Estimating Joint Impedance from the Surface EMG

描述（由申请人提供）：多年来，研究人员一直在研究表面肌电图（EMG）与关节产生的扭矩之间的关系，特别是作为一种非侵入性估计肌肉骨骼负荷的手段，以及关节/肌肉骨骼动力学的一般动态。测量和了解这些动态对于预防工作场所的肌肉骨骼损伤（例如，与举重工作或重复性任务相关的损伤）以及康复工程、神经肌肉疾病、基本运动控制研究和其他领域非常重要。负载的一个独特方面是我们为了完成任务而产生的“刚性”。例如，使用电动工具（如手钻）的工人会故意收缩他/她的肌肉，以增加刚性和稳定工具，通常不会产生任何外部可测量的扭矩/力。然而，过度僵硬（同时产生沉重的内部肌肉骨骼负荷）可能与肌肉骨骼损伤有关。目前，还没有可靠的方法来评估执行有用任务时的刚性程度。正式地说，机械工程专业更恰当地将“刚度”定义为机械阻抗的静态分量。对于固定姿势的任务（和其他有限的任务），已经测量了机械阻抗，但测量需要向身体施加力，从而干扰正在研究的任务。在这项授权中，我们将提出在校准任务中（身体受到干扰）将机械阻抗与肌电图联系起来，以便在校准后，可以在不干扰任务的情况下估计阻抗（从肌电图）。这种模式与肌电-扭矩建模相同。注意，在进行肌电-扭矩建模时，通常从肌电波形中估计肌电振幅（EMGamp），然后建立EMGamp-扭矩模型。目前已有文献表明，估计EMGamp的先进方法可以提供更好的肌电扭矩估计。我们在这项工作中的长期目标是使用基于肌电图的机械阻抗估计来研究职业任务中肌肉骨骼损伤的机制，以及其他应用。我们的具体目标是(a)证明肘部的机械阻抗可以从恒定姿势、缓慢力变化任务的肌电图中估计出来，以及(b)证明估计肌电阻抗的先进方法可以更好地估计肌电阻抗。

DESCRIPTION (provided by applicant): For a number of years, researchers have been studying the relationship between the surface electromyogram (EMG) and torque produced about a joint, as a means of non-invasively estimating musculoskeletal load in particular, and the dynamics of joint/musculoskeletal dynamics in general. Measurement and understanding of these dynamics is important in the prevention of musculoskeletal injuries in the workplace (e.g., injuries associated with heavy lifting jobs or repetitive tasks) and in rehabilitation engineering, neuromuscular disease, basic motor control research and other areas. A distinct aspect of load is the "rigidity" that we produce in order to achieve a task. For example, a worker using a power tool (e.g., a hand drill) will purposely co-contract his/her muscles to increase rigidity and stabilize the tool--often without producing any externally measurable torques/forces. However, excessive rigidity (concomitantly producing heavy internal musculoskeletal loads) may be associated with musculoskeletal injury. Currently, no robust methods exist for estimating the degree of rigidity while performing useful tasks. Formally, the mechanical engineering profession more properly defines "rigidity" as the static component of mechanical impedance. For constant-posture tasks (and other limited tasks), mechanical impedance has been measured, but the measurement requires imparting forces on the body, and thus disturbs the task under study. In this grant, we will propose relating mechanical impedance to EMG in a calibration task (in which the body is perturbed), so that after calibration, impedance might be estimated (from EMG) without perturbing the task. This paradigm is identical to EMG-torque modeling. Note that in performing EMG-torque modeling, one usually estimates EMG amplitude (EMGamp) from the EMG waveform, and then develops an EMGamp-torque model. Advanced methods for estimating EMGamp, now available in the literature, have been shown to provide better EMG-torque estimates. Our long-term objectives in this work are to use EMG-based estimates of mechanical impedance to study mechanisms of musculoskeletal injury in occupation tasks, as well as in other applications. Our specific aims are to (a) demonstrate that mechanical impedance about the elbow can be estimated from the EMG in a constant-posture, slowly force-varying task, and (b) demonstrate that advanced methods for estimating EMGamp lead to better EMG-impedance estimates.