Raymond Leadbetter

An integrated swimming monitoring system for the biomechanical analysis of swimming strokes

This paper describes the development of a complete wearable swimming system for performance analysis, together with a sample application. The system comprises wearable nodes, data processing tools in MATLAB™ and integration with video. The swimming nodes are small in size and designed to be worn on body segments of interest, typically lower leg, lower arm, and the sacral or cervical regions. Each node contains inertial sensors, screen, data storage and RF communications for synchronisation and data download. The device is controlled using a microcontroller with a scheduler-based operating system to conserve power and is custom-packaged with a user interface and USB port that is fully waterproof. The cost of manufacture is a few hundred dollars in small-run quantities. The developed analysis software builds upon previously developed tools, can communicate with the nodes individually and can synchronise the recording of multiple units through a custom-developed protocol. Video is integrated into the developed tools as a method of presenting the sensor data alongside a more traditional analysis tool. A case study of the system analyses swim stroke phase with video and demonstrates the utility of the system as a tool for temporal stroke phase identification in the high-performance environment.

Peak outward acceleration and ball release in cricket

Abstract The purpose of this study was to investigate the utility of peak outward acceleration (POA) measured from an inertial sensor worn at the wrist as an indicator of the critical end point of the bowling action – ball release, a critical element when assessing illegal actions. Twenty-one finger-spin and fast bowlers from nine countries were recruited from the ICC under-19 Cricket World Cup to take part in this research. Bowlers delivered a cross section of their standard deliveries while wearing an inertial sensor placed on their wrists. Ball release was determined by a validated motional analysis ball release (MABR) protocol and compared to the simultaneously collected POA. POA was shown to be highly correlated with MABR (R2 = 0.98) and a Bland–Altman plot indicated that all 148 trials were within the 3.42 frame (0.014 s) limits of agreement. POA when measured by an inertial sensor worn on the wrist during bowling had a close relationship with an established method of identifying ball release in a biomechanical laboratory regardless of bowler and delivery type. Further, accuracy can be achieved with the adoption of a simple regression equation applied to the POA and as such is a valid measure of ball release in cricket bowlers.

Quantifying and assessing biomechanical differences in swim turn using wearable sensors

The swim turn makes up a substantial portion of the total swim time in competition, and efficient turns can determine finishing positions in many competitions. Swim turns can be a neglected area of performance gain. This is largely due to the difficulty in extracting performance measures that might lead to improvement. An inertial sensor was used to assess the different phases of the swimming turn and the data were then compared to the synchronised video data. As a case study, two elite swimmers, a competitive pool swimmer and an elite Triathlete, were compared as a demonstration of the technology as a potential tool for routine use. The participants were asked to perform their typical tumble turn at two velocities. Timing of the rotation relative to the turns push off was measured. The inertial sensor detected differences in rotation between the two swimmers tested. The sensor reported that push off occurred for the competitive swimmer before 90°and for the Triathlete after 90°of rotation and was confirmed by video footage.

An Architectural Based Framework for the Distributed Collection, Analysis and Query from Inhomogeneous Time Series Data Sets and Wearables for Biofeedback Applications

The increasing professionalism of sports persons and desire of consumers to imitate this has led to an increased metrification of sport. This has been driven in no small part by the widespread availability of comparatively cheap assessment technologies and, more recently, wearable technologies. Historically, whilst these have produced large data sets, often only the most rudimentary analysis has taken place (Wisbey et al in: “Quantifying movement demands of AFL football using GPS tracking”). This paucity of analysis is due in no small part to the challenges of analysing large sets of data that are often from disparate data sources to glean useful key performance indicators, which has been a largely a labour intensive process. This paper presents a framework that can be cloud based for the gathering, storing and algorithmic interpretation of large and inhomogeneous time series data sets. The framework is architecture based and technology agnostic in the data sources it can gather, and presents a model for multi set analysis for inter- and intra- devices and individual subject matter. A sample implementation demonstrates the utility of the framework for sports performance data collected from distributed inertial sensors in the sport of swimming.

Low power IEEE 802.15.4 ocean sensor mesh network for dynamic signal propagation characterisation in a wave tank

Commercialisation of the Internet of things has generated a large area of research into a variety of new applications of sensor networks. While research has been conducted into the application of wireless sensor networks for ocean monitoring. Substantial challenges exists for the reliable performance of low cost, low power wireless sensor networks operating in Gigahertz frequency spectrum on the sea surface. Reduction in line of sight communication from passing ocean waves presents a unique challenge for high performance networks while sustaining low power usage. This paper reports on the effects of obstructed line of sight communication with identification of sensor wave height and the effects had on network performance. Through the deployment of a IEEE 802.15.4 specification sensor network in a mechanically simulated wave tank this paper aims to identify changes in network performance based on relative sensor height above the waters surface for improved low power performance in a low cost ocean sensor network.