Real-time monitoring of knee forces and kinematics in vivo
实时监测体内膝关节受力和运动学
基本信息
- 批准号:7925804
- 负责人:
- 金额:$ 12.81万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2009
- 资助国家:美国
- 起止时间:2009-07-01 至 2011-04-30
- 项目状态:已结题
- 来源:
- 关键词:AffectAlgorithmsAreaArthritisArthroplastyAustraliaBiomechanicsCensusesClinicComputational algorithmComputer SimulationComputer SystemsComputer softwareComputersDataDevicesElectronicsEventExerciseFailureFatigueFloridaFluoroscopyFutureGenerationsImplantIncidenceKineticsKneeKnee ProsthesisKnowledgeLaboratoriesLiftingLocationMeasuresMethodsModelingMonitorMotionNoiseOperative Surgical ProceduresPatient EducationPatientsPattern RecognitionPostoperative PeriodProceduresProcessProsthesisProtocols documentationPublic HealthRecreationRehabilitation therapyReportingRiskRotationStagingStressSupervisionSurfaceSystemTestingTimeTranslationsUniversitiesUniversity HospitalsValidationWalkingboneclinically relevantdata acquisitiondesignevidence basein vitro Modelin vivoinnovationinsightinstrumentkinematicsknee replacement arthroplastymagnetic fieldminiaturizenovelpublic health relevancestandard of caresurvivorship
项目摘要
DESCRIPTION (provided by applicant): Total knee arthroplasty has become the standard of care for end-stage arthritis. The US Census Bureau data predicts that demand for primary total knee arthroplasties will grow to 3.5 million procedures annually by 2030. This will double the demand for revision knee surgery by 2015 and will increase demand 600% by 2030. Knee forces directly affect arthroplasty component survivorship, wear of articular bearing surfaces, and integrity of the bone-implant interface. Excessive knee forces accelerate breakdown of the cement interface or induces damage and collapse of the underlying bone. Knee forces and component design features also determine the contact stresses on the bearing surfaces, which are directly associated with the magnitude and distribution of material wear and damage. Knowledge of in vivo knee contact forces and stresses during all activities will be extremely valuable in clearly identifying risks for implant failure. Our design objective is to develop a system for continuously monitoring knee forces and kinematics. We will use a novel algorithm to determine knee kinematics from knee forces measured in implanted force-sensing tibial prosthesis. We will validate the results against fluoroscopically measured kinematics. We will develop a wearable data acquisition system for continuous unsupervised data monitoring. We will develop a pattern recognition algorithm to classify activities in vivo. This is a unique method of obtaining in vivo knee contact forces and kinematics together with a complete contact analysis for knee arthroplasty. The ability to monitor, characterize, and classify activities in vivo over extended periods at the proposed level of technical sophistication is novel. Data generated using this system will identify weaknesses and potential areas of failure in current designs, provide insight into enhancing the function and durability of total knee arthroplasty, and support evidence-based patient education on safe postoperative rehabilitation, recreation, and exercise. PUBLIC HEALTH RELEVANCE: The data collected will be of enormous benefit to the field of knee biomechanics in general and knee arthroplasty in particular. We will be able to continuously monitor data over extended periods of time (days or weeks) and to record naturally occurring events (in contrast to choreographed activity). Since we compute tibiofemoral contact as part of the algorithm to determine the kinematics, the forces and kinematics are already accompanied with contact analysis. We have received requests from several laboratories (including Stanford University, Harvard University, Hospital for Special Surgery, Oxford University, UK, University of Florida, Seoul National University, University of Melbourne, Australia and the Mayo Clinic) for data to develop or validate in silico and in vitro models of knee kinetics and kinematics, as well as to develop more clinically relevant wear and fatigue testing protocols. These data can be used as input into damage and wear models to predict failure or for validation of biomechanical models of the knee, which predict knee forces and kinematics. Knee designs are constantly evolving. One example includes designs that will permit greater knee function and that will allow patients to engage in activities that involve kneeling, squatting, and sitting cross-legged. Studies analyzing these activities have estimated high knee forces without in vivo validation of these forces. A higher incidence of revision knee arthroplasties is reported in patients that routinely squat, kneel, or sit cross-legged. New and existing prosthetic designs will have to be modified to withstand the anticipated increase in loading. Alternative bearings surfaces are being introduced that require more clinically relevant testing than the currently proposed standards. Continuously monitoring in vivo knee forces and kinematics under daily conditions will identify weaknesses and potential areas of failure in current and future designs and will provide insight into enhancing the function and durability of total knee arthroplasty.
描述(由申请人提供):全膝关节置换术已成为终末期关节炎的标准治疗方法。美国人口普查局的数据预测,到2030年,初级全膝关节置换术的需求将增长到每年350万例。到2015年,膝关节翻修手术的需求将增加一倍,到2030年,需求将增加600%。膝关节受力直接影响关节置换术构件的存活、关节承载面磨损和骨-植入物界面的完整性。过度的膝关节力会加速骨水泥界面的破坏或引起骨底层的损伤和塌陷。膝关节力和部件设计特征也决定了轴承表面的接触应力,这与材料磨损和损坏的大小和分布直接相关。在所有活动中,膝关节接触力和应力的知识对于清楚地识别植入物失败的风险是非常有价值的。我们的设计目标是开发一个连续监测膝关节受力和运动学的系统。我们将使用一种新的算法来确定膝关节运动学从膝关节力测量植入力传感胫骨假体。我们将根据透视测量的运动学来验证结果。开发可穿戴式数据采集系统,实现连续无监督数据监测。我们将开发一种模式识别算法来对体内活动进行分类。这是一种获得活体膝关节接触力和运动学以及膝关节置换术完整接触分析的独特方法。在拟议的技术复杂水平上对长时间的体内活动进行监测、表征和分类的能力是新颖的。使用该系统生成的数据将识别当前设计中的弱点和潜在失败区域,为增强全膝关节置换术的功能和耐久性提供见解,并支持基于证据的患者安全术后康复、娱乐和运动教育。公共卫生相关性:收集的数据将对膝关节生物力学领域,特别是膝关节置换术领域产生巨大的益处。我们将能够在很长一段时间内(几天或几周)持续监控数据,并记录自然发生的事件(与精心设计的活动相反)。由于我们将计算胫股接触作为确定运动学的算法的一部分,因此力和运动学已经伴随着接触分析。我们已经收到来自几个实验室(包括斯坦福大学、哈佛大学、特殊外科医院、英国牛津大学、佛罗里达大学、首尔国立大学、澳大利亚墨尔本大学和梅奥诊所)的请求,要求提供数据,以开发或验证膝关节动力学和运动学的硅和体外模型,以及开发更多临床相关的磨损和疲劳测试方案。这些数据可以作为损伤和磨损模型的输入,以预测失效,或用于验证膝关节的生物力学模型,预测膝关节的力量和运动学。膝盖的设计在不断发展。其中一个例子包括允许更大的膝关节功能的设计,并允许患者进行包括跪、蹲和盘腿坐在内的活动。分析这些活动的研究估计了高膝关节力,但没有对这些力进行体内验证。据报道,常规下蹲、跪下或盘腿坐的患者翻修膝关节置换术的发生率较高。新的和现有的假肢设计将不得不进行修改,以承受预期的载荷增加。替代轴承表面正在引入,需要比目前提出的标准更多的临床相关测试。在日常条件下持续监测活体膝关节受力和运动学将识别当前和未来设计中的弱点和潜在失败区域,并将为增强全膝关节置换术的功能和耐用性提供见解。
项目成果
期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Knee joint forces: prediction, measurement, and significance.
- DOI:10.1177/0954411911433372
- 发表时间:2012-02
- 期刊:
- 影响因子:0
- 作者:D'Lima DD;Fregly BJ;Patil S;Steklov N;Colwell CW Jr
- 通讯作者:Colwell CW Jr
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Darryl D. D'Lima其他文献
Darryl D. D'Lima的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Darryl D. D'Lima', 18)}}的其他基金
Evaluation of In Vivo Knee Load Predictions using Instrumented Implants
使用仪器植入物评估体内膝关节负荷预测
- 批准号:
8113161 - 财政年份:2010
- 资助金额:
$ 12.81万 - 项目类别:
Evaluation of In Vivo Knee Load Predictions using Instrumented Implants
使用仪器植入物评估体内膝关节负荷预测
- 批准号:
8270573 - 财政年份:2010
- 资助金额:
$ 12.81万 - 项目类别:
Evaluation of In Vivo Knee Load Predictions using Instrumented Implants
使用仪器植入物评估体内膝关节负荷预测
- 批准号:
7985983 - 财政年份:2010
- 资助金额:
$ 12.81万 - 项目类别:
Evaluation of In Vivo Knee Load Predictions using Instrumented Implants
使用仪器植入物评估体内膝关节负荷预测
- 批准号:
8464099 - 财政年份:2010
- 资助金额:
$ 12.81万 - 项目类别:
Real-time monitoring of knee forces and kinematics in vivo
实时监测体内膝关节受力和运动学
- 批准号:
7713164 - 财政年份:2009
- 资助金额:
$ 12.81万 - 项目类别:
相似海外基金
Approximate algorithms and architectures for area efficient system design
区域高效系统设计的近似算法和架构
- 批准号:
LP170100311 - 财政年份:2018
- 资助金额:
$ 12.81万 - 项目类别:
Linkage Projects
AMPS: Rank Minimization Algorithms for Wide-Area Phasor Measurement Data Processing
AMPS:用于广域相量测量数据处理的秩最小化算法
- 批准号:
1736326 - 财政年份:2017
- 资助金额:
$ 12.81万 - 项目类别:
Standard Grant
Low Power, Area Efficient, High Speed Algorithms and Architectures for Computer Arithmetic, Pattern Recognition and Cryptosystems
用于计算机算术、模式识别和密码系统的低功耗、面积高效、高速算法和架构
- 批准号:
1686-2013 - 财政年份:2017
- 资助金额:
$ 12.81万 - 项目类别:
Discovery Grants Program - Individual
Rigorous simulation of speckle fields caused by large area rough surfaces using fast algorithms based on higher order boundary element methods
使用基于高阶边界元方法的快速算法对大面积粗糙表面引起的散斑场进行严格模拟
- 批准号:
375876714 - 财政年份:2017
- 资助金额:
$ 12.81万 - 项目类别:
Research Grants
Low Power, Area Efficient, High Speed Algorithms and Architectures for Computer Arithmetic, Pattern Recognition and Cryptosystems
用于计算机算术、模式识别和密码系统的低功耗、面积高效、高速算法和架构
- 批准号:
1686-2013 - 财政年份:2016
- 资助金额:
$ 12.81万 - 项目类别:
Discovery Grants Program - Individual
Low Power, Area Efficient, High Speed Algorithms and Architectures for Computer Arithmetic, Pattern Recognition and Cryptosystems
用于计算机算术、模式识别和密码系统的低功耗、面积高效、高速算法和架构
- 批准号:
1686-2013 - 财政年份:2015
- 资助金额:
$ 12.81万 - 项目类别:
Discovery Grants Program - Individual
Low Power, Area Efficient, High Speed Algorithms and Architectures for Computer Arithmetic, Pattern Recognition and Cryptosystems
用于计算机算术、模式识别和密码系统的低功耗、面积高效、高速算法和架构
- 批准号:
1686-2013 - 财政年份:2014
- 资助金额:
$ 12.81万 - 项目类别:
Discovery Grants Program - Individual
AREA: Optimizing gene expression with mRNA free energy modeling and algorithms
区域:利用 mRNA 自由能建模和算法优化基因表达
- 批准号:
8689532 - 财政年份:2014
- 资助金额:
$ 12.81万 - 项目类别:
CPS: Synergy: Collaborative Research: Distributed Asynchronous Algorithms and Software Systems for Wide-Area Monitoring of Power Systems
CPS:协同:协作研究:用于电力系统广域监控的分布式异步算法和软件系统
- 批准号:
1329780 - 财政年份:2013
- 资助金额:
$ 12.81万 - 项目类别:
Standard Grant
CPS: Synergy: Collaborative Research: Distributed Asynchronous Algorithms and Software Systems for Wide-Area Mentoring of Power Systems
CPS:协同:协作研究:用于电力系统广域指导的分布式异步算法和软件系统
- 批准号:
1329745 - 财政年份:2013
- 资助金额:
$ 12.81万 - 项目类别:
Standard Grant