Multimodal Guidance towards Precision Rehabilitation to Improve Upper Extremity Function in Stroke Patients
多模式精准康复指导改善中风患者上肢功能
基本信息
- 批准号:10586179
- 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:2022
- 资助国家:美国
- 起止时间:2022-12-01 至 2024-11-30
- 项目状态:已结题
- 来源:
- 关键词:AccelerationActivities of Daily LivingAcuteAddressAdmission activityAffectAffectiveAlgorithmsAreaAutonomic nervous systemBiological MarkersClinicalComputer softwareDataData CollectionDecision MakingDiagnosisDimensionsElectromyographyEvaluationFamilyFutureGalvanic Skin ResponseGoalsHomeHospitalizationHospitalsHourImpairmentIndividualInpatientsKnowledgeLifeMachine LearningManufacturerMeasurementMeasuresMedicalModalityMonitorMotivationMotorMovementMuscleOutcomeOutcome AssessmentPatientsPhysiologicalProductivityPrognosisPsychological FactorsQuality of lifeRecoveryRehabilitation therapyResearch Project GrantsSamplingSeriesServicesSideStressStrokeSurfaceSweatingTask PerformancesTechniquesTestingTherapy EvaluationTimeUpper ExtremityVeteransacute strokearmarm functioncostdesigndisabilityexperiencefunctional statusimprovedinpatient serviceinsightkinematicslifetime riskmotor impairmentmultimodalitypersonalized interventionpersonalized medicinepost strokepsychologicresponsesensorstroke patientstroke rehabilitationstroke riskstroke survivorstroke therapyusabilitywearable devicewearable sensor technology
项目摘要
The lifetime risk of stroke is 1 in 6 with an estimated 33 million stroke survivors worldwide. Ideally acute
stroke patients would receive an accurate and rapid prognosis regarding return of motor function, followed
by application of those therapies most able to improve it. Yet decisions regarding post-acute treatment of
stroke patients are made on short-term assessments of function that may be influenced by concurrent
treatment, time-of-day, motivation, and other factors. Those assessments are often delayed, with resultant
delays in rehabilitation treatments. There are important decisions that need to be made about the setting
where rehabilitation occurs, if it is needed, and where the stroke patient will best live in the long-term. This
research project aims to significantly add to the current understanding of biomarkers that can be used to
provide better diagnosis, rehabilitative treatment, and long-term disposition advice for veterans who
experience upper-extremity impairments from stroke. The gaps in knowledge we aim to address are the
unknown relationships between 1. immediate post-stroke movement and functional ability, and 2. between
sympathetic tone and psychological response to disability. Clinicians do not yet know how to use the data
from wearable technologies that measure these factors – a problem caused by the volume of data generated
and lack of reliable biomarkers derived from it. Our central hypothesis is that application of machine
learning techniques to data from a multimodal sensor array worn by a patient for multiple hours can
provide better evidence of motor ability, assess latent psychological factors, and predict recovery trajectory
better than conventional short-term assessments. It may also allow more rapid personalization of therapy
plans based on real-world deficits discovered through sensor-based data. We will test our central hypothesis
by pursuing the two following specific aims with associated working hypotheses:
1. Collect functionally relevant data from a wearable inertial, electromyographic, and
electrodermal sensor array. Working Hypothesis: A few strategically placed sensors can capture
functional movement and state of the autonomic nervous system. Kinematic and physiological measures
taken during task performance will be correlated with motor impairment and functional status. Completion
of this aim will lead to the identification of functional variables derived from multimodal sensor
measurements and demonstrate the feasibility of, and challenges to, inpatient use of a sensor array.
2. Predict key clinical outcomes from sensor array-derived variables in acute stroke
inpatients being evaluated for post-discharge therapies. Working Hypothesis: Machine learning
techniques, including Bayesian fusion, will predict deficits and discharge disposition from the multimodal
variables collected. The electrodermal response to challenging movement is an unexplored area that may
provide insight into motivation and affective response to impairment. The trajectory of recovery may be
captured during a two-day sampling period. Overall low activation of the affected arm and lack of affective
responses to challenging movement will be related to poorer recovery and discharge disposition.
The modalities that will be measured by wearable sensors in this study are: acceleration, surface
muscle electrical activity, and galvanic skin responses. We will acquire data using a suite of sensors from a
single manufacturer, aiding the synchronization and convenience of collecting a time-series of data during
daily life in the hospital, as well as during motor tasks and assessments. Biomarkers will be extracted using
the Bayesian fusion algorithm, and outcomes will be both motor function and discharge disposition.
At the conclusion of this project we will have demonstrated that the proposed sensor array can
provide meaningful data regarding movement ability, affective response to motor challenges, and will have
explored the relationship between that data and discharge disposition.
中风的终生风险为六分之一,全世界估计有3300万中风幸存者。理想的急性
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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GEORGE F. WITTENBERG其他文献
GEORGE F. WITTENBERG的其他文献
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{{ truncateString('GEORGE F. WITTENBERG', 18)}}的其他基金
Brain areas that control reaching movements after stroke: Task-relevant connectivity and movement-synchronized brain stimulation
中风后控制伸手运动的大脑区域:任务相关连接和运动同步大脑刺激
- 批准号:
10316643 - 财政年份:2021
- 资助金额:
-- - 项目类别:
Brain areas that control reaching movements after stroke: Task-relevant connectivity and movement-synchronized brain stimulation
中风后控制伸手运动的大脑区域:任务相关连接和运动同步大脑刺激
- 批准号:
10516065 - 财政年份:2021
- 资助金额:
-- - 项目类别:
Neurophysiological and Kinematic Predictors of Response in Chronic Stroke
慢性中风反应的神经生理学和运动学预测因子
- 批准号:
10086003 - 财政年份:2018
- 资助金额:
-- - 项目类别:
Neurophysiological and Kinematic Predictors of Response in Chronic Stroke
慢性中风反应的神经生理学和运动学预测因子
- 批准号:
9397976 - 财政年份:2015
- 资助金额:
-- - 项目类别:
Brain Neurophysiological Biomarkers of Functional Recovery in Stroke
中风功能恢复的脑神经生理学生物标志物
- 批准号:
8635003 - 财政年份:2014
- 资助金额:
-- - 项目类别:
Driving Cortical Plasticity for Rehabilitation of Reaching After Stroke.
驱动皮质可塑性以实现中风后的康复。
- 批准号:
8108653 - 财政年份:2011
- 资助金额:
-- - 项目类别:
Driving Cortical Plasticity for Rehabilitation of Reaching After Stroke.
驱动皮质可塑性以实现中风后的康复。
- 批准号:
8460511 - 财政年份:2011
- 资助金额:
-- - 项目类别:
Driving Cortical Plasticity for Rehabilitation of Reaching After Stroke.
驱动皮质可塑性以实现中风后的康复。
- 批准号:
8286186 - 财政年份:2011
- 资助金额:
-- - 项目类别:
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