Brain–Computer Interfaces - Index of

BCIs Based on Signals from Between the Brain and Skull 231
Subjects and Actions
Subjects who participated in the UM-DBI project studies were patients in either
the University of Michigan Epilepsy Surgery Program or the Henry Ford Hospital
Comprehensive Epilepsy Program and had signed consent forms approved by the
appropriate institutional review board. Early subjects of the UM-DBI project performed
a battery of discrete movements while ECoG was recorded for off-line
analysis [3, 27]. Later subjects performed only a few actions and then participated
in feedback experiments [28], described below. Actions were sometimes modified
to target unique areas over which the individual subject’s electrodes were placed or
to accommodate a subject’s physical impairments. The most common actions were
a pinch movement, extension of the middle finger, tongue protrusion, and lip protrusion
(a pouting motion). The actions ankle flexion and saying a phoneme (“pah”
or “tah”) were also used with some frequency. Subjects repeated a single action
approximately 50 times over a period of several minutes. The time at which each
repetition of the action was performed was documented with recorded EMG (or
another measure of physical performance [3]). For each subject, the ECoG related
to a particular action was visualized using triggered averaging and/or spectral analysis
of the event-related desynchronization (ERD) and event-related synchronization
(ERS) [29] (seeFig.4). This analysis showed the localized nature of the ECoG
related to particular actions and also revealed features that could be used for BCI
detection analysis.
Training and Testing Data and Performance Markup
Detection experiments were generally done on ECoG from single electrodes (e.g.
[26, 30]) with only an initial exploration of the beneficial effects of using combinations
of channels [31]. The first half of the repetitions of an action were used for
training the detection method and the second half of the repetitions were used for
testing. Detection method testing produced an activation/no activation decision for
each sample in the several-minute duration of the test data. An activation was considered
to be valid (a “hit”) if it occurred within a specified activation acceptance
window around one of the actions as shown by EMG recording. False activations
were defined as activations that occurred outside this acceptance window. The
dimensions of the acceptance window used for individual experiments are reported
below along with the results.
The HF-Difference
The UM-DBI project introduced a performance measure called the HF-difference
for evaluation of BCI performance. The HF-difference is the difference between the
hit percentage and a false activation percentage, with both of these measures calculated
from a user’s perspective. A user’s perception of how well a BCI detected their
commands would be based on how many times they tried to use the BCI. Therefore,
the hit percentage is the percentage of actions performed by the subject that were