Rehab Technologies Lab, Fondazione Istituto Italiano di Tecnologia, Via Morego, 30, 16163, Genova, Italy.
Department of Electronics, Information and Bioengineering (DEIB), Neuroengineering and Medical Robotics Laboratory, Politecnico di Milano, Building 32.2, Via Giuseppe Colombo, 20133, Milan, Italy.
J Neuroeng Rehabil. 2022 May 7;19(1):43. doi: 10.1186/s12984-022-01019-1.
The inability of users to directly and intuitively control their state-of-the-art commercial prosthesis contributes to a low device acceptance rate. Since Electromyography (EMG)-based control has the potential to address those inabilities, research has flourished on investigating its incorporation in microprocessor-controlled lower limb prostheses (MLLPs). However, despite the proposed benefits of doing so, there is no clear explanation regarding the absence of a commercial product, in contrast to their upper limb counterparts.
This manuscript aims to provide a comparative overview of EMG-driven control methods for MLLPs, to identify their prospects and limitations, and to formulate suggestions on future research and development. This is done by systematically reviewing academical studies on EMG MLLPs. In particular, this review is structured by considering four major topics: (1) type of neuro-control, which discusses methods that allow the nervous system to control prosthetic devices through the muscles; (2) type of EMG-driven controllers, which defines the different classes of EMG controllers proposed in the literature; (3) type of neural input and processing, which describes how EMG-driven controllers are implemented; (4) type of performance assessment, which reports the performance of the current state of the art controllers.
The obtained results show that the lack of quantitative and standardized measures hinders the possibility to analytically compare the performances of different EMG-driven controllers. In relation to this issue, the real efficacy of EMG-driven controllers for MLLPs have yet to be validated. Nevertheless, in anticipation of the development of a standardized approach for validating EMG MLLPs, the literature suggests that combining multiple neuro-controller types has the potential to develop a more seamless and reliable EMG-driven control. This solution has the promise to retain the high performance of the currently employed non-EMG-driven controllers for rhythmic activities such as walking, whilst improving the performance of volitional activities such as task switching or non-repetitive movements. Although EMG-driven controllers suffer from many drawbacks, such as high sensitivity to noise, recent progress in invasive neural interfaces for prosthetic control (bionics) will allow to build a more reliable connection between the user and the MLLPs. Therefore, advancements in powered MLLPs with integrated EMG-driven control have the potential to strongly reduce the effects of psychosomatic conditions and musculoskeletal degenerative pathologies that are currently affecting lower limb amputees.
用户无法直接、直观地控制最先进的商业假肢，这导致设备接受率较低。由于基于肌电图（EMG）的控制有解决这些问题的潜力，因此研究人员热衷于将其纳入微处理器控制的下肢假肢（MLLP）中。然而，尽管有这样做的好处，但与上肢假肢相比，目前没有商业产品的明确解释。
本文旨在对 MLLP 的 EMG 驱动控制方法进行比较性概述，以确定其前景和局限性，并就未来的研究和发展提出建议。这是通过系统地回顾关于 EMG MLLP 的学术研究来实现的。特别是，本综述通过考虑四个主要主题来构建：（1）神经控制类型，讨论允许神经系统通过肌肉控制假肢设备的方法；（2）EMG 驱动控制器的类型，定义文献中提出的不同类别的 EMG 控制器；（3）神经输入和处理类型，描述 EMG 驱动控制器的实现方式；（4）性能评估类型，报告当前最先进控制器的性能。
获得的结果表明，缺乏定量和标准化的措施阻碍了分析比较不同 EMG 驱动控制器性能的可能性。关于这个问题，EMG 驱动 MLLP 的实际效果尚未得到验证。然而，预计将开发出一种用于验证 EMG MLLP 的标准化方法，文献表明，结合多种神经控制器类型有可能开发出更无缝、更可靠的 EMG 驱动控制。这种解决方案有望保持当前使用的非 EMG 驱动控制器在行走等节奏活动中的高性能，同时提高任务切换或非重复运动等随意活动的性能。尽管 EMG 驱动控制器存在许多缺点，例如对噪声的高度敏感，但最近在用于假肢控制的侵入性神经接口（仿生学）方面的进展将允许在用户和 MLLP 之间建立更可靠的连接。因此，具有集成 EMG 驱动控制的动力 MLLP 的进步有可能大大减轻目前影响下肢截肢者的身心条件和肌肉骨骼退行性病变的影响。
