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

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 the sustained harmonic walking (SHW), which we define as walking for at least 10 seconds with low variability of step frequency. Approach We utilize the harmonic nature of SHW and quantify local periodicity of the tri-axial raw accelerometry data. We also estimate fundamental frequency of observed signals and link it to the instantaneous walking (step-to-step) frequency (IWF). Next, we report 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 Sensitivity of the proposed classification method was found to be 97%, while specificity ranged between 87% and 97% and prediction accuracy between 94% and 97%. We report total time in SHW between 140 and 10 minutes-per-day 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 detection of SHW and estimation of IWF, based on Fourier decomposition.


Publication Date:
Feb 28 2018
Date Submitted:
Jul 01 2019
Citation:
Physiological Measurement
39
2
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 Record created 2019-07-01, last modified 2019-07-24


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