Power Reduction of an Embedded Pattern Recognition Myoelectric Control System

嵌入式模式识别肌电控制系统的功耗降低

• 批准号: 8520088
• 负责人: Blair Lock
• 金额: $ 15.05万
• 依托单位: COAPT, LLC
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-05-01 至 2014-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8520088
• 关键词: Address; Adopted; Agonist; Algorithms; Amputees; Artificial Arm; Bionics; Businesses; Chicago; Clinical; Clinical Data; Consumption; Data Set; Development; Devices; Disabled Persons; Drops; Ensure; Fostering; Freedom; Future; Goals; Grant; Health; Hibernation; Hour; Individual; Institutes; Joints; Knowledge; Laboratories; Limb Prosthesis; Limb structure; Manufacturer Name; Marketing; Measures; Medicine; Military Personnel; Mission; Monitor; Muscle; Myoelectric prosthesis; Orthopedics; Outcome; Patients; Pattern; Pattern Recognition; Pattern Recognition Systems; Personal Computers; Persons; Phase; Population; Productivity; Prosthesis; Public Health; Quality of life; Radio; Rehabilitation Research; Rehabilitation therapy; Research; Research Project Grants; Resources; Savings; Signal Transduction; Simulate; Sleep; Small Business Innovation Research Grant; Staging; System; Talents; Techniques; Technology; Testing; Time; Training; Upper Extremity; Weight; Wireless Technology; Work; arm; base; clinical application; commercial application; design; disability; improved; improved functioning; limb amputation; operation; prevent; prototype; public health relevance; reinnervation; research clinical testing; success; systems research; telemetering

DESCRIPTION (provided by applicant): Pattern recognition (PR) myoelectric control systems can dramatically improve an amputee patient's control over a powered prostheses, but they have not been made commercially available. Coapt, LLC, is a start-up stage company that is seeking to commercialize PR myoelectric control for the benefit of upper-limb amputees. The controller is based on research completed by the Rehabilitation Institute of Chicago's Center for Bionic Medicine. Numerous challenges, including clinically viable training and recalibration routines, have been overcame within the past decade, yet some still remain. One such challenge is to lower the power requirements of an embedded PR control system to an acceptable level such that the controller does not quickly drain the onboard prosthesis battery. The objective of this application is to lower the power requirements of the PR embedded control system such that it uses less than 10% of the battery's energy over a full day's use. Energy reduction is a critical item in the development of embedded control systems as it is directly related to the weight of the battery which must be attached to the prosthesis and carried by the patient whenever wearing the device. We will demonstrate the technical feasibility of the approach by the following two specific aims: (1) Develop power management algorithms to minimize power consumption of our pattern recognition controller in a manner that is transparent to the user, (2) Implement the power management techniques on the firmware of our pattern recognition controller. It is very important that our power management act in a manner that is transparent to the user. They must allow the overall control system to remain responsive to the user's command, even after long periods during which the system remains dormant. The proposed research is significant because it removes one of the few remaining clinical barriers preventing pattern recognition-based myoelectric control from being adopted. Ultimately, this research will help allow thousands of upper limb amputees to dramatically improve the control their prostheses, allowing for an improved quality of life.

描述（由申请人提供）：模式识别（PR）肌电控制系统可以显著地改善截肢患者对动力假肢的控制，但是它们还没有商业化。Coapt，LLC是一家初创的舞台公司，正在寻求将PR肌电控制商业化，以造福上肢截肢者。该控制器是基于芝加哥康复研究所仿生医学中心完成的研究。在过去的十年中，许多挑战，包括临床可行的训练和重新校准程序，已经被克服，但仍然存在一些挑战。一个这样的挑战是将嵌入式PR控制系统的功率要求降低到可接受的水平，使得控制器不会快速耗尽机载假体电池。该应用的目的是降低PR嵌入式控制系统的功率要求，使其在一整天的使用中使用不到10%的电池能量。能量减少是嵌入式控制系统开发中的一个关键项目，因为它与必须连接到假体上并由患者在佩戴设备时携带的电池的重量直接相关。我们将通过以下两个具体目标来证明该方法的技术可行性：（1）开发电源管理算法，以对用户透明的方式最小化模式识别控制器的功耗，（2）在我们的模式识别控制器的固件上实现电源管理技术。我们的电源管理对用户透明是非常重要的。它们必须允许整个控制系统保持对用户命令的响应，即使在系统保持休眠的长时间之后。拟议的研究是重要的，因为它消除了少数剩余的临床障碍之一，阻止模式识别为基础的肌电控制被采用。最终，这项研究将帮助成千上万的上肢截肢者大大改善对假肢的控制，从而提高生活质量。