TY - JOUR
T1 - Evaluation of a Compact Hybrid Brain-Computer Interface System
AU - Shin, Jaeyoung
AU - Müller, Klaus Robert
AU - Schmitz, Christoph H.
AU - Kim, Do Won
AU - Hwang, Han Jeong
N1 - Funding Information:
This research was mainly supported by Business for Cooperative R&D between Industry, Academy, and Research Institute funded Korea Small and Medium Business Administration in 2016 (Grants no. S2380249). The research was also supported in part by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2014R1A6A3A03057524) and the Ministry of Science, ICT & Future Planning (NRF-2015R1C1A1A02037032) and by the BK21 program of NRF and by US/NIH Grant 1R21NS067278. Additionally we acknowledge funding by BMBF 01GQ0831 and BMBF 01GQ0850 and the German Research Foundation (DFG, KU 1453-1). Some equipment was generously provided by NIRx Medizintechnik GmbH, Berlin.
Publisher Copyright:
© 2017 Jaeyoung Shin et al.
PY - 2017
Y1 - 2017
N2 - We realized a compact hybrid brain-computer interface (BCI) system by integrating a portable near-infrared spectroscopy (NIRS) device with an economical electroencephalography (EEG) system. The NIRS array was located on the subjects' forehead, covering the prefrontal area. The EEG electrodes were distributed over the frontal, motor/temporal, and parietal areas. The experimental paradigm involved a Stroop word-picture matching test in combination with mental arithmetic (MA) and baseline (BL) tasks, in which the subjects were asked to perform either MA or BL in response to congruent or incongruent conditions, respectively. We compared the classification accuracies of each of the modalities (NIRS or EEG) with that of the hybrid system. We showed that the hybrid system outperforms the unimodal EEG and NIRS systems by 6.2% and 2.5%, respectively. Since the proposed hybrid system is based on portable platforms, it is not confined to a laboratory environment and has the potential to be used in real-life situations, such as in neurorehabilitation.
AB - We realized a compact hybrid brain-computer interface (BCI) system by integrating a portable near-infrared spectroscopy (NIRS) device with an economical electroencephalography (EEG) system. The NIRS array was located on the subjects' forehead, covering the prefrontal area. The EEG electrodes were distributed over the frontal, motor/temporal, and parietal areas. The experimental paradigm involved a Stroop word-picture matching test in combination with mental arithmetic (MA) and baseline (BL) tasks, in which the subjects were asked to perform either MA or BL in response to congruent or incongruent conditions, respectively. We compared the classification accuracies of each of the modalities (NIRS or EEG) with that of the hybrid system. We showed that the hybrid system outperforms the unimodal EEG and NIRS systems by 6.2% and 2.5%, respectively. Since the proposed hybrid system is based on portable platforms, it is not confined to a laboratory environment and has the potential to be used in real-life situations, such as in neurorehabilitation.
UR - http://www.scopus.com/inward/record.url?scp=85015871799&partnerID=8YFLogxK
U2 - 10.1155/2017/6820482
DO - 10.1155/2017/6820482
M3 - Article
C2 - 28373984
AN - SCOPUS:85015871799
VL - 2017
JO - BioMed Research International
JF - BioMed Research International
SN - 2314-6133
M1 - 6820482
ER -