Abstract
Purpose
Interest in brain computer interfaces (BCI) has recently increased due to the need for quality of life technologies for disabled people. While brain signal processing and its applications have been widely studied for many decades, BCI seldom requires attention to practical and efficient brain signal sensing methods. Noninvasive electroencephalogram (EEG) measurements using wet adhesive Ag/AgCl electrodes are universally employed for BCI, but have limitations in practical acceptability with regard to portability, comfort and aesthetic design. In order to translate the results of laboratory experiments into practical use, EEGs should be recorded easily without requiring scalp preparation and regardless of the presence of hair.
Methods
In this paper, general requirements for capacitive measurement of EEG are presented and four different frontends for capacitive EEG electrodes are evaluated: (a) basic voltage follower scheme with high value resistor bias network (Rb), (b) voltage follower scheme with active guarding (second op-amp), (c) reverse current of signal diodes to providing bias current, (d) electrode scheme without any external bias network. We explore the use of capacitively-coupled electrodes for BCI technologies through the use of current popular BCI paradigms such as steady state visual evoked potential, P300 and sensory motor rhythm.
Results
Our experimental results indicate that capacitive electrode technology allows the acquisition of spontaneous EEG signals through hair with average correlation coefficient of 0.7949, 0.7946, 0.6333, 0.6549 for each capacitive electrode at O2 and 0.8433, 0.7822, 0.6253, 0.5427 for each capacitive electrode at C4. Although signal quality is lower and the movement artifacts are larger than those of conventional electrodes, SSVEP was successfully recorded through hair without spectral difference between SSVEP peaks and stimulus peaks except low stimulus frequency (5.45 Hz). P300 responses was measured with significant coefficient of determination (>0.005) except electrode (d). Sensory motor rhythm was suppressed during right hand imagery movement with log ratio value less than zero for all electrodes.
Conclusions
Further studies are required to apply capacitive measurement technology to uses in diagnostic EEG, but the method can currently be used for simple BCI applications.
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References
Ishikawa N, Kobayashi Y, Kobayashi M. A case of frontal lobe epilepsy in which amplitude-integrated EEG combined with conventional EEG was useful for evaluating clusters of seizures. Epilepsy Behav. 2010; 8:485–487.
Kaplan PW, Rossetti AO. EEG patterns and imaging correlations in encephalopathy: encephalopathy part II. J Clin Neurophysiol. 2011; 28:233–251.
Wijdicks EFM, Varelas PN, Gronseth GS, Greer DM. Evidencebased guideline update: determining brain death in adults. Neurology. 2010; 74:1911–1918.
Teplan M. Fundamentals of EEG measurement. Meas Sci Rev. 2002; 2:1–11.
Lim YG, Hong KH, Kim KK, Shin JH, Lee SM, Chung GS, Baek HJ, Jeong D-U, Park KS. Monitoring physiological signals using nonintrusive sensors installed in daily life equipment. Biomed Eng Lett. 2011; 1:11–20.
Fernandes MS, Lee KS, Ram RJ, Correia JH, Mendes PM. Flexible PDMS-based dry electrodes for electro-optic acquisition of ECG signals in wearable devices. IEEE Eng Med Biol Soc. 2010; 3503–6.
Yoo J, Yan L, Lee S, Kim H, Yoo H-J. A wearable ECG acquisition system with compact planar-fashionable circuit board-based shirt. IEEE T Inf Technol Biomed. 2009; 13:897–902.
Chiou J-C, Ko L-W, Lin C-T, Hong C-T, Jung T-P, Liang S-F, Jeng J-L. Using novel MEMS EEG sensors in detecting drowsiness application. IEEE Biomed Circ Syst Conf, BioCAS. 2006; 33–36.
Lin C-T, Lin F-C, Chen S-A, Lu S-W, Chen T-C, Ko L-W. EEGbased brain-computer interface for smart living environmental autoadjustment. J Med Biol Eng. 2010; 30:237–245.
Ruffini G, Dunne S, Fuentemilla L, Grau C, Farré E, Marco-Pallarés J, Watts PCP, Silva SRP. First human trials of a dry electrophysiology sensor using a carbon nanotube array interface. Sens Actuator A Phys. 2008; 144:275–279.
Lin C-T, Liao L-D, Liu Y-H, Wang I-J, Lin B-S, Chang J-Y. Novel dry polymer foam electrodes for long-term EEG measurement. IEEE T Biomed Eng. 2011; 58:1200–1207.
Grozea C, Voinescu CD, Fazli S. Bristle-sensors-low-cost flexible passive dry EEG electrodes for neurofeedback and BCI applications. J Neural Eng. 2011; 8:1–8.
Fiedler P, Bordkorb S, Fonseca C, Vaz F, Zanow F, Haueisen J. Novel TiN-based dry eeg electrodes; influence of electrode shape and number on contact impedance and signal quality. Int Fed Med Biol Eng. 2010; 29:418–421.
Chi YM, Jung T-P, Cauwenberghs G. Dry-contact and noncontact biopotential electrodes: methodological review. IEEE Rev Biomed Eng. 2010; 3:106–119.
Chi YM, Cauwenberghs G. Micropower non-contact EEG electrode with active common-mode noise suppression and input capacitance cancellation. Conf Proc IEEE Eng Med Biol Soc. 2009; 4218–4221.
Chi YM, Cauwenberghs G. Wireless non-contact EEG/ECG electrodes for body sensor networks. Int Conf IEEE Body Sens Netw. 2010; 297–301.
Lim YG, Kim KK, Park KS. ECG measurement on a chair without conductive contact. IEEE T Biomed Eng. 2006; 53:956–959.
Lim YG, Kim KK, Park KS. ECG recording on a bed during sleep without direct skin-contact. IEEE T Biomed Eng. 2007; 54:718–725.
Lee SM, Sim KS, Kim KK, Lim YG, Park KS. Thin and flexible active electrodes with shield for capacitive electrocardiogram measurement. Med Biol Eng Comput. 2010; 48:447–457.
Schalk G, McFarland DJ, Hinterberger T, Birbaumer N, Wolpaw JR. BCI2000: a general-purpose brain-computer interface (BCI) system. IEEE T Biomed Eng. 2004; 51:1034–1043.
Oberman LM, Hubbard EM, McCleery JP, Altschuler EL, Ramachandran VS, Pineda JA. EEG evidence for mirror neuron dysfunction in autism spectrum disorder. Cogn Brain Res. 2005; 24:190–198.
Ahi ST, Kambara H, Koike Y. A dictionary-driven P300 speller with a modified interface. IEEE T Neural Syst Rehabil Eng. 2011; 19:6–14.
Jia C, Gao X, Hong B, Gao S. Frequency and phase mixed coding in SSVEP-based brain-computer interface. IEEE T Biomed Eng. 2011; 58:200–206.
Cecotti H. A self-paced and calibration-less SSVEP-based brain-computer interface speller. IEEE T Neural Syst Rehabil Eng. 2010; 18:127–133.
Grychtol B, Lakany H, Valsan G, Conway BA. Human behavior integration improves classification rates in real-time BCI. IEEE T Neural Syst Rehabil Eng. 2010; 18:362–368.
Guger C, Krausz G, Edlinger G. Brain-computer interface control with dry EEG electrodes. Int Brain Comput Interf. 2011; 316–319.
Saab J, Battes B, Grosses-Wentrup M. Simultaneous EEG recording with dry and wet electrodes in motor-imagery. Int Brain Comput Interf. 2011; 312–315.
Luo A, Sullivan TJ. A user-friendly SSVEP-based braincomputer interface using a time-domain classifier. J Neural Eng. 2010; 7:1–10.
Grozea C, Nolte G, Popescu F. Performance of novel dry electrode EEG cap for evoked potential and band-power activity detection. Int Fed Med Biol Eng. 2009; 25:510–513.
Sellers EW, Turner P, Sarnacki WA, McManus T, Vaughan TM, Matthew R. A novel dry electrode for brain-computer interface. Int Conf Human-Computer Interaction: Part II. 2009; 623–631.
Oehler M, Neumann P, Becker M, Curio G, Schilling M. Extraction of SSVEP signals of capacitive EEG helmet for human machine interface. Conf Proc IEEE Eng Med Biol Soc. 2008; 4495–4498.
Chi YM, Wang Y-T, Wang Y, Maier C, Jung T-P, Cauwenberghs G. Dry and non-contact EEG sensors for mobile brain-computer interfaces. IEEE T Neural Syst Rehabil Eng. 2012; 20:228–235.
Popescu F, Fazli S, Badower Y, Blankertz B, Müller K-R. Single trial classification of motor imagination using 6 dry EEG electrode. PLoS ONE. 2007; 2:e637.
Matthews R, McDonald NJ, Anumula H, Trejo LJ. Novel hybrid sensors for unobtrusive recording of human biopotentials. Found Augmen Cognit. 2006; 91–101.
Baek HJ, Lee HJ, Lim YG, Park KS. Conductive polymer foam surface improves the performance of a capacitive EEG electrode. IEEE T Biomed Eng. 2012; 59:3422–3431.
Baek HJ, Kim HS, Heo J, Lim YG, Park KS. Brain-computer interfaces using capacitive measurement of visual or auditory steady-state responses. J Neural Eng. 2013; 10:1–9.
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Baek, H.J., Lee, H.J., Lim, Y.G. et al. Comparison of pre-amplifier topologies for use in brain-computer interface with capacitively-coupled EEG electrodes. Biomed. Eng. Lett. 3, 158–169 (2013). https://doi.org/10.1007/s13534-013-0099-6
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DOI: https://doi.org/10.1007/s13534-013-0099-6