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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.

Orientation tracking of a moving object has a wide variety of applications, including but not limited to military, surgical aid, navigation systems, mobile robots, gaming, virtual reality, and gesture recognition. In this paper, a novel algorithm is presented to automatically track and quantify change of direction (COD) incident angles or heading angles (i.e., turning angles) of a moving athlete using the inertial sensor signals from a microtechnology unit [an inertia measurement unit (IMU)] commonly used in elite sport. The algorithm is capable of automatically classifying a COD incident according to the degree of the turn and the direction of the turn (left or right). The system involves 1) the accurate determination of the heading angle using IMU sensor fusion and 2) the use of an algorithm to detect and categorize all changes in angle using various signal computation processing techniques. This paper presents the algorithm to detect changes in angle and subsequent categorization. The algorithm is intended to accurately quantify changes in mechanical loading (angle) during COD incidents, which may present a new perspective in the monitoring of athletes for performance enhancement and injury prevention purposes.