2021
Wearables and Deep Learning Classify Fall Risk From Gait in Multiple Sclerosis
Meyer B, Tulipani L, Gurchiek R, Allen D, Adamowicz L, Larie D, Solomon A, Cheney N, McGinnis R. Wearables and Deep Learning Classify Fall Risk From Gait in Multiple Sclerosis. IEEE Journal Of Biomedical And Health Informatics 2021, 25: 1824-1831. PMID: 32946403, PMCID: PMC8221405, DOI: 10.1109/jbhi.2020.3025049.Peer-Reviewed Original ResearchConceptsWearable sensorsPreventive interventionsBidirectional long short-termInexpensive wearable sensorsDeep neural networksWearable sensor dataFall prevention interventionsSpatiotemporal gait parametersFall risk assessmentLong-Short-TermMachine learning modelsGait biomechanicsGait parametersSensor dataFall riskNeural networkHealthcare providersStatistical featuresLearning modelsPatient reportsAccelerometer dataIdentified measuresMultiple sclerosisWearableGood performance
2015
Detection of postural sway abnormalities by wireless inertial sensors in minimally disabled patients with multiple sclerosis: a case–control study
Solomon A, Jacobs J, Lomond K, Henry S. Detection of postural sway abnormalities by wireless inertial sensors in minimally disabled patients with multiple sclerosis: a case–control study. Journal Of NeuroEngineering And Rehabilitation 2015, 12: 74. PMID: 26324067, PMCID: PMC4556213, DOI: 10.1186/s12984-015-0066-9.Peer-Reviewed Original ResearchConceptsActivities-specific Balance ConfidenceWireless inertial sensorsBalance impairmentMSWS-12Postural swayExpanded Disability Status ScaleMobility impairmentsPatient reportsMeasures of postural swayTimed 25-Foot WalkMS Walking ScaleMSWS-12 scoresImpaired gait speedSway path lengthResultsThe regression modelPredictors of group statusRegression modelsEyes-open conditionLogistic regression modelsCase-control studyBalance confidenceGait speedInertial sensorsInertial motion sensorsInstrumented sway