato, T. 2004. Principle and technique of NIRS-Imaging for human brain FORCE:
Fast-oxygen response in capillary event. International Congress Series, 1270:
85–90.
Kawamoto, H. and Sankai, Y. 2005. Power assist method based on PhaseSequence and
muscle force condition for HAL. Advanced Robotics, 19(7): 717–734.
Koizumi, H., Maki, A., Yamamoto, T., Sato, H., Yamamoto, Y. and Kawaguchi, H..
2005. Non-invasive brain-function imaging by optical topography. Trends in
Analytical Chemistry, 24(2): 147–156.
Koizumi, H., Yamamoto, T., Maki, A., Yamashita, Y., Sato, H., Kawaguchi, H. and
Ichikawa, N. 2003. Optical topography: practical problems and new applications. Applied Optics, 42(16): 3054–3062.
Lee, S. and Sankai, Y. 2003. The natural frequency-based power assist control for lower
body with HAL-3. International Conference on Systems, Man and Cybernetics,
Washington, DC, October 5–8, 2003.
203
using learning algorithms can potentially increase the success rate of the
experiment. It is important to notice that bioelectrical signals from the brain
were not used. The use of bioelectrical signals could increase the accuracy
of the test.
10.7 Conclusion
In this chapter, a hybrid sensor that can collect both bioelectrical and optical data from the same spot on the scalp was developed and evaluated in
order to measure brain activity. Data analysis during and after the experiments showed that the bioelectrical data collected by the hybrid sensor
were very similar to the data collected by an ordinary disposable electrode.
Similarly, the optical data collected by the hybrid sensor were similar to the
data collected using a standard functioning near-infrared imaging device.
Our next step is to use this new technology to accurately register the user’s
movement intentions and use these data to accurately control assistive devices.
References
Hayashi, T., Kawamoto, H., and Sankai, Y. 2005. Control method of RobotSuit HAL
working as operator’s muscle using biological and dynamical information. IEEE/
RSJ International Conference on Intelligent Robots and Systems, Edmonton,
Canada, August 2–6, 2005.
Johnson, C. and Guy, A. 1972. Nonionizing electromagnetic wave effect in biological
matherials and systems. Proceedings of the IEEE, 60(6): 692–718.
Kato, T. 2004. Principle and technique of NIRS-Imaging for human brain FORCE:
Fast-oxygen response in capillary event. International Congress Series, 1270:
85–90.
Kawamoto, H. and Sankai, Y. 2005. Power assist method based on PhaseSequence and
muscle force condition for HAL. Advanced Robotics, 19(7): 717–734.
Koizumi, H., Maki, A., Yamamoto, T., Sato, H., Yamamoto, Y. and Kawaguchi, H..
2005. Non-invasive brain-function imaging by optical topography. Trends in
Analytical Chemistry, 24(2): 147–156.
Koizumi, H., Yamamoto, T., Maki, A., Yamashita, Y., Sato, H., Kawaguchi, H. and
Ichikawa, N. 2003. Optical topography: practical problems and new applications. Applied Optics, 42(16): 3054–3062.
Lee, S. and Sankai, Y. 2003. The natural frequency-based power assist control for lower
body with HAL-3. International Conference on Systems, Man and Cybernetics,
Washington, DC, October 5–8, 2003.