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Assessment of a novel algorithm to determine change-of-direction angles while running using inertial sensors

Authors :
Balloch, Aaron
Meghji, Mahir
Newton, Robert U.
Hart, Nicolas H.
Weber, Jason A.
Ahmad, Iftekhar
Habibi, Daryoush
Balloch, Aaron
Meghji, Mahir
Newton, Robert U.
Hart, Nicolas H.
Weber, Jason A.
Ahmad, Iftekhar
Habibi, Daryoush
Source :
Research outputs 2014 to 2021
Publication Year :
2020

Abstract

The ability to detect and quantify change-of-direction (COD) movement may offer a unique approach to load-monitoring practice. Validity and reliability of a novel algorithm to calculate COD angles for predetermined COD movements ranging from 45 to 180° in left and right directions was assessed. Five recreationally active men (age: 29.0 ± 0.5 years; height: 181.0 ± 5.6 cm; and body mass: 79.4 ± 5.3 kg) ran 5 consecutive predetermined COD trials each, at 4 different angles (45, 90, 135, and 180°), in each direction. Participants were fitted with a commercially available microtechnology unit where inertial sensor data were extracted and processed using a novel algorithm designed to calculate precise COD angles for direct comparison with a high-speed video (remotely piloted, position-locked aircraft) criterion measure. Validity was assessed using Bland-Altman 95% limits of agreement and mean bias. Reliability was assessed using typical error (expressed as a coefficient of variation [CV]). Concurrent validity was present for most angles. Left: (45° = 43.8 ± 2.0°; 90° = 88.1 ± 2.0°; 135° = 136.3 ± 2.1°; and 180° = 181.8 ± 2.5°) and Right: (45° = 46.3 ± 1.6°; 90° = 91.9 ± 2.2°; 135° = 133.4 ± 2.0°; 180° = 179.2 ± 5.9°). All angles displayed excellent reliability (CV < 5%) while greater mean bias (3.6 ± 5.1°, p < 0.001), weaker limits of agreement, and reduced precision were evident for 180° trials when compared with all other angles. High-level accuracy and reliability when detecting COD angles further advocates the use of inertial sensors to quantify sports-specific movement patterns.

Details

Database :
OAIster
Journal :
Research outputs 2014 to 2021
Notes :
application/pdf, Research outputs 2014 to 2021
Publication Type :
Electronic Resource
Accession number :
edsoai.on1333621679
Document Type :
Electronic Resource