Designed for people with severe disabilities, the Toyota/RIKEN wheelchair is fitted with an EEG detector in the form of a electrode array skull cap, a cheek puff detector and a display that assists with control. To turn left, right and move forward, the driver simply thinks about the movement and the wheelchair instantly and seamlessly responds. To stop the wheelchair, the driver puffs his/her cheek. A detector on the face picks up the signal and immediately stops the wheelchair. This form of braking is necessary for safety reasons as a puff detector is more reliable than the EEG reader.
A brief history of EEG
- 1875 Richard Caton (1842-1926) reports the electrical phenomena of the exposed brains of rabbits and monkeys
- 1929 Hans Berger (1873-1941) discovers the human EEG
- 1932 J. F. Toennies (1902-1970) invents the first ink-writing EEG recorder
- 1965 computer based system with superior analysis is developed by Cooley and Tukey
- 1990s Increasing use of EEG combined with neuro-imaging techniques emerges; real-time digital EEG monitoring for critical care becomes important in intensive care units, operating rooms, and emergency rooms; improved algorithms for analyzing EEG results in new applications and possibilities for cognitive neurosciences and Brain Machine Interfaces
- June 2009 Toyota and RIKEN announce their development of a thought controlled wheelchair
March 2009 Honda creates a BMI that allows the control of an Asimo robot using thought alone via EEG
Why brain waves are difficult to work with
Previous attempts all around the world to use brain waves to control devices have only been partially successful. One of the biggest problems with EEG signals is that on the surface of the skull they are in the order of micro-volts (millionth of a volt) and prone to electrical noise. Another problem is that reliable and repeatable placement of EEG electrodes on specific areas above the brain is hard to achieve. Electrodes are typically held in place using caps or other harnesses. Any movement by the patient is bound to create noise and artifacts that are hard to eliminate. Finally, the EEG waves themselves are difficult to interpret. Each signal is a composite of the electrical activity of billions of brain cells working in unison. So while the brain waves are certainly a result of the activity of the brain and its thought processes, the signals are so complicated that we still don’t fully understand them.
Toyota and RIKEN have made a breakthrough in the field by refining the analysis algorithms, signal processing and noise elimination to the point that their device can detect discreet thought processes and use them to trigger events such as driving a wheelchair forward, left or right. Furthermore, by being able to reduce the latency of the processing response to just 125 milliseconds (1/8 of a second) they have created one of the fastest such systems in the world, allowing real-time control.
The system fuses RIKEN’s blind signal separation* and space-time-frequency Filtering** technology to allow rapid brain-wave analysis and display the results on a panel so quickly that drivers do not sense any delay. The system has the capacity to adjust itself to the characteristics of each individual driver, and thereby is able to improve the efficiency with which it senses the driver’s commands. As a result, the driver is able to get the system to learn his/her commands (forward/right/left) with very little training. The new system has succeeded in having drivers correctly give commands to their wheelchairs with an accuracy rate of 95%, one of the highest in the world.
Plans are underway to utilize this technology in a wide range of applications centered on medicine, rehabilitation and nursing care management. R&D under consideration includes increasing the number of commands given and developing more efficient dry electrodes. So far the research has centered on brain waves related to imaginary hand and foot control. However, through further measurement and analysis it is anticipated that this system may be applied to other types of brain waves generated by various mental states and emotions.
As exciting as this development is, there are no current plans to commercialize the technology. This is also true for Honda’s work on EEG detection. This is possibly because outside of the research laboratories, it is very hard to make a robust and reliable EEG detector that the lay consumer can operate. So for the time being we are all going to wait a bit longer for our brain controlled personal transport systems.
* Blind signal separation (BSS) is a technology that separates the noise components and useful signal components from brain signals that can be used to control the wheelchair. It utilizes only on-line-recorded EEG signals.
** Space-time-frequency filtering is a technology which extracts space and time patterns and frequency oscillation data from EEG electrodes to discriminate significant features and components which are able to reliably control the wheelchair.