|本期目录/Table of Contents|

[1]高诺△,杨玉娜,翟文文,等.基于脑机接口的脑卒中患者语音看护系统*[J].生物医学工程研究,2018,04:465-469.
 GAO Nuo,YANG Yuna,ZHAI Wenwen,et al.A speech care system for stroke patients based on brain-computer interface[J].Journal of Biomedical Engineering Research,2018,04:465-469.
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基于脑机接口的脑卒中患者语音看护系统*(PDF)

《生物医学工程研究》[ISSN:1006-6977/CN:61-1281/TN]

期数:
2018年04期
页码:
465-469
栏目:
出版日期:
2018-12-25

文章信息/Info

Title:
A speech care system for stroke patients based on brain-computer interface
文章编号:
1672-6278 (2018)04-0465-05
作者:
高诺△杨玉娜翟文文高枫王蕴辉
山东建筑大学信息与电气工程学院,济南 250101
Author(s):
GAO NuoYANG YunaZHAI WenwenGAO FengWANG Yunhui
Information & Electrical Engineering Department, Shandong Jianzhu University, Jinan 250101, China
关键词:
脑卒中脑机接口Alpha波稳态视觉诱发电位语音合成
Keywords:
Stroke Brain-computer interface Alpha wave Steady-state visual evoked potentialVoice synthesis
分类号:
R318
DOI:
10.19529/j.cnki.1672-6278.2018.04.17
文献标识码:
A
摘要:
脑卒中患者的语言障碍使得他们无法表达自己的意图,给患者的治疗和生活带来了巨大的困难。为了改善患者的语言状况,便于家人和看护人员的看护,本研究利用脑机接口技术设计实现了一种服务于脑卒中患者的语音看护系统。该系统利用Alpha波实现异步的工作方式,患者可以自主地选择何时启动系统运行;利用对稳态视觉诱发电位(steady-state visual evoked potential,SSVEP)信号的分析实现患者语言意图的识别;利用语音合成技术完成患者语言的语音表达输出。该系统的在线实验结果证实了该系统的可行性与有效性,四名被试者可以利用Alpha波控制系统的启动与空闲,系统启动后再利用SSVEP信号控制自身的表达意图,控制准确率高达90%以上。
Abstract:
The language barrier of stroke patients makes them unable to express their language intention, which makes great difficulties to the treatment and life of them. In order to improve the language condition of patients and facilitate the care of family members and nurses, we used brain-computer interface technology to design a speech care system for stroke patients. This system used Alpha wave to realize asynchronous working mode, and patients could choose when to start the system with this working mode. The analysis of SSVEP signals was used to identify the patient′s language intention. The speech output of patient was achieved by speech synthesis. The online experiment results of the system confirmes the feasibility and effectiveness of this system. Four subjects can use the Alpha wave control system to start and idle, and the SSVEP signal is used to control their expression intention after the system is started, with the control accuracy over 90%.

参考文献/References

备注/Memo

备注/Memo:
(收稿日期:2018-09-16) 山东省重点研发计划项目(2017CXGC1505)。△通信作者Email:gaonuo@sdjzu.edu.cn
更新日期/Last Update: 2019-01-30