Prediction of sustained harmonic walking in the free-living environment using raw accelerometry data

Jacek K. Urbanek, Vadim Zipunnikov, Tamara Harris, William Fadel, Nancy Glynn, Annemarie Koster, Paolo Caserotti, Ciprian Crainiceanu, Jaroslaw Harezlak*

*Corresponding author for this work

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Abstract

Objective: Using raw, sub-second-level accelerometry data, we propose and validate a method for identifying and characterizing walking in the free-living environment. We focus on sustained harmonic walking (SHW), which we define as walking for at least 10 s with low variability of step frequency. Approach: We utilize the harmonic nature of SHW and quantify the local periodicity of the tri-axial raw accelerometry data. We also estimate the fundamental frequency of the observed signals and link it to the instantaneous walking (step-to-step) frequency (IWF). Next, we report the total time spent in SHW, number and durations of SHW bouts, time of the day when SHW occurred, and IWF for 49 healthy, elderly individuals. Main results: The sensitivity of the proposed classification method was found to be 97%, while specificity ranged between 87% and 97% and the prediction accuracy ranged between 94% and 97%. We report the total time in SHW between 140 and 10 min d(-1) distributed between 340 and 50 bouts. We estimate the average IWF to be 1.7 steps-per-second. Significance: We propose a simple approach for the detection of SHW and estimation of IWF, based on Fourier decomposition.
Original languageEnglish
Article number02NT02
Number of pages8
JournalPhysiological Measurement
Volume39
Issue number2
DOIs
Publication statusPublished - 1 Feb 2018

Keywords

  • accelerometry
  • movement recognition
  • physical activity
  • walking quantification
  • wearable computing
  • free-living data
  • MEASURE HUMAN MOVEMENT
  • TRIAXIAL ACCELEROMETERS
  • ACTIVITY MONITOR
  • OLDER-ADULTS
  • VALIDITY
  • POSTURE
  • SPEED
  • STEPS

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