Deep Learning Gait Analytics for Primary Care

Alzheimerandapos s diseaseADis the most common cause of dementia and is the third leading cause of death in older adults in the USOvermillion Americans agedand older live with AD and this number is expected to climb to nearlymillion byHoweverfewer thanof individuals with AD have been diagnosedand patients who have the condition are unlikely to receive a full diagnostic workup to identify the cause sof their impairmentDetection of functional markers is an essential first step toward prevention and early diagnosis of MCIAlzheimerandapos s DiseaseADand related dementiasRecentlyseveral highly regarded clinical aging studies have demonstrated that subtle changes in gait are earlysensitive and specificnoninvasive risk markers for both cognitive decline and fall riskThe majority of these clinical investigations have used an instrumented mat systeme gthe GaitRite systemthat measures spatio temporal gait parameters from footfallsAlthough the literature is consistent about the potential for spatio temporal footfall based metrics as a predictor of MCI and dementiathe technology industry has not delivered an accurate yet affordable solution appropriate for widespread use in a primary care settingA new and novel approach is required to transfer the significant clinical research findings to clinical practiceThe goal of this SBIR is to create an accuratelow costsimple to use primary care clinical screening tool for MCI and dementia and a risk assessment and stratification tool for older adults with normal cognitionThis will be accomplished by commercializing recent research in novel software based deep learning marker less motion capture and advanced kinematic analysis methodsA secure mobile application and cloud based big data analytics platform delivers this Software as a Service to providers with the low cost and ease of use required to accelerate adoptionThis new approach applies deep learning technology to measure footfall based gait parametersIt can replicate the level of precision and accuracy of expensiveandgt $and space consuming electronic mats used in previous research studiesIn additionour work will significantly advance the research field by simultaneously measuringfrom the same video streamaccurateD joint angleswhich have recently been shown to be even more specific markers of neurodegeneration compared to footfall parametersLong Term GoalAll patients will routinely have equal access to advanced gait analytics in primary care practicesBy providing a consistent methodologyincluding integration in the Medicare Annual Wellness Visitvery large population data will be collected and analyzed to provide new insights into early stages of dementiadiscover new functional markers fromD kinematicsimprove diagnostic assessmentsand identify new preventive strategies for cognitive decline and risk of falls Alzheimer s disease continues to be difficult to predict and diagnose in clinical settings andwhile advanced imagingneuropsychological testing and CSF measures may be available to specializedclinician investigators involved in research and clinical trialsthese are not accessible togeneral health care providersResearch has clearly demonstrated that quantitative measures ofgaitnot routinely assessed in a cliniccan contribute substantially to identifying older adultsat high risk for transitioning to dementiaAvailability of the GaitIQ motion capture system at aprimary care or geriatric clinic will aid the early identification of older adults who need furtherclinical evaluationsupportive treatment and rehabilitative care