Full Text:   <1338>

Summary:  <499>

CLC number: TP39; R31

On-line Access: 2014-10-09

Received: 2014-04-26

Revision Accepted: 2014-08-11

Crosschecked: 2014-09-17

Cited: 1

Clicked: 2834

Citations:  Bibtex RefMan EndNote GB/T7714

-   Go to

Article info.
1. Reference List
Open peer comments

Journal of Zhejiang University SCIENCE C 2014 Vol.15 No.10 P.839-847

http://doi.org/10.1631/jzus.C1400152


A bidirectional brain-computer interface for effective epilepsy control


Author(s):  Yu Qi, Fei-qiang Ma, Ting-ting Ge, Yue-ming Wang, Jun-ming Zhu, Jian-min Zhang, Xiao-xiang Zheng, Zhao-hui Wu

Affiliation(s):  Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):   ymingwang@zju.edu.cn

Key Words:  Brain-computer interface, Epilepsy, Seizure detection, Responsive neurostimulation


Yu Qi, Fei-qiang Ma, Ting-ting Ge, Yue-ming Wang, Jun-ming Zhu, Jian-min Zhang, Xiao-xiang Zheng, Zhao-hui Wu. A bidirectional brain-computer interface for effective epilepsy control[J]. Journal of Zhejiang University Science C, 2014, 15(10): 839-847.

@article{title="A bidirectional brain-computer interface for effective epilepsy control",
author="Yu Qi, Fei-qiang Ma, Ting-ting Ge, Yue-ming Wang, Jun-ming Zhu, Jian-min Zhang, Xiao-xiang Zheng, Zhao-hui Wu",
journal="Journal of Zhejiang University Science C",
volume="15",
number="10",
pages="839-847",
year="2014",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.C1400152"
}

%0 Journal Article
%T A bidirectional brain-computer interface for effective epilepsy control
%A Yu Qi
%A Fei-qiang Ma
%A Ting-ting Ge
%A Yue-ming Wang
%A Jun-ming Zhu
%A Jian-min Zhang
%A Xiao-xiang Zheng
%A Zhao-hui Wu
%J Journal of Zhejiang University SCIENCE C
%V 15
%N 10
%P 839-847
%@ 1869-1951
%D 2014
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.C1400152

TY - JOUR
T1 - A bidirectional brain-computer interface for effective epilepsy control
A1 - Yu Qi
A1 - Fei-qiang Ma
A1 - Ting-ting Ge
A1 - Yue-ming Wang
A1 - Jun-ming Zhu
A1 - Jian-min Zhang
A1 - Xiao-xiang Zheng
A1 - Zhao-hui Wu
J0 - Journal of Zhejiang University Science C
VL - 15
IS - 10
SP - 839
EP - 847
%@ 1869-1951
Y1 - 2014
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.C1400152


Abstract: 
brain-computer interfaces (BCIs) can provide direct bidirectional communication between the brain and a machine. Recently, the BCI technique has been used in seizure control. Usually, a closed-loop system based on BCI is set up which delivers a therapic electrical stimulus only in response to seizure onsets. In this way, the side effects of neurostimulation can be greatly reduced. In this paper, a new BCI-based responsive stimulation system is proposed. With an efficient morphology-based seizure detector, seizure events can be identified in the early stages which trigger electrical stimulations to be sent to the cortex of the brain. The proposed system was tested on rats with penicillin-induced epileptic seizures. Online experiments show that 83% of the seizures could be detected successfully with a short average time delay of 3.11 s. With the therapy of the BCI-based seizure control system, most seizures were suppressed within 10 s. Compared with the control group, the average seizure duration was reduced by 30.7%. Therefore, the proposed system can control epileptic seizures effectively and has potential in clinical applications.

基于双向脑机接口的癫痫抑制系统

研究目的:皮层电刺激作为新的治疗手段,能够有效抑制癫痫发作,弥补传统癫痫治疗方法的不足。现有电刺激治疗方法大都采用持续刺激的方式,或遵照既定的刺激方案,刺激量大,副作用强,尚未广泛应用于临床。脑机接口技术有望为电刺激治疗提供有效闭环控制,从而降低电刺激带来的组织损伤和副作用。
创新要点:首先,提出"双阈值"癫痫检测算法,针对癫痫脑电波形态特征,实现在线快速检测;其次,建立闭环脑机接口系统,通过反应性高频皮层刺激,有效抑制癫痫。
试验结果:通过建立双向脑机接口技术,对脑电信号进行实时分析,从而在癫痫发作前期将其准确检测出来,并触发反应性电刺激,有效抑制癫痫。在青霉素癫痫大鼠模型上的对照试验表明,基于癫痫脑电形态学特征的癫痫检测方法,癫痫检测率83%,平均检测延迟3.11秒;实验组相比于对照组,平均癫痫发作时间减少30.7%。
重要结论:通过双向闭环脑机接口系统,能够实现"按需刺激",从而大大降低电刺激量,减小副作用和组织损伤。基于脑机接口的反应性电刺激系统,能够对癫痫进行实时检测和刺激,有效抑制癫痫发作。该系统具有临床应用潜力。
脑机接口;癫痫;癫痫检测;反应性电刺激

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Berenyi, A., Belluscio, M., Mao, D., et al., 2012. Closed-loop control of epilepsy by transcranial electrical stimulation. Science, 337(6095):735-737.

[2]Bikson, M., Lian, J., Hahn, P.J., et al., 2001. Suppression of epileptiform activity by high frequency sinusoidal fields in rat hippocampal slices. J. Physiol., 531(1):181-191.

[3]Carney, P.R., Myers, S., Geyer, J.D., 2011. Seizure prediction: methods. Epilepsy Behav., 22(Suppl 1):S94-S101.

[4]Engel, J.Jr., Wiebe, S., French, J., et al., 2003. Practice parameter: temporal lobe and localized neocortical resections for epilepsy. Epilepsia, 44(6):741-751.

[5]Fisher, R., Salanova, V., Witt, T., et al., 2010. Electrical stimulation of the anterior nucleus of thalamus for treatment of refractory epilepsy. Epilepsia, 51(5):899-908.

[6]Grewal, S., Gotman, J., 2005. An automatic warning system for epileptic seizures recorded on intracerebral EEGs. Clin. Neurophysiol., 116(10):2460-2472.

[7]Hochberg, L.R., Bacher, D., Jarosiewicz, B., et al., 2012. Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature, 485(7398):372-375.

[8]Kinoshita, M., Ikeda, A., Matsuhashi, M., et al., 2005. Electric cortical stimulation suppresses epileptic and background activities in neocortical epilepsy and mesial temporal lobe epilepsy. Clin. Neurophysiol., 116(6):1291-1299.

[9]Kossoff, E.H., Ritzl, E.K., Politsky, J.M., et al., 2004. Effect of an external responsive neurostimulator on seizures and electrographic discharges during subdural electrode monitoring. Epilepsia, 45(12):1560-1567.

[10]Kwan, P., Brodie, M.J., 2000. Early identification of refractory epilepsy. N. Engl. J. Med., 342(5):314-319.

[11]Majumdar, K.K., Vardhan, P., 2011. Automatic seizure detection in ECoG by differential operator and windowed variance. IEEE Trans. Neur. Syst. Rehabil. Eng., 19(4):356-365.

[12]Mormann, F., Andrzejak, R.G., Elger, C.E., et al., 2007. Seizure prediction: the long and winding road. Brain, 130(2):314-333.

[13]Morrell, M., 2011. Responsive cortical stimulation for the treatment of medically intractable partial epilepsy. Neurology, 77(13):1295-1304.

[14]Motamedi, G.K., Lesser, R.P., Miglioretti, D.L., et al., 2002. Optimizing parameters for terminating cortical afterdischarges with pulse stimulation. Epilepsia, 43(8):836-846.

[15]Osorio, I., Frei, M.G., Sunderam, S., et al., 2005. Automated seizure abatement in humans using electrical stimulation. Ann. Neurol., 57(2):258-268.

[16]Pfurtscheller, G., Flotzinger, D., Kalcher, J., 1993. Brain-computer interface—a new communication device for handicapped persons. J. Microcomput. Appl., 16(3):293-299.

[17]Psatta, D.M., 1983. Control of chronic experimental focal epilepsy by feedback caudatum stimulations. Epilepsia, 24(4):444-454.

[18]Rosin, B., Slovik, M., Mitelman, R., et al., 2011. Closed-loop deep brain stimulation is superior in ameliorating parkinsonism. Neuron, 72(2):370-384.

[19]Sun, F.T., Morrell, M.J., Wharen, R.E.Jr., 2008. Responsive cortical stimulation for the treatment of epilepsy. Neurotherapeutics, 5(1):68-74.

[20]Velasco, A.L., Velasco, F., Velasco, M., et al., 2007. Electrical stimulation of the hippocampal epileptic foci for seizure control: a double-blind, long-term follow-up study. Epilepsia, 48(10):1895-1903.

[21]Velasco, F., Velasco, M., Jimenez, F., et al., 2001. Stimulation of the central median thalamic nucleus for epilepsy. Stereotact. Funct. Neurosurg., 77(1-4):228-232.

[22]Velasco, F., Carrillo-Ruiz, J.D., Brito, F., et al., 2005. Double-blind, randomized controlled pilot study of bilateral cerebellar stimulation for treatment of intractable motor seizures. Epilepsia, 46(7):1071-1081.

[23]Velliste, M., Perel, S., Spalding, M.C., et al., 2008. Cortical control of a prosthetic arm for self-feeding. Nature, 453(7198):1098-1101.

[24]Vonck, K., Boon, P., Achten, E., et al., 2002. Long-term amygdalohippocampal stimulation for refractory temporal lobe epilepsy. Ann. Neurol., 52(5):556-565.

[25]Wang, L., Guo, H., Yu, X., et al., 2012. Responsive electrical stimulation suppresses epileptic seizures in rats. PLoS ONE, 7(5):e38141.

[26]Wang, S., Wu, D.C., Ding, M.P., et al., 2008. Low-frequency stimulation of cerebellar fastigial nucleus inhibits amygdaloid kindling acquisition in Sprague-Dawley rats. Neurobiol. Dis., 29(1):52-58.

[27]Wolpaw, J.R., Birbaumer, N., Heetderks, W.J., et al., 2000. Brain-computer interface technology: a review of the first international meeting. IEEE Trans. Rehabil. Eng., 8(2):164-173.

[28]Wolpaw, J.R., Birbaumer, N., McFarland, D.J., et al., 2002. Brain-computer interfaces for communication and control. Clin. Neurophysiol., 113(6):767-791.

[29]Wu, Z., Reddy, R., Pan, G., et al., 2013. The convergence of machine and biological intelligence. IEEE Intell. Syst., 28(5):28-43.

[30]Yadav, R., Swamy, M.N.S., Agarwal, R., 2012. Model-based seizure detection for intracranial EEG recordings. IEEE Trans. Biomed. Eng., 59(5):1419-1428.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - Journal of Zhejiang University-SCIENCE