Evaluation of a restoration algorithm applied to clipped tibial acceleration signals

Z. Y. S. Chan, C. Angel, Daniel Thomson, R. Ferber, S. M. H. Tsang, Roy T. H. Cheung

Research output: Contribution to journalArticlepeer-review

Abstract

Wireless accelerometers with various operating ranges have been used to measure tibial acceleration. Accelerometers with a low operating range output distorted signals and have been found to result in inaccurate measurements of peaks. A restoration algorithm using spline interpolation has been proposed to restore the distorted signal. This algorithm has been validated for axial peaks within the range of 15.0–15.9 g. However, the accuracy of peaks of higher magnitude and the resultant peaks have not been reported. The purpose of the present study is to evaluate the measurement agreement of the restored peaks using a low-range accelerometer (±16 g) against peaks sampled using a high-range accelerometer (±200 g). The measurement agreement of both the axial and resultant peaks were examined. In total, 24 runners were equipped with 2 tri-axial accelerometers at their tibia and completed an outdoor running assessment. The accelerometer with an operating range of ±200 g was used as reference. The results of this study showed an average difference of −1.40 ± 4.52 g and −1.23 ± 5.48 g for axial and resultant peaks. Based on our findings, the restoration algorithm could skew data and potentially lead to incorrect conclusions if used without caution.

Original languageEnglish
Article number4609
Number of pages10
JournalSensors
Volume23
Issue number10
DOIs
Publication statusPublished - May 2023

Open Access - Access Right Statement

© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/)

Fingerprint

Dive into the research topics of 'Evaluation of a restoration algorithm applied to clipped tibial acceleration signals'. Together they form a unique fingerprint.

Cite this