NRI: Small: EEG and EMG Human Model-Based Adaptive Control of a Dexterous Artificial Hand

NRI：小型：基于脑电图和肌电图人体模型的灵巧假手自适应控制

• 批准号: 1536136
• 负责人: Erik Engeberg
• 金额: $ 16.18万
• 依托单位: Florida Atlantic University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-04-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1536136&HistoricalAwards=false
• 关键词: NRI; Small; EEG; EMG; Human

The research goal of this award is to explore different methods for upper limb amputees to control dexterous artificial hands with brain waves. Biomedical signal processing techniques will be developed to enable this with a single, small recording electrode placed noninvasively on the amputees' heads. The recorded brain waves will be wirelessly transmitted to the hand in real time. A top-level controller will be developed to interpret the intent of the amputees while a low-level controller will be used to synchronize the dexterous grasp motions of the artificial hand. Algorithms will also be developed using tactile feedback from the fingertips to automatically prevent grasped objects from being accidentally dropped when they are transported or disturbed. Amputees will participate in a study to compare the newly developed artificial hand control techniques with brain waves to conventional control techniques with muscle signals during common tasks of daily life.If successful, this research will result in a noninvasive and economic method for amputees to control a dexterous artificial hand with brain waves. This could substantially improve the functionality of prosthetic hands for many amputees. The use of minimal hardware will facilitate the clinical adoption of this technique and the autonomous low-level control algorithms will produce a brain machine interface that places a low cognitive burden on the operator. This research can also be readily applied to benefit many disabled people including stroke victims and quadriplegics and can positively impact other areas of robotics such as improvised explosive disarmament, underwater and space exploration, and rescue robotics. Underrepresented engineering students will benefit from being included in this research plan. Additionally, undergraduate and graduate engineering students will benefit from newly developed classes and laboratory exercises resulting from this research.

本奖项的研究目标是探索上肢截肢者用脑电波控制灵巧假手的不同方法。生物医学信号处理技术将被开发出来，通过将一个小的记录电极无创地放置在截肢者的头上来实现这一点。记录下来的脑电波将实时无线传输到手上。将开发一个顶级控制器来解释截肢者的意图，而一个低级控制器将用于同步人工手的灵巧抓取动作。还将开发算法，利用指尖的触觉反馈，自动防止抓取的物体在运输或受到干扰时意外掉落。截肢者将参加一项研究，在日常生活中比较新开发的人工手部控制技术与脑电波和传统的肌肉信号控制技术。如果成功，这项研究将为截肢者提供一种无创和经济的方法，用脑电波控制灵巧的假手。这将极大地改善许多截肢者假手的功能。使用最少的硬件将促进临床采用这种技术，自主的低级控制算法将产生一个脑机接口，给操作员带来较低的认知负担。这项研究也可以很容易地应用于许多残疾人，包括中风患者和四肢瘫痪者，并可以积极影响其他领域的机器人技术，如简易爆炸解除武装，水下和空间探索，以及救援机器人。未被充分代表的工程专业学生将受益于纳入本研究计划。此外，工程专业的本科生和研究生将受益于这项研究新开发的课程和实验练习。