ETSense: Adaptive Portable Essential Tremor Monitor
ETSense: Adaptive Portable Essential Tremor Monitor
批准号:
8200062
负责人:
Dustin A. Heldman
金额:
$69.23万
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:
2009-09-01 至 2013-08-31
关键词:
Academic Medical CentersAccountingActivities of Daily LivingAffectAgeAlgorithmsCaringCellsClinicalClinical DataClinical ResearchComplexComputersContinuous TremorsDataData CollectionData ReportingData Storage and RetrievalDeep Brain StimulationDetectionDevelopmentDevice or Instrument DevelopmentDevicesDiscriminationDiseaseEnsureEssential TremorEvaluationFingersFunctional disorderGenerationsGenesGrowthHealth Care CostsHealth Services AccessibilityHome environmentHourHousingHumanIntention TremorInterventionJudgmentKineticsLifeLimb structureMasksMeasuresMedical DeviceMedicineMemoryMonitorMotionMovementMovement DisordersMultiple SclerosisOffice VisitsOnline SystemsOutcomeParkinson DiseasePatientsPerformancePharmaceutical PreparationsPharmacologic SubstancePhasePopulationPrevalenceRadioReportingResearchResolutionRestRural PopulationSecureSeveritiesSignal TransductionSiliconesSymptomsSystemTechnologyTestingTherapeutic InterventionTimeTransplantationTreatment ProtocolsTremorUnderserved PopulationUnited StatesValidationWireless TechnologyWristactigraphybasecollegedata acquisitiondata exchangedesigndiariesergonomicsimprovedinnovationkinematicsnovelnovel therapeutic interventionprogramsprototyperesearch and developmentresponsesensorweb interface
中文摘要
描述(由申请人提供):目的是设计、实施和临床评估ETSense,一种自适应、紧凑、便携式特发性震颤(ET)监测仪,用于优化治疗干预。ET的主要特征是肢体的体位性和动态性(动作)震颤,这些震颤由各种主观震颤评定量表评定。这些量表都在一个离散的时间点提供了一个离散的、主观的症状评级,需要临床医生直观地评估患者,并且不能捕捉到全天因干预而发生的复杂波动。在日常活动中持续客观地捕捉ET症状,并使用自适应算法对震颤类型和严重程度进行分类,将有助于临床医生更好地滴定治疗,以最大限度地减少症状波动,并将护理扩大到农村和服务不足的人群。第一阶段ETSense工作成功地使用了从放置在ET受试者手指上的传感器单元记录的运动学数据,以区分与日常活动相关的震颤和自主运动,并客观地量化震颤严重程度,得分与临床医生的定性评分高度相关,为持续的ET评估提供了标准化的平台。将震颤量化算法外推到非标准化任务中,表明在日常生活活动中全天连续评估震颤是可行的。提出的系统的三个主要创新包括:1)一个紧凑、便携、用户穿戴的设备,用于adl期间的连续监测;2)智能、自适应算法,连续分类震颤类型和频率严重程度;3)基于网络的症状反应报告访问。临床部署的系统将包含在一个轻量级的,手指佩戴的外壳中,当患者在家中或公共场所进行日常任务时,可以持续佩戴。一个按钮日记将允许病人指示何时服药。所有数据将存储在存储器中,以供后续分析和报告生成,详细说明对治疗干预的反应的症状波动。在第一阶段开发的自适应算法将进一步优化,以考虑可能产生震颤假阳性或掩盖运动学震颤信号的自主运动。系统将根据检测到的任意自主运动在评分算法(即静止、动态)之间切换。数据收集完成后,临床医生将使用网络界面查看患者报告。这些报告将详细说明震颤的类型、严重程度和波动,以及何时服用药物,以帮助临床医生优化现有的治疗干预措施或研究和开发新的治疗方案。我们假设商业ETSense系统将1)在日常生活活动中持续量化震颤严重程度,2)通过更好和/或更快的药物优化改善患者结果,3)通过减少办公室就诊减少医疗保健成本,4)通过高分辨率连续家庭监测促进新型治疗干预的测试和验证。
英文摘要
DESCRIPTION (provided by applicant): The objective is to design, implement, and clinically assess ETSense", an adaptive, compact, portable essential tremor (ET) monitor for optimizing therapeutic interventions. ET is characterized primarily by postural and kinetic (action) tremors of the limbs, which are rated by various subjective tremor rating scales. These scales all provide a discrete, subjective symptom rating at a discrete point in time, require a clinician to visually assess the patient, and cannot capture complex fluctuations that occur throughout the day in response to interventions. Objectively capturing ET symptoms continuously during daily activities and using adaptive algorithms to both classify tremor types and severity will help clinicians better titrate therapy to minimize symptom fluctuations and expand care to rural and underserved populations. The Phase I ETSense effort successfully used kinematic data recorded from a sensor unit placed on the finger of subjects with ET to discriminate tremor from voluntary motion associated with daily activities and objectively quantified tremor severity with scores highly correlated with clinicians' qualitative ratings, providing a standardized platform for continuous ET assessment. Tremor quantification algorithms were extrapolated to non-standardized tasks, suggesting that it is feasible to rate tremor continuously throughout the day during activities of daily living. The three primary innovations of the proposed system include: 1) a compact, portable, user-worn device for continuous monitoring during ADLs, 2) intelligent, adaptive algorithms to continuously classify tremor type and rate severity, and 3) web-based access to symptom response reports. The clinically deployable system will be contained in a lightweight, finger-worn housing for continuous wear while patients perform everyday tasks at home or in public. A push button diary will allow the patient to indicate when medication is taken. All data will be stored in memory for subsequent analysis and report generation detailing symptom fluctuations in response to therapeutic interventions. Adaptive algorithms developed in Phase I will be further optimized to account for voluntary motion that can create tremor false positives or mask over kinematic tremor signals. The system will shift between scoring algorithms (i.e. rest, kinetic) based on any voluntary motion detected. After data collection is complete, clinicians will use a web-interface to view patient reports. These reports will detail tremor type, severity, and fluctuations, as well as when medication was taken to aid clinicians in optimizing existing therapeutic interventions or in the research and development of novel treatment protocols. We hypothesize that the commercial ETSense system will 1) continuously quantify tremor severity throughout the day during activities of daily living, 2) improve patient outcomes with better and/or faster medication optimization, 3) decrease healthcare costs by reducing office visits, and 4) enable the testing and validation of novel therapeutic interventions, facilitated by high-resolution continuous home monitoring.
PUBLIC HEALTH RELEVANCE: Essential tremor, characterized primarily by tremor during movement, affects approximately 4% of the population over age 40 in the United States, though exact prevalence may be much higher since up to 90% of ET patients do not seek treatment. The proposed ETSense adaptive, portable essential tremor monitor will classify tremor type and rate tremor severity continuously throughout the day while a patient performs typical activities, which should help clinicians to better prescribe treatment and aid in the development of novel therapeutic interventions.
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