2022
How Much Data Is Enough? A Reliable Methodology to Examine Long-Term Wearable Data Acquisition in Gait and Postural Sway
Meyer B, Depetrillo P, Franco J, Donahue N, Fox S, O’Leary A, Loftness B, Gurchiek R, Buckley M, Solomon A, Ng S, Cheney N, Ceruolo M, McGinnis R. How Much Data Is Enough? A Reliable Methodology to Examine Long-Term Wearable Data Acquisition in Gait and Postural Sway. Sensors 2022, 22: 6982. PMID: 36146348, PMCID: PMC9503816, DOI: 10.3390/s22186982.Peer-Reviewed Original ResearchConceptsFree-living environmentBalance impairmentIntra-class correlationPostural sway measuresMeasures of gaitEvaluation of gaitWearable accelerometer dataWear durationSway measuresPostural swayCapturing gaitEstablished patientMovement variabilityImpairment measuresGaitPatient burdenAccelerometer dataClinical measuresDays of monitoringWearable sensor-based methodsSensor wearSwayRegression analysisComprehensive assessmentStudy costs
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