Page 154 - Handbook of Biomechatronics

Biomechatronic Applications of Brain-Computer Interfaces 151

drink a mug of coffee; 717days after implantation, he was able to feed him-
self. While the participant still needed a mobile arm support (which was also
BCI-controlled) to help move his weakened arm, such technology repre-
sents a promising step toward restoring independence of people with severe
disabilities. A simpler noninvasive BCI-stimulation combination was
recently presented by Gant et al. (2018), who used a motor-imagery-based
BCI to control only the opening and closing of the hand through electrical
stimulation with a classification accuracy (open vs close) of 75%. Further-
more, a similar noninvasive system by Soekadar et al. (2016) combines a
motor-imagery-based BCI to control a hand exoskeleton (rather than elec-
trical stimulator) that opens and closes the hand of individuals with
tetraplegia. While not as effective as implanted BCI systems, such
imagery-based BCIs may still become popular among users who wish to
restore their limb function but are unwilling to undergo brain surgery.
An approach similar to the one of Ajiboye et al. (2017) was recently also
presented for the lower limbs by Capogrosso et al. (2016), who implanted
intracortical electrodes and an epidural spinal cord stimulation system into a
monkey with a corticospinal tract lesion at the thoracic level. Six days after
the spinal cord injury, the monkey was able to walk again without any train-
ing, both on a treadmill and over normal ground. Similar results have also
been achieved in rats (Knudsen and Moxon, 2017); while no successful tests
have been performed with humans, first experiments are expected in the
near future, and the technology has great potential to further increase the
functional independence of people with tetraplegia.

2.5 Communication Devices
BCIs can also be used for communication by people with severe disabilities
that prevent them from both moving their limbs and speaking. As long as
users can still move their eyes and read, they can make use of BCI
spellers—devices that allow them to spell out letters and words via SSVEPs,
P300 responses, and motor imagery (Rezeika et al., 2018). While the speed
of such communication is not very fast compared to typing on a keyboard by
able-bodied people (with information transfer rates of BCI spellers ranging
from 5 to 25bits/min in users with disabilities (Rezeika et al., 2018)), it
nonetheless serves as a valuable tool for users with, for example, locked-
in syndrome, who cannot communicate in any other way.
One of the earliest BCI spellers was a matrix-based P300 speller devel-
oped by Farwell and Donchin (1988). Users are given a screen that shows a