HIGHLAND INSTRUMENTS INC — Department of Health and Human Services SBIR Phase I: 108

Description

ProprietaryThis proposal includes trade secrets and other proprietary or confidential information of Highland Instruments and is being provided for use by the National Institutes of HealthNIHfor the sole purpose of evaluating this SBIR proposalNo other rights are conferredThis proposal andthe trade secrets and other proprietary or confidential information contained herein shal further not be disclosed in whole or in partsoutside of NIH without Highland Instrumentandapos s permissionThis restriction does not limit the NIHandapos s right to use information contained in the data if it is obtained fromanother source without restrictionThis legend applies to the AbstractSpecific AimsResearch Planal componentsCommercialization Planand Human Subjectandapos s Sections of this proposalAbstract The AHA Stroke Rehabilitation guideline states that in the current fiscal climatethe provision of comprehensive rehabilitation programs with adequate resourcesdoseand duration is an essential aspect of stroke care and should be a priorityWhile near and long term rehabilitation goals should be guided by patient baseline motor status and potential for motor recoveryacute motor assessment and prognostication remain a clinically difficult taskConventional clinical assessmentse gNIH Stroke ScaleFugl MeyerFMScalethat power prognosis are highly dependent on the initial severity and care provider point of careand often reduced further to even coarser prognostic scalese gOrpington Prognostic ScaleOPSOverall they lack the level of sophistication required to predict motor recovery and tailor rehabilitation due to ceiling effectsomission of fractionated and complex distal movementsand or unequal weighting of the two extremities in assessmentsFurthermoremany survivors do not even receive comprehensive assessments prior to dischargeand telestroke approaches which are being implemented to address such issues are limited in their scope of care and still not fully developed for functional assessmentsThis is critical becauseall patients benefit from a formal assessment of the patient s rehabilitation needs prior to dischargeTo address these and other limitations the AHA guidelines specifically call for the development ofcomputer adapted assessments for personalized and tailored interventionsnewer technologies such as body worn sensorsandbetter predictor models to identify responders and nonrespondersTo address these limitationswe propose to develop a system of multimodalintegrated sensorsi emotion capture camerasforce sensorsaccelerometersand gyroscopesthat will interface with a patient for recording their movementa software suite with signal processing and data fusion algorithms to reduce data dimensionality and provide kinematic kinetic based evaluationsand system software to trackclassifyand predict patient disease severityWe will test this computational Integrated sensor based Motion Analysis SuiteIMASinstroke patients undergoing IMAS directed motor evaluationsrepeatedtimes in aday periodwithindays post stroke andweeks post strokeafter having undergone rehabilitationfocused on assessments identified as important to patient independenceactivities of daily livingand ability to return to workQuantitative kinematic kinetic metrics descriptive of motor behavior will be derived from IMAS sensor recordings to characterize subjectsmotor performancee gjoint displacementvelocityaccelerationjerkand movement quality measuresThenwe will investigate the statistical relationships between the IMAS collected dataand with additional clinical data gathered during the patient assessments including demographicsimaging derived informationand FMOPSand Barthel index scoresto build statistical models toextract a low dimensional representation of disease statepredict the FM scaleandpredict likelihood of motor recovery following treatment Project Narrative Stroke is a major cause of death and the leading cause of disabilityIn the clinicthe lack of quantitativeobjective methods for outcome assessment and outcome prediction considerably hamper management of the diseaseultimately leading to sub optimal strategies for managing patient careThis study will develop a motion analysis suite for quantitativeobjective outcome assessment and prediction in stroke patients