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胫骨力可以在跑步时通过穿在鞋上的可穿戴传感器进行监测。

Tibial bone forces can be monitored using shoe-worn wearable sensors during running.

机构信息

Department of Mechanical Engineering, Vanderbilt University, Nashville, Tennessee, United States.

Institute for Software Integrated Systems, Vanderbilt University, Nashville, Tennessee, United States.

出版信息

J Sports Sci. 2022 Aug;40(15):1741-1749. doi: 10.1080/02640414.2022.2107816. Epub 2022 Aug 6.

Abstract

Tibial bone stress injury is a common overuse injury experienced by runners, which results from repetitive tissue forces. Wearable sensor systems () that monitor tibial forces could help understand and reduce injury incidence. However, there are currently no validated wearables that monitor tibial bone forces. Previous work using simulated wearables demonstrated accurate tibial force estimates by combining a shoe-worn inertial measurement unit (IMU) and pressure insole with a trained algorithm. This study aimed assessed how accurately tibial bone forces could be estimated with existing wearables. Nine recreational runners ran at a series of different speeds and slopes, and with various stride patterns. Shoe-worn IMU and insole data were input into a trained algorithm to estimate peak tibial force. We found an average error of 5.7% in peak tibial force estimates compared with lab-based estimates calculated using motion capture and a force instrumented treadmill. Insole calibration procedures were essential to achieving accurate tibial force estimates. We concluded that a shoe-worn, multi-sensor system is a promising approach to monitoring tibial bone forces in running. This study adds to the literature demonstrating the potential of wearables to monitor musculoskeletal forces, which could positively impact injury prevention, and scientific understanding.

摘要

胫骨骨应力性损伤是跑步者常见的过度使用损伤,它是由反复的组织力量引起的。可穿戴传感器系统()可以监测胫骨力,有助于了解和减少损伤的发生率。然而,目前还没有经过验证的可穿戴设备可以监测胫骨骨力。以前使用模拟可穿戴设备的研究表明,通过将鞋穿式惯性测量单元(IMU)和压力鞋垫与经过训练的算法相结合,可以准确估计胫骨力。本研究旨在评估现有的可穿戴设备可以多准确地估计胫骨骨力。9 名休闲跑步者以不同的速度和坡度,以及不同的步幅模式进行跑步。将鞋穿式 IMU 和鞋垫数据输入经过训练的算法,以估计峰值胫骨力。我们发现,与使用运动捕捉和力感应跑步机计算得出的实验室估计值相比,峰值胫骨力估计值的平均误差为 5.7%。鞋垫校准程序对于实现准确的胫骨力估计至关重要。我们得出的结论是,一种多传感器的可穿戴系统是监测跑步时胫骨骨力的有前途的方法。本研究增加了文献中关于可穿戴设备监测肌肉骨骼力的潜力的内容,这可能对预防损伤和科学理解产生积极影响。

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