Enhancing AFO Efficacy through Continuous, Non-Invasive Gait Assessment
通过连续、非侵入性步态评估提高 AFO 功效
基本信息
- 批准号:1034071
- 负责人:
- 金额:$ 30万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2010
- 资助国家:美国
- 起止时间:2010-10-01 至 2014-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
PI: Bennett, B. C., Abel, M. F., and Lach, J. C.Proposal Number: 1034071Individuals with mobility disabilities as a result of cerebral palsy (CP) are often prescribed ankle foot orthoses (AFOs) to aid in their walking and prevent muscle contractures. More than 50% of the estimated 764,000 people with another 9500 children diagnosed each year. in the United States who have one or more symptoms of CP are prescribed orthoses21, with significantly larger numbers worldwide. Despite this widespread use of AFOs, current methods for evaluating " and ultimately enhancing" their efficacy in this population are limited. Most studies of gait changes with AFO use are based on single visit data collections in the gait lab, which only reveal short-term improvements in gait mechanics and do not address the AFOs' larger goals of increasing activity and participation in school and society and preventing muscle contractures and bony deformities. Accessing such data would provide insight into the efficacy of current AFOs and guidance for future AFO development, but longer-term, more continuous data collections in the wearers' natural environments are necessary. The proposed project seeks to address these limitations of solely relying on in-clinic data collections by addressing the fundamental scientific and technical challenges to the non-invasive and continuous collection and analysis of gait and activity data in any location over an extended period of time. Accelerometers, gyroscopes, microcontrollers, non-volatile memory, batteries, and supporting circuitry will be molded into AFOs, sensing, pre-processing, and storing movement data that is later downloaded and post-processed to determine both the amount and type of activity (e.g. walking vs. running vs. crawling) and various spatial-temporal gait parameters (e.g. stride length, ankle angle, etc.). This objective, long-term, patient-specific assessment of AFO efficacy will transform the way doctors and gait specialists prescribe and monitor AFO use and will inform the development of future AFO technologies. For the first time clinicians will be able to follow the real world progress of the effect of AFO use. The sensing system is completely non-invasive as it will reside in the AFOs themselves, and the effect on day-to-day performance of different AFOs can be studied. Limitations that affect behavior (e.g. stair climbing) can be documented, and ankle position will be recorded as a function of time so that it can be determined if desired positions are held long enough to prevent contractures and deformities. If AFO use results in decreased walking performance or limits other activities, the clinician can modify the AFO, prescribe a different type of AFO (e.g. hinged vs. solid), or can suggest that the AFOs only be worn part of the time or not at all.Intellectual Merit: This work - which brings together an orthopedics and gait biomechanics specialist, a body sensor networks expert, and an orthopedic surgeon - will make several scientific and technical advancements in the fields of motion analysis and assistive technologies for CP. First, this work advances the area of long-term, non-invasive movement data collection and analysis. Increasingly, clinicians are using evidence-based interventions and are interested in quantitative measures in daily life, outside of the clinic or laboratory. This work goes beyond the mere measurement of general activity or number of steps (as is provided by existing off-the-shelf technologies) in that it will provide activity classification and spatial-temporal gait parameters. Second, the resulting knowledge of how an individual child is moving in the world with his/her AFOs will provide feedback as to the appropriateness of the devices, enabling changes to the AFOs to be made as necessary. Finally, the results of this analysis will provide insights into opportunities for future AFO development.Broader Impact: The impact of this work spans improved basic understanding of activity to improved quality of life for individuals with walking disabilities. While this work focuses on aiding those with CP, the basic science of this work can be applied to AFOs for individuals with different disabilities as well as the ability to non-invasively and continuously measure the movement of other body segments/joints. In addition, this work will develop technology that will provide information that will be needed in the future when active devices come into practice. Finally, with improved batteries and electronics it will become feasible to build sensors into every AFO so that gait/activities could be monitored intermittently to assess performance changes over time without a lab visit.
PI:班尼特,B。C.对所述化合物进行纯化,Abel,M. F.、和Lach,J.C.建议编号:1034071由于脑性麻痹(CP)而具有行动障碍的个体通常被规定踝足矫形器(AFO)以帮助他们行走并防止肌肉挛缩。超过50%的估计764,000人与另外9500名儿童每年确诊。在美国,有一种或多种CP症状的人被规定使用矫形器21,在世界范围内数量要大得多。尽管AFO被广泛使用,但目前用于评估“并最终增强”其在该人群中的疗效的方法是有限的。大多数关于使用AFO的步态变化的研究都是基于步态实验室的单次访问数据收集,这些数据只显示了步态力学的短期改善,并没有解决AFO增加活动和参与学校和社会以及预防肌肉挛缩和骨骼畸形的更大目标。这些数据将为当前AFO的功效提供洞察力,并为未来AFO的发展提供指导,但需要在佩戴者的自然环境中进行更长期,更连续的数据收集。拟议的项目旨在解决这些局限性,仅仅依靠在诊所数据收集,解决基本的科学和技术挑战的非侵入性和连续收集和分析的步态和活动数据在任何位置在一段较长的时间。加速度计、陀螺仪、微控制器、非易失性存储器、电池和支持电路将被模制到AFO中,用于感测、预处理和存储运动数据,这些运动数据随后被下载和后处理,以确定活动的量和类型(例如,步行、跑步、爬行)以及各种时空步态参数(例如,步长、脚踝角度等)。 这种客观、长期、针对患者的AFO疗效评估将改变医生和步态专家处方和监测AFO使用的方式,并将为未来AFO技术的发展提供信息。临床医生将第一次能够跟踪AFO使用效果的真实的世界进展。传感系统是完全非侵入性的,因为它将驻留在AFO本身,并且可以研究对不同AFO的日常性能的影响。可以记录影响行为的限制(例如爬楼梯),并将踝关节位置记录为时间的函数,以便可以确定所需位置是否保持足够长的时间以防止挛缩和畸形。如果使用AFO导致行走能力下降或限制其他活动,临床医生可以修改AFO,(例如铰链式与实心式),或可暗示AFO只在部分时间佩戴或根本不佩戴。知识专长:这项工作汇集了骨科和步态生物力学专家,身体传感器网络专家,和整形外科医生-将在运动分析和CP辅助技术领域取得一些科学和技术进步。首先,这项工作推进了长期、非侵入性运动数据收集和分析领域。临床医生越来越多地使用循证干预措施,并对临床或实验室以外的日常生活中的定量测量感兴趣。这项工作超越了一般活动或步数的单纯测量(如现有的现成技术所提供的),因为它将提供活动分类和时空步态参数。第二,所得到的关于个体儿童如何带着他/她的AFO在世界上移动的知识将提供关于设备的适当性的反馈,使得能够根据需要对AFO进行改变。最后,这项分析的结果将提供洞察未来AFO的发展机会。更广泛的影响:这项工作的影响跨越了改善活动的基本理解,以提高个人的生活质量与行走残疾。虽然这项工作的重点是帮助CP患者,但这项工作的基础科学可以应用于具有不同残疾的个人的AFO,以及非侵入性和连续测量其他身体部位/关节运动的能力。此外,这项工作将开发技术,将提供信息,将需要在未来时,主动装置付诸实践。最后,随着电池和电子设备的改进,在每个AFO中安装传感器将变得可行,这样就可以间歇性地监测步态/活动,以评估性能随时间的变化,而无需进行实验室访问。
项目成果
期刊论文数量(0)
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会议论文数量(0)
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John Lach其他文献
Making Meaning of “Messy” Data: Creating Clinically Useful Visualizations to Represent the Experience of Cancer Pain in the Home Setting (GP732)
- DOI:
10.1016/j.jpainsymman.2022.04.123 - 发表时间:
2022-06-01 - 期刊:
- 影响因子:
- 作者:
Virginia LeBaron;Nutta Homdee;Nyota Patel;Rachel Bennett;Nadim El-Jaroudi;Yudel Martinez Salgado;Emmanuel Ogunjirin;John Lach - 通讯作者:
John Lach
Alloyed Branch History: Combining Global and Local Branch History for Robust Performance
- DOI:
10.1023/a:1022669325321 - 发表时间:
2003-04-01 - 期刊:
- 影响因子:0.900
- 作者:
Zhijian Lu;John Lach;Mircea R. Stan;Kevin Skadron - 通讯作者:
Kevin Skadron
Understanding the Experience of Cancer Pain From the Perspective of Patients and Family Caregivers to Inform Design of an In-Home Smart Health System: Multimethod Approach (Preprint)
从患者和家庭护理人员的角度了解癌症疼痛的经历,为家庭智能医疗系统的设计提供信息:多方法方法(预印本)
- DOI:
10.2196/preprints.20836 - 发表时间:
2020 - 期刊:
- 影响因子:13.6
- 作者:
Virginia T. LeBaron;Rachel Bennett;Ridwan Alam;L. Blackhall;Kate Gordon;J. Hayes;Nutta Homdee;Randy Jones;Yudel Martinez;Emmanuel Ogunjirin;Tanya Thomas;John Lach - 通讯作者:
John Lach
Automatic, wearable-based, in-field eating detection approaches for public health research: a scoping review
用于公共卫生研究的基于可穿戴设备的自动现场进食检测方法:范围审查
- DOI:
10.1038/s41746-020-0246-2 - 发表时间:
2020-03-13 - 期刊:
- 影响因子:15.100
- 作者:
Brooke M. Bell;Ridwan Alam;Nabil Alshurafa;Edison Thomaz;Abu S. Mondol;Kayla de la Haye;John A. Stankovic;John Lach;Donna Spruijt-Metz - 通讯作者:
Donna Spruijt-Metz
John Lach的其他文献
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{{ truncateString('John Lach', 18)}}的其他基金
2018 Connections in Smart Health Workshop
2018智慧健康连线工作坊
- 批准号:
1841671 - 财政年份:2018
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
REU Site: Wireless Technologies for Health Applications
REU 网站:健康应用无线技术
- 批准号:
1461162 - 财政年份:2015
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
Safety Analysis of Body Sensor Networks
人体传感器网络的安全分析
- 批准号:
1240454 - 财政年份:2012
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
SHB: Medium: Collaborative Research: Non-Intrusive Multi-Patient Fall-Risk Monitoring in Health Care Facilities
SHB:中:协作研究:医疗保健机构中的非侵入式多患者跌倒风险监测
- 批准号:
1065262 - 财政年份:2011
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
CI-P: Development of Community Infrastructure for Body Sensor Network Research, Education, and Support
CI-P:身体传感器网络研究、教育和支持的社区基础设施开发
- 批准号:
0855197 - 财政年份:2009
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
Collaborative Research: Multi-Scale QoS for Body Sensor Networks
协作研究:身体传感器网络的多尺度 QoS
- 批准号:
0901686 - 财政年份:2009
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
Collaborative Research: Continuous, Non-Invasive Gait Analysis and Fall-Risk Assessment
合作研究:连续、非侵入性步态分析和跌倒风险评估
- 批准号:
0756645 - 财政年份:2008
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
Collaborative Research: CT-T: Manufacturing Variability-based Hardware Protection Techniques
合作研究:CT-T:基于制造变异性的硬件保护技术
- 批准号:
0716443 - 财政年份:2007
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
SEI: Hierarchical Dependency Graphs for Col-Space Design with Application to Leukocyte Detection and Tracking
SEI:Col 空间设计的分层依赖图及其在白细胞检测和跟踪中的应用
- 批准号:
0612049 - 财政年份:2006
- 资助金额:
$ 30万 - 项目类别:
Continuing Grant
EHS: Highly Flexible Multi-Mode Embedded Systems
EHS:高度灵活的多模式嵌入式系统
- 批准号:
0410526 - 财政年份:2004
- 资助金额:
$ 30万 - 项目类别:
Continuing Grant
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在中风后康复的早期阶段,调整 AFO 参数以优化步态的真正神经运动恢复
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