A sensing platform for physiological and contextual feedback to tennis athletes

In this paper we describe our work on creating a multi-modal sensing platform for providing feedback to tennis coaches and players. The platform includes a fixed installation around a tennis court consisting of a video camera network and a localisation system as well as wearable sensing technology deployed to individual athletes. We describe the various components of this platform and explain how we can capture synchronised multi-modal sensor data streams for games or training sessions. We then describe the content-based retrieval system we are building to facilitate the development of novel coaching tools. We provide some examples of the queries that the system can support, where these queries are chosen to be suitably expressive so as to reflect a coach's complex information needs regarding tennis-related performance factors

Multi-sensor classification of tennis strokes

In this work, we investigate tennis stroke recognition using a single inertial measuring unit attached to a player’s forearm during a competitive match. This paper evaluates the best approach for stroke detection using either accelerometers, gyroscopes or magnetometers, which are embedded into the inertial measuring unit. This work concludes what is the optimal training data set for stroke classification and proves that classifiers can perform well when tested on players who were not used to train the classifier. This work provides a significant step forward for our overall goal, which is to develop next generation sports coaching tools using both inertial and visual sensors in an instrumented indoor sporting environment

Intelligent middleware for adaptive sensing of tennis coaching sessions

In professional tennis training matches, the coach needs to be able to view play from the most appropriate angle in order to monitor players activities. In this paper, we present a system which can adapt the operation of a series of cameras in order to maintain optimal system performance based on a set of wireless sensors. This setup is used as a testbed for an agent based intelligent middleware that can correlate data from many different wired and wireless sensors and provide effective in-situ decision making. The proposed solution is flexible enough to allow the addition of new sensors and actuators. Within this setup we also provide details of a case study for the embedded control of cameras through the use of Ubisense data

Functionalised fabrics and wearer interaction

This talk will present wearable sensor research carried within CLARITY - Centre for Sensor Web Technologies. The aim of CLARITY is to bridge the molecular and digital worlds. This interdisciplinary research encompasses all stages of development - from novel materials and sensor research right through to end user applications. The research theme is to “Bring information to life” - there is much information that can be harvested about our bodies and the environment we move through using sensor technology, the important question is what to do with all the information? It is vital to develop interactive systems that are accessible and straightforward to use. Two case studies will be presented of systems for use in hospital wards and home settings – a sensor glove for stroke rehabilitation and a breathing feedback system for respiratory rehabilitation and stress management. Another area of research involving smart fabrics for healthcare is on-body chemical analysis. This is a new and challenging concept in the field of smart fabrics and interactive textiles. This work commenced as part of the EU BIOTEX project, and in this paper we present lessons learnt and current developments and findings. Sensor glove Carbon-loaded elastomer(CE) sensors have piezo-resitive properties which can be used to detect hand movements. The CE sensors are integrated into an oedema glove which is often worn by stroke patients to reduce swelling in the hand. The glove is used to assess the patient’s performance by scoring the movements based on the Fugel-Meyer Assessment system which assesses various motor functions (0 = cannot perform; 1 = performs partially; 2 = performs fully). This method of garment-based sensed information/personalised user feedback would allow an individual to be assessed from home on a continual basis under remote supervision by a trained physical therapist. Breathing feedback A vest integrating CE stretch sensors has been developed to measure breathing patterns. Patients with respiratory illnesses often tend to take shallow short breaths which exacerbates chest muscle weakness, and associated reduced oxygen circulation, shortness of breath and fatigue. Proper breathing exercises can help to reduce these symptoms as well as strengthen muscles, improve posture and enhance mental attitude. This paper presents a wearable system which monitors breathing technique and provides straightforward feedback to the user through a graphical interface. An avatar displayed on the screen encourages diaphragmatic breathing while a real-time representation of the user’s breathing technique is also displayed. The user’s goal is to perform deep diaphragmatic breathing in synchronization with the avatar. Real-time sweat analysis Real-time analysis of sweat loss is an exciting prospect for the sports industry. Replacing the fluids and electrolytes lost during exercise is vital to ensure adequate hydration which affects health and performance. We have developed a wearable device to provide immediate feedback to the user regarding the pH level of their sweat. An array of pH indicators are used to create a coloured barcode onto thin layers of poly(methyl methacrylate) (PMMA). The barcode sensor is flexible and can adapt to the contours of the body easily. It is integrated into a sweat band to be placed on different body regions e.g. forearm, wrist or forehead. We have also developed a wearable microfluidic device to sample and analyse small quantities of sweat

Local Positioning Systems in (Game) Sports

Position data of players and athletes are widely used in sports performance analysis for measuring the amounts of physical activities as well as for tactical assessments in game sports. However, positioning sensing systems are applied in sports as tools to gain objective information of sports behavior rather than as components of intelligent spaces (IS). The paper outlines the idea of IS for the sports context with special focus to game sports and how intelligent sports feedback systems can benefit from IS. Henceforth, the most common location sensing techniques used in sports and their practical application are reviewed, as location is among the most important enabling techniques for IS. Furthermore, the article exemplifies the idea of IS in sports on two applications

Multi-sensor human action recognition with particular application to tennis event-based indexing

The ability to automatically classify human actions and activities using vi- sual sensors or by analysing body worn sensor data has been an active re- search area for many years. Only recently with advancements in both fields and the ubiquitous nature of low cost sensors in our everyday lives has auto- matic human action recognition become a reality. While traditional sports coaching systems rely on manual indexing of events from a single modality, such as visual or inertial sensors, this thesis investigates the possibility of cap- turing and automatically indexing events from multimodal sensor streams. In this work, we detail a novel approach to infer human actions by fusing multimodal sensors to improve recognition accuracy. State of the art visual action recognition approaches are also investigated. Firstly we apply these action recognition detectors to basic human actions in a non-sporting con- text. We then perform action recognition to infer tennis events in a tennis court instrumented with cameras and inertial sensing infrastructure. The system proposed in this thesis can use either visual or inertial sensors to au- tomatically recognise the main tennis events during play. A complete event retrieval system is also presented to allow coaches to build advanced queries, which existing sports coaching solutions cannot facilitate, without an inordi- nate amount of manual indexing. The event retrieval interface is evaluated against a leading commercial sports coaching tool in terms of both usability and efficiency

Game, shot and match: Event-based indexing of tennis

Identifying events in sports video offers great potential for advancing visual sports coaching applications. In this paper, we present our results for detecting key events in a tennis match. Our overall goal is to automatically index a complete tennis match into all the main tennis events, so that a match can be recorded using affordable visual sens-ing equipment and then be automatically indexed into key events for retrieval and editing. The tennis events detected in this paper are a tennis game, a change of end and a tennis serve - all of which share temporal commonalities. There are of course other events in tennis which we aim to index in our overall indexing system, but this paper focuses solely on the aforementioned tennis events. This paper proposes a novel approach to detect key events in an instrumented tennis environment by analysing a players location and the visual features of a player