Use of Wearable Sensors to Assess Prosthetic Alignment in Veterans with Unilateral Transtibial Amputations

经胫骨截肢的退伍军人需要假肢行走，并且继发性风险增加。 受伤、不适和生活质量下降。正确的假体对线可以降低这些风险， 经胫骨截肢患者的功能能力和舒适度。目前，假肢专家（临床医生） 主观地对准假体，这可能需要多次临床访问。主观对齐依赖于 假肢专家的经验和视觉检查的步行，这是容易出错和费时。因此，在本发明中， 迫切需要开发用于假体对准的客观工具。我们的目标是开发一种新的方法 为了使用无线传感器技术准确地、精确地和经济地[评估]假体对准， 这可以提高生活质量，减少数百万假肢使用者的二次伤害风险， 美国的本研究的目的是确定使用可穿戴传感器的准确性和精度 结合算法评估10例经胫骨截肢的退伍军人的假体对线。 [We我将要求10名经胫骨截肢的退伍军人在力量跑步机上以1.25米/秒的速度行走，同时他们使用 一种假体，具有中性对线，在矢状面、冠状面 和横向平面，共13个假体对线。对于每个对齐条件，我们将确定 使用惯性测量单元（伊穆斯）与数值算法相结合的准确度和精度 在10分钟步行过程中估计假体和生物小腿的动静角（DSA）， 单侧经胫骨截肢的退伍军人（目标1），其中DSA提供了关于 假体和生物柄的方向。我们还将确定的准确性和精度， 使用与数值算法相结合的伊穆斯来估计步长、步长 频率和接触时间，这是重要的离散时空参数，在10 单侧经胫骨截肢的退伍军人（目标2）。我们将比较使用伊穆斯估计的结果， 使用3D运动捕捉和地面反应的传统黄金标准测量计算的结果 力.我们还将研究假体对线角度变化与DSA之间的关系 和肢间对称指数（目标3）。我们假设IMU方法将提供准确的（根- 均方误差[RMSE]<6°）和精确（类间相关系数[ICC]>0.75）估计 下肢DSA和肢体间对称指数（平均绝对百分比误差[MAPE]<10%，ICC>0.75） 时空参数。我们还假设假体对线的改变会导致 使用IMU方法和运动捕捉测量的DSA中的显著差异。我们假设 假体对线的改变将导致台阶的肢体间对称指数的显著差异， 长度、步频和接地时间。[If我们的研究结果表明，惯性测量单元方法不能提供 准确和精确的估计DSA或对称指数，我们将考虑使用更复杂的 使用伊穆斯预测DSA的预测模型（例如机器学习）。] 我们的研究成果是开发了一种使用无线IMU传感器的新方法， [评估]假体准确对准（与基于摄像头的运动捕捉系统的精度相当 和测力板地面反作用力系统），快速（一次访问），成本效益（<200美元）。【我们 我还希望这个项目将提供数据，以支持一个更大的赠款建议，进行一项研究， 研究假体排列与舒适度、行走对称性和 二次伤害风险在退伍军人截肢。从长远来看，所提出的IMU方法可以改善 调整过程，从而最大限度地提高退伍军人的功能独立性和生活质量，以及 降低二次伤害风险。

Veterans with transtibial amputation require a prosthesis to walk and are at an increased risk of secondary injury, discomfort, and reduced quality of life. Proper prosthetic alignment can reduce these risks and improve functional ability and comfort in individuals with transtibial amputation. Currently, prosthetists (clinicians) subjectively align a prosthesis, and this may require several clinical visits. Subjective alignment relies on prosthetists’ experience and visual inspection of walking, which is prone to errors and time consuming. Thus, there is an urgent need to develop objective tools for prosthesis alignment. We aim to develop a novel method to [assess] prosthesis alignment accurately, precisely, and cost-efficiently using wireless sensor technology, which could improve quality of life and reduce secondary injury risk for the millions of prosthesis users in the United States. The goal of this study is to determine the accuracy and precision of using wearable sensors combined with an algorithm to assess prosthesis alignment in 10 Veterans with transtibial amputation. [We will ask 10 Veterans with transtibial amputation to walk on a force-treadmill at 1.25 m/s while they use a prosthesis with neutral alignment and that varies by 3° and 6° in one of three planes, the sagittal, coronal, and transverse planes, for a total of 13 prosthesis alignments. For each alignment condition, we will determine the accuracy and precision of using inertial measurement units (IMUs) combined with a numerical algorithm to estimate dynamic-to-static angle (DSA) of the prosthesis and the biological shank during walking in 10 Veterans with unilateral transtibial amputation (Aim 1), where DSA provides information regarding the orientation of the prosthesis and the biological shank. We will also determine the accuracy and precision of using IMUs combined with a numerical algorithm to estimate inter-limb symmetry indices of step length, step frequency, and contact time, which are important discrete temporal-spatial parameters during walking in 10 Veterans with unilateral transtibial amputation (Aim 2). We will compare results estimated using IMUs with results calculated using traditional gold-standard measurements of 3D motion capture and ground reaction forces. We will also investigate the association between angular changes in prosthesis alignment and DSA and interlimb symmetry indices (Aim 3).] We hypothesize that the IMU method will provide accurate (root- mean squared error [RMSE]<6°) and precise (inter-class correlation coefficient [ICC]>0.75) estimations of DSA for both legs and inter-limb symmetry indices (mean absolute percentage error [MAPE]<10%, ICC>0.75) of temporal-spatial parameters. We also hypothesize that changes in prosthesis alignment will result in significant differences in DSA using the IMU method and motion capture measurements. We hypothesize that changes in prosthesis alignment will result in significant differences in interlimb symmetry index of step length, step frequency, and ground contact time. [If our results suggest that the IMU method does not provide accurate and precise estimations of DSA or symmetry indices, we will consider using a more sophisticated prediction model (e.g. machine learning) to predict DSA using IMUs.] The outcome of our research is the development of a novel method that uses wireless IMU sensors to [assess] prosthesis alignment accurately (comparable accuracy with camera-based motion capture system and force plate ground reaction force system), quickly (within a single visit), and cost-efficiently (<$200). [We also expect that this project will provide data to support a larger grant proposal to conduct a study that investigates the relationship between prosthesis alignment and comfort level, walking symmetry, and secondary injury risk in Veterans with amputations.] In the long term, the proposed IMU method could improve the alignment process and thus maximize Veterans’ functional independence and quality of life, as well as reduce secondary injury risk.