PMID- 33320813
OWN - NLM
STAT- MEDLINE
DCOM- 20210624
LR  - 20210624
IS  - 1558-0210 (Electronic)
IS  - 1534-4320 (Linking)
VI  - 28
IP  - 12
DP  - 2020 Dec
TI  - Optimization of Visual Stimulus Sequence in a Brain-Computer Interface Based on 
      Code Modulated Visual Evoked Potentials.
PG  - 2762-2772
LID - 10.1109/TNSRE.2020.3044947 [doi]
AB  - Brain-computer interfaces based on code-modulated visual evoked potentials 
      provide high information transfer rates, which make them promising alternative 
      communication tools. Circular shifts of a binary sequence are used as the 
      flickering pattern of several visual stimuli, where the minimum correlation 
      between them is critical for recognizing the target by analyzing the EEG signal. 
      Implemented sequences have been borrowed from communication theory without 
      considering visual system physiology and related ergonomics. Here, an approach is 
      proposed to design optimum stimulus sequences considering physiological factors, 
      and their superior performance was demonstrated for a 6-target c-VEP BCI system. 
      This was achieved by defining a time-factor index on the frequency response of 
      the sequence, while the autocorrelation index ensured a low correlation between 
      circular shifts. A modified version of the non-dominated sorting genetic 
      algorithm II (NSGAII) multi-objective optimization technique was implemented to 
      find, for the first time, 63-bit sequences with simultaneously optimized 
      autocorrelation and time-factor indexes. The selected optimum sequences for 
      general (TFO) and 6-target (6TO) BCI systems, were then compared with m-sequence 
      by conducting experiments on 16 participants. Friedman tests showed a significant 
      difference in perceived eye irritation between TFO and m-sequence (p = 0.024). 
      Generalized estimating equations (GEE) statistical test showed significantly 
      higher accuracy for 6TO compared to m-sequence (p = 0.006). Evaluation of EEG 
      responses showed enhanced SNR for the new sequences compared to m-sequence, 
      confirming the proposed approach for optimizing the stimulus sequence. 
      Incorporating physiological factors to select sequence(s) used for c-VEP BCI 
      systems improves their performance and applicability.
FAU - Behboodi, Mohammadreza
AU  - Behboodi M
FAU - Mahnam, Amin
AU  - Mahnam A
FAU - Marateb, Hamidreza
AU  - Marateb H
FAU - Rabbani, Hossein
AU  - Rabbani H
LA  - eng
SI  - figshare/10.6084/m9.figshare.11316326
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20210128
PL  - United States
TA  - IEEE Trans Neural Syst Rehabil Eng
JT  - IEEE transactions on neural systems and rehabilitation engineering : a 
      publication of the IEEE Engineering in Medicine and Biology Society
JID - 101097023
SB  - IM
MH  - *Brain-Computer Interfaces
MH  - Electroencephalography
MH  - Evoked Potentials, Visual
MH  - Humans
MH  - Neurologic Examination
MH  - Photic Stimulation
EDAT- 2020/12/16 06:00
MHDA- 2021/06/25 06:00
CRDT- 2020/12/15 17:12
PHST- 2020/12/16 06:00 [pubmed]
PHST- 2021/06/25 06:00 [medline]
PHST- 2020/12/15 17:12 [entrez]
AID - 10.1109/TNSRE.2020.3044947 [doi]
PST - ppublish
SO  - IEEE Trans Neural Syst Rehabil Eng. 2020 Dec;28(12):2762-2772. doi: 
      10.1109/TNSRE.2020.3044947. Epub 2021 Jan 28.