王仲朋,陈龙,何峰,万柏坤,明东.面向康复与辅助应用的脑 机接口趋势与展望[J].仪器仪表学报,2017,(6):1307-1318
面向康复与辅助应用的脑 机接口趋势与展望
Development trend and prospect of BCI technology facing rehabilitation and assisting applications
  
DOI:
中文关键词:  脑机接口  临床康复  辅助控制  模型优化
英文关键词:brain computer interface  clinical rehabilitation  assistive control  model optimization
基金项目:国家自然科学基金(81630051, 91520205, 61603269, 81601565, 31500865)、天津市科技支撑计划 (15ZCZDSY00930)项目资助
作者单位
王仲朋 天津大学精密仪器与光电子工程学院天津300072 
陈龙 天津大学精密仪器与光电子工程学院天津300072 
何峰 天津大学精密仪器与光电子工程学院天津300072 
万柏坤 天津大学精密仪器与光电子工程学院天津300072 
明东 天津大学精密仪器与光电子工程学院天津300072 
AuthorInstitution
Wang Zhongpeng College of Precision Instruments & Optoelectronics Engineering, Tianjin University, Tianjin 300072,China 
Chen Long College of Precision Instruments & Optoelectronics Engineering, Tianjin University, Tianjin 300072,China 
He Feng College of Precision Instruments & Optoelectronics Engineering, Tianjin University, Tianjin 300072,China 
Wan Baikun College of Precision Instruments & Optoelectronics Engineering, Tianjin University, Tianjin 300072,China 
Ming Dong College of Precision Instruments & Optoelectronics Engineering, Tianjin University, Tianjin 300072,China 
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中文摘要:
      无需肢体神经肌肉接触便可实现人与外界机器设备信息交互、使“思想”变成“行动”的脑 机接口 (BCI)是脑神经科学与工程技术结合的新产物,亦是临床神经功能康复与运动辅助控制的新技术,可望为部分或完全丧失语言交流与肢体运动控制能力患者(如脑卒中、脊髓损伤、脊髓侧索硬化等疾病)提供全新的增强治疗与康复手段,但目前实际应用尚存在信息处理效率欠高、康复训练时间过长、控制模型通用性差等技术瓶颈。综述了上述技术难点并以运动想象(MI)BCI和BCI拼写器(Speller)为典型介绍了其可能的模型优化策略和解决方案,最后展望了未来BCI发展方向。
英文摘要:
      Brain computer interface can realize the information interaction between human and outer devices and change “thinking” in the mind into real actions without the contact of the limb or neuromuscular system. Brain computer interface is a novel product combining brain neuroscience and engineering technology, and also a new technique for clinical neural function rehabilitation and assistive motor control. It hopefully provides a brand new enhancing treatment and rehabilitation means for the patients losing the ability of language communication and body movement control partly or completely (such as stroke, spinal cord injury (SCI), amyotrophic lateral sclerosis (ALS) and etc.). However, current practical applications are still facing the technical bottlenecks of low information processing efficiency, long rehabilitation training time and poor control model generality. In this paper, these technical difficulties are reviewed. Then, taking the motor imagery BCI and BCI speller as examples, the possible model optimization strategies and solution schemes are introduced. The future development direction of BCI is discussed in the end of the paper.
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