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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.

Because of the need to minimize the energy consumption of sensor nodes to prolong battery life in wireless sensor networks, we have extended the research previously reported (Meghji et al. in Lecture Notes in Computer Science, vol. 6886, pp. 130–143, 2011) to conclusively demonstrate some relevant advantages of single-hop transmission power control (TPC) over multi-hop TPC. We investigate TPC in multi-hop and single-hop WSNs using typical Telosb platform parameters, which are IEEE 802.15.4 standard compliant. We provide a more detailed description of a new approach to testing TPC in multi-hop networks at the physical layer, and provide energy consumption performance results via simulation and a numerical model. Our results indicate that sending packets using a short-range multi-hop path, instead of a single-hop, does not necessarily save energy as suggested by some researchers (Zhao and Leonidas, in Wireless Sensor Networks: An Information Processing Approach, 2004; Kai et al., in 6th International Conference on ITS Telecommunications Proceedings, pp. 675–679, 2006; Monks et al., in 26th Annual IEEE Conference on Local Computer Networks, 2001. Proceedings. LCN 2001, pp. 550–559, 2001). Moreover, transmitting in single-hop networks at lower transmission power levels, while still maintaining reliable connectivity, reduced energy consumption by up to 23 %. Both the radiation and electronic components of the energy consumption are characterized. Furthermore, we show that both packet collisions and delays affect the performance of WSNs that have an increased number of hops. Since the use of TPC in star topology/cellular networks transmission can save energy, we recommend cluster based (hybrid) or similar topology over completely multi-hop topology.

Wireless sensor networks (WSNs) are distributed networks comprising small sensing devices equipped with a processor, memory, power source, and often with the capability for short range wireless communication. These networks are used in various applications, and have created interest in WSN research and commercial uses, including industrial, scientific, household, military, medical and environmental domains. These initiatives have also been stimulated by the finalisation of the IEEE 802.15.4 standard, which defines the medium access control (MAC) and physical layer (PHY) for low-rate wireless personal area networks (LR-WPAN). Future applications may require large WSNs consisting of huge numbers of inexpensive wireless sensor nodes with limited resources (energy, bandwidth), operating in harsh environmental conditions. WSNs must perform reliably despite novel resource constraints including limited bandwidth, channel errors, and nodes that have limited operating energy. Improving resource utilisation and quality-of-service (QoS), in terms of reliable connectivity and energy efficiency, are major challenges in WSNs. Hence, the development of new WSN applications with severe resource constraints will require innovative solutions to overcome the above issues as well as improving the robustness of network components, and developing sustainable and cost effective implementation models. The main purpose of this research is to investigate methods for improving the performance of WSNs to maintain reliable network connectivity, scalability and energy efficiency. The study focuses on the IEEE 802.15.4 MAC/PHY layers and the carrier sense multiple access with collision avoidance (CSMA/CA) based networks. First, transmission power control (TPC) is investigated in multi and single-hop WSNs using typical hardware platform parameters via simulation and numerical analysis. A novel approach to testing TPC at the physical layer is developed, and results show that contrary to what has be

This is an Author's Accepted Manuscript version of: Balloch, A. S., Meghji, M., Newton, R. U., Hart, N. H., Weber, J. A., Ahmad, I. , & Habibi, D. (2020). Assessment of a Novel Algorithm to Determine Change-of-Direction Angles While Running Using Inertial Sensors. Journal of Strength and Conditioning Research. 34(1) 134 - 144. Published version of record available here

Meghji, M., Balloch, A., Habibi, D., Ahmad, I., Hart, N., Newton, R., ... & Waqar, A. (2019). An Algorithm for the Automatic Detection and Quantification of Athletes Change of Direction Incidents Using IMU Sensor Data. IEEE Sensors Journal, 19(12) 4518 - 4527. Available here.