PDF(Pubmed)
Abstract：
The human body constantly experiences mechanical loading. However, quantifying internal loads within the musculoskeletal system remains challenging, especially during unconstrained dynamic activities. Conventional measures are constrained to laboratory settings, and existing wearable approaches lack muscle specificity or validation during dynamic movement. Here, we present a strategy for estimating corresponding joint torque from muscles with different architectures during various dynamic activities using wearable A-mode ultrasound. We first introduce a method to track changes in muscle thickness using single-element ultrasonic transducers. We then estimate elbow and knee torque with errors less than 7.6% and coefficients of determination (R2) greater than 0.92 during controlled isokinetic contractions. Finally, we demonstrate wearable joint torque estimation during dynamic real-world tasks, including weightlifting, cycling, and both treadmill and outdoor locomotion. The capability to assess joint torque during unconstrained real-world activities can provide new insights into muscle function and movement biomechanics, with potential applications in injury prevention and rehabilitation.
摘要：
人体不断经历机械负荷。然而,量化肌肉骨骼系统内的内部负荷仍然具有挑战性，特别是在不受约束的动态活动中。常规措施仅限于实验室环境，而现有的可穿戴方法在动态运动过程中缺乏肌肉特异性或验证。这里,我们提出了一种策略，用于使用可穿戴式A模式超声在各种动态活动中从具有不同结构的肌肉估算相应的关节扭矩。我们首先介绍一种使用单元素超声换能器跟踪肌肉厚度变化的方法。然后，在受控的等速收缩过程中，我们估计肘部和膝盖扭矩的误差小于7.6％，确定系数（R2）大于0.92。最后,我们演示了动态现实任务中的可穿戴关节扭矩估计，包括举重,骑自行车,以及跑步机和户外运动。在不受约束的现实世界活动中评估关节扭矩的能力可以提供对肌肉功能和运动生物力学的新见解，在伤害预防和康复中具有潜在的应用。
