ParkinStep: Automated PD Gait and Balance Assessment for Optimizing DBS
ParkinStep: Automated PD Gait and Balance Assessment for Optimizing DBS
批准号:
8314296
负责人:
Joseph Giuffrida
金额:
$87.14万
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-30 至 2015-03-31
关键词:
AddressAffectAlgorithmsBiological Neural NetworksBradykinesiaClinicClinicalClinical ResearchComplexComputer softwareDataDatabasesDeep Brain StimulationDevelopmentDevicesDiagnosticEffectivenessEquilibriumEvaluationFeedbackFigs - dietaryFrequenciesFunctional disorderGaitGeographic LocationsHealth Care CostsHealth Insurance Portability and Accountability ActHealth Services AccessibilityHome environmentHourHumanInstructionLeadLearningLower ExtremityMeasuresMethodsModelingModificationMonitorMotionMotorMovementMovement DisordersMulti-Institutional Clinical TrialOnline SystemsOperative Surgical ProceduresOutcomeOutcome AssessmentOutputParkinson DiseasePatientsPhaseQuality of lifeReportingResearch InfrastructureSafetyServicesSeveritiesSpecialistSpeedStudy SubjectSummary ReportsSymptomsSystemTabletsTechniquesTechnologyTestingTimeTrainingTreatment EffectivenessTremorUpper ExtremityVisitWireless Technologybasecomputerized data processingdesigndiariesdisabilityequilibration disorderexperiencefall riskfallsimprovedinnovationneurotechnologynovelprogramsresponsesensorsuccesstooltouchscreentrendweb based interface
中文摘要
描述(由申请人提供):目的是设计、构建和临床评估ParkinStep,这是一种创新的神经技术,集成了无线运动传感、自动化家庭帕金森病(PD)步态和平衡评估以及脑深部电刺激(DBS)参数估计,使用基于网络的数据库模型整合各临床中心的数据。DBS手术后,在诊所进行刺激设置程控,以优化治疗效果。上肢运动症状,如震颤、运动迟缓(运动减慢)和僵硬,通常根据DBS设置进行评价。虽然步态和平衡是生活质量指标的关键组成部分,下肢功能障碍可能导致残疾,但目前的临床评价有限。刺激完全影响步态和平衡所需的时间可能超过程控会话的典型时间。虽然DBS对震颤的影响可能几乎是即时的,但在调整刺激设置时,获得关于刺激有效性、步态和平衡的反馈可能需要超过三个小时。从编程的角度来看,刺激设置对步态和平衡的影响不如其他运动症状了解,可能是由于步态中涉及的复杂运动电路。ParkinStep将通过家庭监测来解决这些问题,以充分捕捉刺激的效果和全天可能经历的波动。此外,在家庭测试期间收集的患者数据将持续编译到符合HIPAA的在线数据库中,以自动输出建议的刺激设置。因此,临床医生无论地理位置或编程经验如何,都可以使用该服务来改善步态和平衡的DBS编程结果。II期开发产生的临床系统将1)允许高依从性家庭监测PD步态和平衡症状以响应DBS,2)允许临床医生使用刺激参数估计模型优化PD对DBS的响应,以及3)解决患者临床访问的地理差异,以评估步态和平衡障碍。这将通过修改我们现有的Kinesia HomeView系统来实现,以便在家庭环境中实现下肢磨损和高顺应性。将在多中心临床研究中对系统进行评价,以填充在线数据库,从而训练DBS参数估计模型。最后,开发的模型将用于临床影响研究,以确定ParkinStep系统是否可以实现比传统方法更好的DBS步态和平衡反应。
公共卫生相关性:与帕金森病(PD)患者步态和平衡障碍相关的跌倒风险可导致严重残疾,并对治疗质量产生负面影响。
生活程控脑深部电刺激(DBS)参数以治疗PD步态和平衡症状比其他症状(包括震颤和运动迟缓)更具挑战性。ParkinStep:用于优化DBS的自动PD步态和平衡评估是一种创新的神经技术,它集成了无线运动传感、自动化家庭步态和平衡评估以及使用基于网络的数据库模型的DBS参数估计,以改善程控结果和患者生活质量并降低医疗保健成本。
英文摘要
DESCRIPTION (provided by applicant): The objective is to design, build, and clinically assess ParkinStep, an innovative neurotechnology that integrates wireless motion sensing, automated home-based Parkinson's disease (PD) gait and balance assessment, and deep brain stimulation (DBS) parameter estimation using a web-based database model to integrate data across clinical centers. Following DBS surgery, programming of stimulation settings is performed in the clinic to optimize treatment effectiveness. Upper extremity motor symptoms such as tremor, bradykinesia (slowed movements), and rigidity are typically evaluated in response to DBS settings. Although gait and balance are critical components to quality of life measures and lower extremity dysfunction can be disabling, current in-clinic evaluations are limited. The time required for stimulation to fully impact gait and balance may exceed the typical time of a programming session. While the effect of DBS on tremor may be almost immediate, obtaining feedback on stimulation effectiveness, gait and balance may require in excess of three hours when stimulation settings are adjusted. From a programming standpoint, the effect of stimulation settings on gait and balance is less understood than with other motor symptoms, possibly due to the complex motor circuits involved in gait. ParkinStep will address these concerns through home monitoring to fully capture the effect of stimulation and possible fluctuations experienced throughout the day. In addition, the patient data collected during home tests will be continuously compiled into an online HIPAA-compliant database to automatically output suggested stimulation settings. Therefore, clinicians, independent of geographic location or programming experience, will have access to this service for improved DBS programming outcomes of gait and balance. The clinical system resulting from Phase II development will 1) allow high compliance home monitoring of PD gait and balance symptoms in response to DBS, 2) allow clinicians to optimize PD response to DBS using a stimulation parameter estimation model, and 3) address geographic disparities of patient clinical access to evaluate gait and balance impairment. This will be achieved by modifying our existing Kinesia HomeView system for lower extremity wear and high compliance in the home settings. The system will be evaluated in a multi-center clinical study to populate the online database to train the DBS parameter estimation model. Finally, the developed model will be used in a clinical impact study to determine whether the ParkinStep system can achieve improved gait and balance response to DBS over traditional methods.
PUBLIC HEALTH RELEVANCE: Fall risk associated with gait and balance impairment in Parkinson's disease (PD) patients can cause significant disability and negatively affect quality of
life. Programming of deep brain stimulation (DBS) parameters to treat PD gait and balance symptoms is significantly more challenging than for other symptoms including tremor and bradykinesia. ParkinStep: Automated PD Gait and Balance Assessment for Optimizing DBS is an innovative neurotechnology that integrates wireless motion sensing, automated home-based gait and balance assessment, and DBS parameter estimation using a web-based database model to improve programming outcome and patient quality of life and reduce healthcare costs.
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