Prediction of sustained harmonic walking in the free-living environment using raw accelerometry data. (28th February 2018)

• Record Type: Journal Article
• Authors: Urbanek, Jacek K; Zipunnikov, Vadim; Harris, Tamara; Fadel, William; Glynn, Nancy; Koster, Annemarie; Caserotti, Paolo; Crainiceanu, Ciprian; Harezlak, Jaroslaw
• Is Part Of: Physiological measurement. Volume 39:Number 2(2018:Feb.)
• Publication Date: 2018-02-28
• Subjects: accelerometry -- movement recognition -- physical activity -- walking quantification -- wearable computing -- free-living data; Physiology -- Measurement -- Periodicals; Patient monitoring -- Periodicals; 612
• DOI: 10.1088/1361-6579/aaa74d
• Languages: English
• ISSNs: 0967-3334

Abstract

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.