On Design and Implementation of Neural-Machine Interface for Artificial Legs.
On Design and Implementation of Neural-Machine Interface for Artificial Legs.
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DOI：
10.1109/tii.2011.2166770
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发表时间：
2011-09-06
影响因子：
12.3
通讯作者：
Huang H
中科院分区：
文献类型：
--
作者：
Zhang X;Liu Y;Zhang F;Ren J;Sun YL;Yang Q;Huang H
通过使用网络物理系统（CPS），腿部截肢者的生活质量可以得到显著改善，该系统基于代表截肢者预期动作的神经信号来控制假肢。CPS的关键是神经-机器接口（NMI），它通过感知肌电图（EMG）信号来做出控制决策。本文介绍了一种新型NMI的设计和实现，该NMI使用嵌入式计算机系统从物理系统（截肢者）收集神经信号，提供足够的计算能力来解释这些信号，并做出决策以识别用户实时控制假肢的意图。提出了一种由肌电模式分类器和后处理方案组成的新的解密算法来识别用户的下肢运动意图。为了应对环境的不确定性，设计了一种信任管理机制来处理意外的传感器故障和信号干扰。将神经解密算法与信任管理机制相结合，形成了一个高精度、高可靠性的人工腿神经控制软件系统。然后将软件嵌入到新设计的基于嵌入式微控制器和图形处理单元（GPU）的硬件平台中，形成完整的NMI以进行实时测试。在截肢者和健全人身上进行了实时实验，验证了新型NMI的控制精度。我们的大量实验在这两方面都显示出良好的结果，为神经控制人工腿的临床可行性铺平了道路。
The quality of life of leg amputees can be improved dramatically by using a cyber physical system (CPS) that controls artificial legs based on neural signals representing amputees’ intended movements. The key to the CPS is the neural-machine interface (NMI) that senses electromyographic (EMG) signals to make control decisions. This paper presents a design and implementation of a novel NMI using an embedded computer system to collect neural signals from a physical system - a leg amputee, provide adequate computational capability to interpret such signals, and make decisions to identify user’s intent for prostheses control in real time. A new deciphering algorithm, composed of an EMG pattern classifier and a post-processing scheme, was developed to identify the user’s intended lower limb movements. To deal with environmental uncertainty, a trust management mechanism was designed to handle unexpected sensor failures and signal disturbances. Integrating the neural deciphering algorithm with the trust management mechanism resulted in a highly accurate and reliable software system for neural control of artificial legs. The software was then embedded in a newly designed hardware platform based on an embedded microcontroller and a graphic processing unit (GPU) to form a complete NMI for real time testing. Real time experiments on a leg amputee subject and an able-bodied subject have been carried out to test the control accuracy of the new NMI. Our extensive experiments have shown promising results on both subjects, paving the way for clinical feasibility of neural controlled artificial legs.