A Biofeedback Smart Cane to Reduce Knee Loading Associated with Osteoarthritis

生物反馈智能手杖可减少与骨关节炎相关的膝盖负荷

基本信息

  • 批准号:
    9032838
  • 负责人:
  • 金额:
    --
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2016
  • 资助国家:
    美国
  • 起止时间:
    2016-01-01 至 2017-12-31
  • 项目状态:
    已结题

项目摘要

 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.
 描述(由申请人提供): 项目摘要/摘要 膝骨关节炎 (OA) 是导致成人残疾的五大主要原因之一,约 25% 的膝骨关节炎患者行走时疼痛,并且难以进行主要的日常生活活动 (ADL),例如行走 1/4。膝关节内侧胫股关节处发生的机械负荷与膝关节骨关节炎的发生和进展密切相关,膝关节内收力矩是与膝关节负荷相关的一种测量指标。 OA 患者的一种保守治疗方法是使用拐杖在受影响的膝关节的对侧使用,可以显着减少膝关节内侧疼痛。如果达到适当的手杖负载,则关节承受的负载意味着手杖支撑了人体重量的很大一部分,例如,最近的研究表明,施加在手杖上的负载越大。例如,KAM 峰值增加 20% 会导致膝骨关节炎的风险增加 6 倍。虽然步行手杖如果正确使用是有效的,但有证据表明,很少有患者接受过如何使用手杖的指导,67% 的老年社区手杖使用者会自行使用手杖,82% 的人没有接受过任何教育或演示。从因此,我们建议开发一种使用直观、可增加手杖负荷、并且比传统手杖更有效地减少膝盖负荷的步行手杖,这对膝关节骨关节炎患者群体是有益的。开发和验证智能手杖,通过引导用户通过手杖保持更大的纵向力来促进正确的手杖加载。智能手杖使用实时振动触觉生物反馈来通知用户何时实现了正确的手杖加载。已经开发出智能手杖的功能,当将特定手杖负载(以体重百分比表示)应用于手杖时,它会通过手柄振动向用户发出信号。在本研究中,我们建议根据手杖来评估智能手杖。与传统手杖相比,它能够增加手杖负载并减少膝盖负载,具体来说,我们的目标是证明:1)使用智能手杖行走时的手杖负载比使用传统手杖行走时更大,2)步行时 KAM 会减少与使用传统手杖行走相比,我们假设 H1) 使用智能手杖时的平均峰值手杖负载大于使用传统手杖时的平均峰值手杖负载,H2) 使用智能手杖时的平均峰值 KAM 为小于使用传统手杖时的平均峰值 KAM,并且在比较智能手杖练习之前和之后一周的常规手杖使用时,平均峰值手杖负载将更大 (H3.1),并且 KAM 将减少 (H3.2)。相信简单的生物反馈技术可用于提高步行手杖的功效,实时向用户传递手杖力量可以使膝关节骨关节炎患者更准确、一致地将步行手杖的负载保持在适当的水平。使用拐杖有可能持续减少膝关节负荷,从而减轻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,将有利于膝关节骨关节炎患者并改善其功能。的质量生活。

项目成果

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Patrick Mark Aubin其他文献

Patrick Mark Aubin的其他文献

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{{ truncateString('Patrick Mark Aubin', 18)}}的其他基金

Robotic Knee Exoskeleton to Reduce Joint Loading and Improve Mobility in Veterans with Medial Compartment Knee Osteoarthritis
机器人膝关节外骨骼可减轻膝关节内侧骨关节炎退伍军人的关节负荷并提高其活动能力
  • 批准号:
    10016814
  • 财政年份:
    2020
  • 资助金额:
    --
  • 项目类别:
Design and Evaluation of a Biarticular Prosthesis to Reduce Gait Compensations
减少步态补偿的双关节假体的设计和评估
  • 批准号:
    10023198
  • 财政年份:
    2016
  • 资助金额:
    --
  • 项目类别:
A Biofeedback Smart Cane to Reduce Knee Loading Associated with Osteoarthritis
生物反馈智能手杖可减少与骨关节炎相关的膝盖负荷
  • 批准号:
    9212015
  • 财政年份:
    2016
  • 资助金额:
    --
  • 项目类别:
Design and Evaluation of a Biarticular Prosthesis to Reduce Gait Compensations
减少步态补偿的双关节假体的设计和评估
  • 批准号:
    9567852
  • 财政年份:
    2016
  • 资助金额:
    --
  • 项目类别:
Design and Evaluation of a Biarticular Prosthesis to Reduce Gait Compensations
减少步态补偿的双关节假体的设计和评估
  • 批准号:
    9812191
  • 财政年份:
    2016
  • 资助金额:
    --
  • 项目类别:

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