Assessment of a New Change of Direction Detection Algorithm Based on Inertial Data
dc.contributor.author | Avilés, Roberto | |
dc.contributor.author | Souza, Diego Brito | |
dc.contributor.author | Pino Ortega, José | |
dc.contributor.author | Castellano Paulis, Julián | |
dc.date.accessioned | 2023-03-29T11:50:31Z | |
dc.date.available | 2023-03-29T11:50:31Z | |
dc.date.issued | 2023-03-14 | |
dc.identifier.citation | Sensors 23(6) : (2023) // Article ID 3095 | es_ES |
dc.identifier.issn | 1424-8220 | |
dc.identifier.uri | http://hdl.handle.net/10810/60544 | |
dc.description.abstract | The purpose of this study was to study the validity and reproducibility of an algorithm capable of combining information from Inertial and Magnetic Measurement Units (IMMUs) to detect changes of direction (COD). Five participants wore three devices at the same time to perform five CODs in three different conditions: angle (45°, 90°, 135° and 180°), direction (left and right), and running speed (13 and 18 km/h). For the testing, the combination of different % of smoothing applied to the signal (20%, 30% and 40%) and minimum intensity peak (PmI) for each event (0.8 G, 0.9 G, and 1.0 G) was applied. The values recorded with the sensors were contrasted with observation and coding from video. At 13 km/h, the combination of 30% smoothing and 0.9 G PmI was the one that showed the most accurate values (IMMU1: Cohen’s d (d) = −0.29;%Diff = −4%; IMMU2: d = 0.04 %Diff = 0%, IMMU3: d = −0.27, %Diff = 13%). At 18 km/h, the 40% and 0.9 G combination was the most accurate (IMMU1: d = −0.28; %Diff = −4%; IMMU2 = d = −0.16; %Diff = −1%; IMMU3 = d = −0.26; %Diff = −2%). The results suggest the need to apply specific filters to the algorithm based on speed, in order to accurately detect COD. | es_ES |
dc.description.sponsorship | The authors are grateful for the support received from the Government of Spain in the sub-project “Mixed methods approach in performance analysis (in training and competition) in elite and academy sports” [PGC2018-098742-B-C33] (Ministry of Science, Innovation and Universities, State Program for Knowledge Generation and Scientific and Technological Strengthening of the R+D+i System). | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.relation | info:eu-repo/grantAgreement/MICIU/PGC2018-098742-B-C33 | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.subject | validation | es_ES |
dc.subject | reliability | es_ES |
dc.subject | inertial sensors | es_ES |
dc.subject | time-motion | es_ES |
dc.title | Assessment of a New Change of Direction Detection Algorithm Based on Inertial Data | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.date.updated | 2023-03-28T12:56:49Z | |
dc.rights.holder | © 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/). | es_ES |
dc.relation.publisherversion | https://www.mdpi.com/1424-8220/23/6/3095 | es_ES |
dc.identifier.doi | 10.3390/s23063095 | |
dc.departamentoes | Educación física y deportiva | |
dc.departamentoeu | Gorputz eta Kirol Hezkuntza |
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Except where otherwise noted, this item's license is described as © 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/).