Managing Dementia through a Multisensory Smart Phone Application to Support Aging in Place
Managing Dementia through a Multisensory Smart Phone Application to Support Aging in Place
批准号:
9339726
负责人:
Tanvi Banerjee
金额:
$17.02万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-09-01 至 2019-08-31
关键词:
AddressAgingAlzheimer&aposs DiseaseAreaAssisted Living FacilitiesBayesian ModelingBehaviorCaregiver BurdenCaregiversCaringCellular PhoneChronicClinicalClinical ResearchCollaborationsCommunity HealthCouplesCustomDataData AnalysesDementiaDementia caregiversDevelopmentDevelopment PlansDiagnosisEarly InterventionElderlyEngineeringEnsureGeriatricsGoalsHealthHealthcareHome environmentImpaired cognitionIndividualIndustryInterventionK-Series Research Career ProgramsKnowledgeLearningLongitudinal StudiesLongitudinal observational studyMachine LearningMapsMentorsMethodsMissouriModalityModelingMonitorParticipantPatientsPatternPersonsPhysiologicalPilot ProjectsQuality of lifeQuestionnairesRecruitment ActivityReportingResearchResearch AssistantResearch PersonnelSemanticsSignal TransductionStressStructureSymptomsSystemTechnologyTestingTimeUniversitiesValidationWorkagedbasebehavior changecareer developmentcohortcomputer based statistical methodscomputer sciencecostdata modelingdesigndigitalexperiencefitnessimprovedindividual patientinstructorinstrumentlearned behaviormedical schoolsmeetingsmembermild cognitive impairmentmobile applicationmultisensoryprimary caregiverprofessorprogramsrehabilitation technologyresearch clinical testingsensorsupport toolstraitusabilityweb app
中文摘要
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英文摘要
SUMMARY
This proposal is for an NLM sponsored K01 Mentored Career Development Award. The
research I propose involves the development of a smart mobile application combined with
commercially available sensors, to capture actionable information about behavior pattern
changes in both patients with dementia and their primary caregivers. Through continuously
collected physiological sensor data, I will build data models that can learn the behavior patterns
of both the patient with dementia and his/her caregiver. My research plan involves three stages.
The first stage involves instrument validation and generating context-specific ground truth or the
baseline for each participating couple. The second stage will involve longitudinal observational
study using the system built in the first stage in an assisted living facility. The final stage will
involve deploying our system for a longitudinal study in the homes of our participants. This study
merges well with my short term goals to learn more about the challenges faced by older adults
as they battle physical and cognitive decline. As a computer science researcher, my long term
goal is to work on building technologies that allow older couples to live independently in their
homes for a longer time, and to have more control over their quality of life. I have experience
working in eldercare research as a part of my doctoral studies in University of Missouri's Center
for Eldercare and Rehabilitation Technology. I plan to continue working in this field and develop
my independent research program that facilitates aging in place through the use of low cost
sensors and machine learning analytics. Currently as an Instructor and Research Assistant
Professor at Wright State University's Department of Computer Science and Engineering, I have
strong mentors both in the technical and clinical areas that will allow me to grow in this highly
interdisciplinary area. My career development plan includes coursework, regular meetings with
mentors and collaborators, and practical clinical study experience that will facilitate my
development of an independent research program that will enrich and improve the lives of older
adults for years to come.
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