Advanced Myoelectric Control for Improved Prosthetic Function

人类的运动是一个复杂的过程，随着运动次数的增加，涉及的过程变得更加复杂。表面肌电信号(SEMG)是一种监测肌肉收缩行为所产生的电活动并进一步了解神经肌肉功能的方法。 我的研究计划的长期目标是使用新技术更好地了解神经肌肉功能和自愿运动，并开发更健壮的动态肌肉模型。我研究的短期目标是使用包括表面肌电信号和动态力测量在内的先进技术来检查影响神经肌肉功能的各种因素。观察神经肌肉功能的一种方法是使用表面电极记录收缩肌肉的肌电信号(MES)。MES测量发送到肌肉的神经命令的结果，并可以提供有关导致缺陷和功能的神经机制的信息。传统上，表面电极记录活动，数据采集系统上可用通道的数量限制了测量的肌肉数量。最近，MES处理方面的进步导致了新技术的出现，这些技术更加健壮。高密度肌电图(HD-EMG)可以采集更多的信号通道，从而获得更多的信息。这些新系统允许开发地形图，然后可以用来进一步研究肌肉激活模式。 从HD-EMG系统获得的数据将使研究人员能够更好地研究肢体间协调(即多个肢体的协调)和运动效率中的神经肌肉功能，并开发更好的人体运动模型。这在从工业人体工程学到生物力学的许多不同领域和职业设置中都有应用。这项技术在更新的无线HD-EMG系统上的进步使研究人员能够在实际环境中不受限制地研究功能。这项研究还将有助于开发更好的假体控制系统和先进的机器人技术(例如外部皮肤骨骼)。新的信号处理技术的发展，包括利用从HDEMG收集的数据的新方法，将有助于推动研究。

Human movement is a complex process and as the number of movements increase, the processes involved become even more complicated. Surface electromyography (sEMG) is one method of monitoring the electrical activity that results from muscle contraction muscle behaviour and gaining further insight into neuromuscular function. The long-term goal of my research program is to use new technologies to better understand neuromuscular function and voluntary movement and to develop more robust dynamic muscle models. The short-term objectives of my research are to examine the variety of factors that affect neuromuscular function using advanced techniques including sEMG and dynamic force measures. One method to observe neuromuscular function is through the use of surface electrodes to record myoelectric signals (MES) from contracting muscles. The MES measures the result of the neural commands sent to the muscle and can provide information regarding the neural mechanisms responsible for deficiencies and function. Traditionally, surface electrodes record activity and the number of available channels on a data acquisition system limits the number of muscles measured. Recently, advances in MES processing have resulted in new techniques, which are more robust. High-density electromyography (HD-EMG) allows the acquisition of significantly greater numbers of signal channels and therefore greater information. These new systems allow for the development of topographical maps, which can then be used to further study muscle activation patterns. The data obtained from HD-EMG systems will allow researchers to better investigate interlimb coordination (i.e. the coordination of more than one limb) and neuromuscular function in movement efficiency and to develop better models of human movement. This has applications in a number of different fields and occupational settings from industrial ergonomics to biomechanics. The advancement of this technology to newer, wireless HD-EMG systems has enabled researchers to investigate function without restriction and in practical settings. This research will also help to develop better prosthesis control systems and advance robotics (e.g. external dermoskeletons). The development of new signal processing techniques, including novel methods of utilizing the data collected from HDEMG will help to advance research.