Thalmic Labs: EMG Pattern Recognition

Thalmic Labs：肌电图模式识别

• 批准号: 445334-2012
• 负责人: Stashuk, Daniel
• 金额: $ 1.77万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2012
• 资助国家: 加拿大
• 起止时间: 2012-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=510867
• 关键词: Thalmic; Labs; EMG; Pattern; Recognition

The proposed research will focus on the development of signal processing and pattern recognition algorithms capable of processing mulitple channels of surface-detected EMG (sEMG) signals to extract information related to the execution of dynamic hand and arm gestures. The output of the developed algorithms are intended to be used to control various computer software appliactions. The sEMG signals are to be acquired using an existing band of 8 electrodes applied to the forearm and a dedicated data acquisition system. The sEMG signals will be processed to extract features related to various gestures or hand or arm movements. These features will be input to a series of pattern recognition algorithms devloped to determine which gesture is currently being executed. The devloped algorithms will be an integral part of an overall hardware and software device being designed and developed to allow effortless and wireless interaction to computer software applications. The ultimate goal is to create a novel interface device for machines such as computers, mobile devices, or robotics, thereby creating a new method of user input based on natural gestures and movements in free-space.

拟议的研究将集中在信号处理和模式识别算法的发展，能够处理多通道的表面检测EMG（sEMG）信号，以提取有关执行动态手部和手臂手势的信息。 所开发的算法的输出旨在用于控制各种计算机软件应用。 将使用应用于前臂的8个电极的现有带和专用数据采集系统采集sEMG信号。 sEMG信号将被处理以提取与各种手势或手或手臂运动相关的特征。 这些特征将被输入到一系列模式识别算法中，以确定当前正在执行哪个手势。 所开发的算法将成为正在设计和开发的整个硬件和软件设备的组成部分，以允许轻松和无线地与计算机软件应用程序交互。 最终目标是为诸如计算机、移动的设备或机器人之类的机器创建新颖的接口设备，从而创建基于自由空间中的自然手势和运动的用户输入的新方法。