4.3.2 Blink Detection
For blink detection, we developed the Continuous Wavelet
Transform—Blink Detection (CWT-BD) algorithm. Similarly to
CWT-SD, the algorithm uses a threshold thbd on the wavelet
coefficients to detect blinks in EOGv. In contrast to a saccade,
a blink is characterized by a sequence of two large peaks in
the coefficient vector directly following each other: one
positive, the other negative. The time between these peaks is
smaller than the minimum time between two successive
saccades rapidly performed in opposite direction. This is
because, typically, two saccades have at least a short fixation
in between them. For this reason, blinks can be detected by
applying a maximum threshold thbdt on this time difference.
We evaluated our algorithm on EOG signals recorded in a
stationary setting from five participants looking at different
pictures (two females and three males, age: 25-29 years,
mean ¼ 26:4, sd ¼ 1:7). We labeled a total of 706 blinks by
visual inspection of the vertical EOG signal component. With
an average blink rate of 12 blinks perminute, this corresponds
to about one hour of eye movement data.We evaluated CWTBD
over sweeps of its two main parameters: thbd ¼
100 . . . 50;000 (in 500 steps) and thbdt ¼ 100 . . . 1;000 ms (in
10 steps).
The F1 score was calculated by matching blink events
with the annotated ground truth. Fig. 6 shows the F1 scores
for five selected values of thbdt over all participants. CWTBD
performs best with thbdt between 400 and 600 ms while
reaching top performance (F1 score: 0.94) using a thbdt of
500 ms. Time differences outside this range, as exemplarily
shown for 300 and 1,000 ms, are already subject to a
considerable drop in performance. This finding nicely
reflects the values for the average blink duration cited
earlier from the literature.