title: Using Embedded Sensors in Independent Living to Predict Gait Changes and Falls.
abstract: This study explored using Big Data, totaling 66 terabytes over 10 years, captured from sensor systems installed in independent living apartments to predict falls from pre-fall changes in residents' Kinect-recorded gait parameters. Over a period of 3 to 48 months, we analyzed gait parameters continuously collected for residents who actually fell ( n = 13) and those who did not fall ( n = 10). We analyzed associations between participants' fall events ( n = 69) and pre-fall changes in in-home gait speed and stride length ( n = 2,070). Preliminary results indicate that a cumulative change in speed over time is associated with the probability of a fall ( p < .0001). The odds of a resident falling within 3 weeks after a cumulative change of 2.54 cm/s is 4.22 times the odds of a resident falling within 3 weeks after no change in in-home gait speed. Results demonstrate using sensors to measure in-home gait parameters associated with the occurrence of future falls.
authors.affiliation: 1 University of Missouri, Columbia, MO, USA.
authors.forename: Lorraine J
authors.initials: LJ
authors.lastname: Phillips
authors.affiliation: 1 University of Missouri, Columbia, MO, USA.
authors.forename: Chelsea B
authors.initials: CB
authors.lastname: DeRoche
authors.affiliation: 1 University of Missouri, Columbia, MO, USA.
authors.forename: Marilyn
authors.initials: M
authors.lastname: Rantz
authors.affiliation: 1 University of Missouri, Columbia, MO, USA.
authors.forename: Gregory L
authors.initials: GL
authors.lastname: Alexander
authors.affiliation: 1 University of Missouri, Columbia, MO, USA.
authors.forename: Marjorie
authors.initials: M
authors.lastname: Skubic
authors.affiliation: 1 University of Missouri, Columbia, MO, USA.
authors.forename: Laurel
authors.initials: L
authors.lastname: Despins
authors.affiliation: 1 University of Missouri, Columbia, MO, USA.
authors.forename: Carmen
authors.initials: C
authors.lastname: Abbott
authors.affiliation: 1 University of Missouri, Columbia, MO, USA.
authors.forename: Bradford H
authors.initials: BH
authors.lastname: Harris
authors.affiliation: 1 University of Missouri, Columbia, MO, USA.
authors.forename: Colleen
authors.initials: C
authors.lastname: Galambos
authors.affiliation: 1 University of Missouri, Columbia, MO, USA.
authors.forename: Richelle J
authors.initials: RJ
authors.lastname: Koopman
keywords: falls; gait speed; older adults; sensors; stride length