Advanced Methods of Human Machine Interface for Improved Myoelectric Control

改进肌电控制的人机界面先进方法

• 批准号: RGPIN-2021-02638
• 负责人: Kuruganti, Usha
• 金额: $ 2.04万
• 依托单位: University of New Brunswick
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=757900
• 关键词: Advanced; Methods; Human; Machine; Interface

While prosthesis design has evolved greatly over the last several decades, current artificial limbs do not fully replace the intricate, multifunctional human limb. Advancements in materials and technology have led to improved human¬ machine interfaces, but operations can be slow and are often not intuitive, leading to user dissatisfaction and abandonment of the device. Traditionally, surface electromyography (EMG) is used as the control input for powered upper limb prostheses. The advent of multichannel signal recordings or high density EMG (HDEMG) is a promising technique that collects signals from many closely spaced electrodes, resulting in accurate and detailed muscle activation data. Harnessing the information contained within HDEMG will advance research towards the development of a dexterous upper limb prosthesis with multifunction control. Combining HDEMG data with neural actitivty measure through electroencaephalography (EEG) will further advance knowledge to examine cognitive burden on the device user. The ability to combine these biological signals will advance efforts to develop artificial limbs. The proposed research program will be conducted in the Andrew and Marjorie McCain Human Performance Laboratory (HPL) at the University of New Brunswick. The HPL is a state¬-of¬-the-¬art research, education and clinical service facility within the Faculty of Kinesiology at UNB. The HPL is well equipped with highly specialized equipment to study human movement and has significant experience in prosthesis design, control and development. This research program aims to develop more intuitive myoelectric control systems that are capable of many degrees of freedom to more closely resemble intact human limbs. Through the use of biological sensors including HDEMG and EEG we will explore muscular and neural components of muscle activation and signal control to develop new methods of myoelectric control. Analysis of the data will require advanced signal processing techniques as well as the development of new algorithms to investigate muscle behavior and neuromuscular function. We will also exploit the tremendous recent increase in availability of wireless sensor technology to develop new and innovative systems of obtaining muscle data (for example e¬textiles). This research has applications in a number of areas of biomedical engineering from prosthesis design to development of exoskeletons. Over the next five years, the proposed research program will support four graduate students and four undergraduate students and provide them with significant training in state¬-of-¬the-¬art myoelectric control systems and prosthesis design.

虽然假肢设计在过去几十年中有了很大的发展，但目前的假肢并不能完全取代复杂的多功能人体肢体。材料和技术的进步已经导致改进的人机界面，但是操作可能是缓慢的并且通常不是直观的，导致用户不满和放弃设备。传统上，表面肌电图（EMG）被用作动力上肢假肢的控制输入。多通道信号记录或高密度EMG（HDEMG）的出现是一种很有前途的技术，它从许多紧密间隔的电极收集信号，从而获得准确和详细的肌肉激活数据。利用HDEMG中包含的信息将推进研究，以开发具有多功能控制的灵巧上肢假肢。通过脑电图（EEG）将HDEMG数据与神经活动测量相结合，将进一步提高对器械用户认知负担的认识。联合收割机将这些生物信号结合在一起的能力将推动假肢的发展。 拟议的研究计划将在新玩法大学的安德鲁和马乔里·麦凯恩人类绩效实验室（HPL）进行。HPL是UNB运动机能学学院内最先进的研究，教育和临床服务设施。HPL配备了高度专业化的设备来研究人体运动，并在假肢设计，控制和开发方面拥有丰富的经验。 该研究计划旨在开发更直观的肌电控制系统，这些系统能够实现多个自由度，以更接近完整的人类肢体。通过使用生物传感器，包括HDEMG和EEG，我们将探索肌肉激活和信号控制的肌肉和神经成分，以开发新的肌电控制方法。数据分析将需要先进的信号处理技术以及新算法的开发来研究肌肉行为和神经肌肉功能。我们还将利用最近无线传感器技术的巨大增长来开发获得肌肉数据的新的和创新的系统（例如纺织品）。这项研究在生物医学工程的许多领域都有应用，从假肢设计到外骨骼的开发。 在接下来的五年里，拟议的研究计划将支持四名研究生和四名本科生，并为他们提供最先进的肌电控制系统和假肢设计方面的重要培训。