Brain Computer Interface: Inference of Spatial Field

脑机接口：空间场推理

• 批准号: 7599005
• 负责人: CLAUDIA J BONIN
• 金额: $ 0.7万
• 依托单位: UNIV OF MARYLAND, COLLEGE PARK
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-05-15 至 2009-09-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7599005
• 关键词: Address; Algorithms; Alien; Brain; Brain region; Bypass; Chorea; Classification; Clinical; Communication Aids for Disabled; Computers; Conscious; Contralateral; Detection; Disabled Persons; Disease; Dissociation; Electromagnetics; Environment; Etiology; Fatigue; Feedback; Fellowship; Hand; Individual; Intention; Ipsilateral; Knowledge; Laboratories; Lead; Life; Light; Limb structure; Magnetoencephalography; Mental Fatigue; Methods; Monitor; Motor; Movement; Names; Neurosciences; Parietal; Patients; Perception; Physiological Processes; Preparation; Process; Prosthesis; Schizophrenia; Self-Help Devices; Signal Transduction; Spinal cord injury; Syndrome; System; Systematic Bias; Technology; Testing; Thinking; Training; Translating; Translational Research; Wheelchairs; Writing; brain computer interface; design; experience; eye center; improved; insight; motor control; motor learning; practical application; response

DESCRIPTION (provided by applicant): Brain-Computer-Interfaces (BCIs) extract and classify electrical signals recorded from the brain to allow users to bypass the motor system and control hardware such as a computer cursor or a prosthetic device by thoughts alone. Practical applications for locked-in patients with ALS or severe spinal cord injury have been demonstrated in laboratory settings; however, current methods rely on the subjects to train their thoughts using feedback and often lead to user mental fatigue and unreliability in non-laboratory, self-paced conditions. The translational research proposed here seeks to address those issues by extracting information from the electrical activity in parietal regions of the brain associated with the intended targets of voluntary reaching movements. An algorithm will be written to translate those electrophysiological signatures of intended spatial field in eye-centered coordinates into spatial features of the computer screen. This inferential method is expected to provide more robust detection of the user's intentions under self-paced, non-laboratory conditions. Contributions include improved assistive technologies for disabled populations as well as new generalizable knowledge in basic neuroscience regarding sensorimotor processing.

描述（由申请人提供）：脑机接口（BCI）提取并分类从大脑记录的电信号，以允许用户绕过运动系统并仅通过思想控制硬件，例如计算机光标或假肢设备。ALS或严重脊髓损伤患者的实际应用已经在实验室环境中得到证实;然而，目前的方法依赖于受试者使用反馈来训练他们的思想，并且经常导致用户精神疲劳和非实验室自定进度条件下的不可靠性。这里提出的转化研究旨在通过从与自愿达到运动的预期目标相关的大脑顶叶区域的电活动中提取信息来解决这些问题。将编写算法以将以眼睛为中心的坐标中的预期空间场的那些电生理特征转换为计算机屏幕的空间特征。这种推理方法有望在自定进度的非实验室条件下提供对用户意图的更鲁棒的检测。其贡献包括改进残疾人的辅助技术以及关于感觉运动处理的基础神经科学的新的可推广知识。