Szczegóły publikacji
Opis bibliograficzny
Sampling frequency requirements for estimating physical activity metrics from wearable accelerometer data / Marcin STRĄCZKIEWICZ // Sensors [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 1424-8220 . — 2026 — vol. 26 iss. 20 art. no. 6652, s. 1–22. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 20–22, Abstr. — Publikacja dostępna online od: 2026-10-21
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Dane bibliometryczne
| ID BaDAP | 171316 |
|---|---|
| Data dodania do BaDAP | 2026-11-12 |
| Tekst źródłowy | URL |
| DOI | 10.3390/s26206652 |
| Rok publikacji | 2026 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Sensors |
Abstract
Highlights What are the main findings? What are the implications of the main findings?Highlights What are the main findings? What are the implications of the main findings?Abstract Accelerometers are widely used to quantify physical activity in population health research, yet the sampling frequency required to preserve commonly reported measures remains uncertain. We evaluated sampling frequency using 315.4 h of labelled tri-axial accelerometer data from 321 participants across 11 publicly available datasets. Signals were harmonized to a 50 Hz reference and downsampled to 40, 30, 20, 10, and 5 Hz using anti-aliased resampling. We compared Monitor-Independent Movement Summary (MIMS), Euclidean Norm Minus One (ENMO), Activity Index (AI), dominant spectral frequency, and retained spectral power across activities and sensor locations. For MIMS, 20 Hz remained within the prespecified 5% error margin for many walking, stair-climbing, cycling, jumping, household activities, and motorized-transportation conditions, whereas running exceeded this margin at 20 Hz at lower-limb and trunk locations. At 10 Hz, errors increased for most ambulatory activities, and only about 60-72% of reference spectral power was retained for walking and running, despite preservation of their dominant movement frequencies. MIMS error was not associated with age, sex/gender, or BMI, although small sex/gender associations were observed for ENMO and AI. Sampling-frequency requirements, therefore, depend on the metric, activity, and sensor location, supporting fit-for-purpose selection rather than use of a single universal sampling rate.