ArticleSensors (Basel, Switzerland)2023
Assessment of a New Change of Direction Detection Algorithm Based on Inertial Data.
Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Trial
- Leg dominance influences side-specific directional movement demands during change-of-direction movements in elite youth soccer players.Frontiers in sports and active living · 2026Article
- Interpretable Machine Learning on Simulation-Derived Biomechanical Features for Hamstrings-Quadriceps Imbalance Detection in Running.Sports (Basel, Switzerland) · 2025Article
- Exploring the Relationship Between Game Performance and Physical Demands in Youth Male Basketball Players.Journal of functional morphology and kinesiology · 2025Article
- Relationship between Physical Demands and Player Performance in Professional Female Basketball Players Using Inertial Movement Units.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.