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）和关节周围产生的扭矩之间的关系，作为无创估计肌肉骨骼负荷的一种方法，特别是关节/肌肉骨骼动力学的动力学。 测量和了解这些动态对于预防工作场所的肌肉骨骼损伤非常重要（例如，与举重工作或重复性工作相关的伤害）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。负荷的一个独特方面是我们为了完成任务而产生的“刚性”。例如，使用电动工具的工人（例如，手钻）将有目的地共同收缩他/她的肌肉以增加刚性并稳定工具--通常不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，不存在鲁棒的方法来估计刚度，同时执行有用的任务。形式上，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。 对于恒定姿势任务（和其他有限的任务），已经测量了机械阻抗，但测量需要在身体上施加力，因此干扰了正在研究的任务。在这项补助金中，我们将建议在校准任务（其中身体受到干扰）中将机械阻抗与EMG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EMG）。该范例与EMG扭矩建模相同。注意，在执行EMG扭矩建模时，通常从EMG波形估计EMG幅度（EMGamp），然后开发EMG扭矩模型。用于估计EMGamp的先进方法，现在可在文献中，已被证明提供更好的EMG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的估计，以研究在职业任务中的肌肉骨骼损伤的机制，以及在其他应用。我们的具体目标是：（a）证明手肘的机械阻抗可以在恒定姿势、缓慢变力的任务中从EMG中估计出来;（B）证明估计EMG的先进方法可以更好地估计EMG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.