A Biofeedback Smart Cane to Reduce Knee Loading Associated with Osteoarthritis

 描述（由申请人提供）： 膝关节骨关节炎（OA）是成人残疾的五大原因之一。大约25%的膝关节OA患者在行走时疼痛，并且难以进行主要的日常生活活动（ADL），例如行走1/4英里，爬楼梯或跪着。发生在内侧胫股膝关节的机械负荷与膝关节OA的发生和进展密切相关。膝关节内收力矩是膝关节负荷的一种测量方法，与内侧间室OA的存在、放射学疾病严重程度、进展速度和OA症状的存在相关。OA患者的一种保守治疗方法是使用拐杖。研究表明，如果达到适当的手杖载荷，则对患膝使用手杖可以显著降低关节承受的内侧载荷。适当的手杖负载意味着手杖支撑一个人体重的大部分，例如体重的15%。最近的研究表明，手杖上的负荷越大，膝关节内侧负荷的减少越大。减少内侧膝关节负荷的重要性是显著的。例如，KAM峰值增加20%会导致6年内膝关节骨关节炎风险增加6倍。如果正确使用，手杖可以有效，但有证据表明，很少有患者接受如何使用手杖的指导。67%的老年生活社区手杖使用者自己开手杖处方，82%的人没有接受医疗专业人员的教育或示范。因此，我们建议开发一种使用直观、鼓励更大手杖负荷、并且在减少膝关节负荷方面比传统手杖更有效的步行手杖，这将有利于膝关节OA患者人群。我们的目标是开发和验证一种智能手杖，通过引导用户保持更大的纵向力通过手杖，可以促进适当的手杖加载。智能手杖使用实时振动触觉生物反馈来通知用户何时达到适当的手杖负荷。智能手杖的第一个原型已经开发出来，当特定的手杖负载（以体重百分比表示）施加到手杖上时，它通过手柄振动向用户发出信号。在这项研究中，我们建议评估智能手杖的能力，以增加手杖负荷和减少膝盖负荷相比，传统的步行手杖。具体而言，我们旨在证明，1）与使用传统手杖行走相比，使用智能手杖行走时手杖负载更大，2）与使用传统手杖行走相比，使用智能手杖行走时KAM减少。我们假设H1）使用智能手杖时的平均峰值手杖载荷大于使用传统手杖时的平均峰值手杖载荷，H2）使用智能手杖时的平均峰值KAM小于使用传统手杖时的平均峰值KAM，这意味着峰值甘蔗负荷将更大当比较智能手杖练习之前和之后一周的常规手杖使用时，KAM（H3.1）和KAM（H3.2）将减少。我们相信，简单的生物反馈技术可以用来提高手杖的功效。将手杖力实时地传递给用户可以允许膝关节OA患者更准确地和一致地将他们的步行手杖加载到适当的水平。这种持续的长期正确手杖使用有可能导致膝关节负荷的持续减少，从而减少膝关节疼痛并改善膝关节功能。开发更有效的保守治疗策略，可以减缓关节恶化的进展，这将使膝关节OA患者受益，并改善他们的生活质量。

 DESCRIPTION (provided by applicant): Project Summary/Abstract Knee osteoarthritis (OA) is one of five leading causes of disability among adults. About 25% of people with knee OA have pain on walking and have difficulty doing major activities of daily living (ADLs) such as walking 1/4 mile, climbing stairs, or kneelin. Mechanical loading that occurs at the medial tibiofemoral knee joint is strongly associated with the development and progression of knee OA. The knee adduction moment is one measure of knee loading that is associated with medial compartment OA presence, radiographic disease severity, rate of progression, and the presence of OA symptoms. One conservative treatment method for OA patients is the prescription of a walking cane. Studies have shown cane use contralateral to the affected knee can significantly reduce the medial load experienced by the joint if proper cane loading is achieved. Proper cane loading implies the cane supports a substantial portion of one's body weight, e.g. 15% body weight. Recent work has shown that the greater the load placed on the cane the greater the resulting reduction in medial knee load. The importance of reducing the medial knee load is significant. For example, a 20% increase in peak KAM was shown to lead to a 6-fold increase in the risk of knee osteoarthritis over a six-year period. While walking canes can be effective if used correctly there is evidence that very few patients receive instruction on how to use a cane. Sixty seven percent of senior living community cane users self- prescribe their canes and 82% receive no education or demonstration from medical professionals. Therefore we propose that the development of a walking cane that is intuitive to use, encourages greater cane loading, and shown to be more effective at reduce knee loading than a conventional cane would be beneficial for the knee OA patient population. We aim to develop and validate a smart cane that can facilitate proper cane loading by guiding the user to maintain greater longitudinal forces through the cane. The smart cane uses real-time vibrotactile biofeedback to inform the user when proper cane load has been achieved. A first prototype of the smart cane has already been developed which signals the user via handle vibration when a specific cane load, expressed in terms of percent body weight has been applied to the cane. For this study, we propose to evaluate the smart cane in terms of the its ability to increase cane loading and decrease knee loading as compared to a conventional walking cane. Specifically, we aim to demonstrate that, 1) cane loading is greater when walking with a smart cane as compared to walking with a conventional cane and 2) the KAM is reduced when walking with a smart cane as compared to walking with a conventional cane. We hypothesis that H1) mean peak cane load when using a smart cane is greater than mean peak cane load when using a conventional cane, H2) mean peak KAM when using a smart cane is less than mean peak KAM when using a conventional cane, and that mean peak cane loading will be greater (H3.1) and KAM will be reduced (H3.2) when comparing regular cane use before and one week after smart cane practice. We believe that simple biofeedback technologies can be used to improve the efficacy of walking canes. Relaying cane force to the user in real-time may allow knee OA patients to more accurately and consistently load their walking cane to the appropriate level. This consistent long term proper cane use has the potential to result in persistent reduction of knee loading resulting in a decrease in knee pain and improved knee joint function. Developing more effective conservative treatment strategies that can slow the progression of joint deterioration would benefit those suffering from knee OA and improve their quality of life.