Classifying step and spin turns using wireless gyroscopes and implications for fall risk assessments

Peter C. Fino, Christopher W. Frames, Thurmon Lockhart

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Recent studies have reported a greater prevalence of spin turns, which are more unstable than step turns, in older adults compared to young adults in laboratory settings. Currently, turning strategies can only be identified through visual observation, either in-person or through video. This paper presents two unique methods and their combination to remotely monitor turning behavior using three uniaxial gyroscopes. Five young adults performed 90° turns at slow, normal, and fast walking speeds around a variety of obstacles while instrumented with three IMUs (attached on the trunk, left and right shank). Raw data from 360 trials were analyzed. Compared to visual classification, the two IMU methods' sensitivity/specificity to detecting spin turns were 76.1%/76.7% and 76.1%/84.4%, respectively. When the two methods were combined, the IMU had an overall 86.8% sensitivity and 92.2% specificity, with 89.4%/100% sensitivity/specificity at slow speeds. This combined method can be implemented into wireless fall prevention systems and used to identify increased use of spin turns. This method allows for longitudinal monitoring of turning strategies and allows researchers to test for potential associations between the frequency of spin turns and clinically relevant outcomes (e.g., falls) in non-laboratory settings.

Original languageEnglish (US)
Pages (from-to)10676-10685
Number of pages10
JournalSensors (Switzerland)
Volume15
Issue number5
DOIs
StatePublished - 2015

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risk assessment
Gyroscopes
gyroscopes
classifying
Risk assessment
sensitivity
Sensitivity and Specificity
joints (junctions)
Young Adult
visual observation
walking
Monitoring
Research Personnel
Observation

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Classifying step and spin turns using wireless gyroscopes and implications for fall risk assessments. / Fino, Peter C.; Frames, Christopher W.; Lockhart, Thurmon.

In: Sensors (Switzerland), Vol. 15, No. 5, 2015, p. 10676-10685.

Research output: Contribution to journalArticle

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