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. 2023 Feb 23;6:29. doi: 10.1038/s41746-022-00745-z

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 4 — a Distribution of accelerometer-based signal features (peak-to-peak amplitude and wavelet coefficients) for various sensor body locations and studies during normal walking. Each row corresponds to a subject while color intensity corresponds to the frequency of a given value for this subject. In each study, subjects were sorted by the location of maximum wavelet coefficient between 1.4 Hz and 2.3 Hz. b Cumulative cross-study distribution of peak-to-peak amplitude and wavelet coefficients for normal walking and other common daily activities for various sensor body locations. Distributions were normalized to have equal area under the curve. Distributions reveal that amplitude- and frequency-based features are well suited to separate walking from other activities. They also reveal visual differences between frequency-based features at locations typical to smartphone (thigh, waist, chest, arm) and smartwatch (wrist).