The use of inertial sensors for distinguishing different types of users' everyday activities was demonstrated in existing work. The sensing for sports and managed exercise (SESAME) project investigates a different aspect of on-body wireless inertial sensing: one of the major aims of the project is to evaluate whether inertial sensors are useful for detecting the smallest details of a rapidly moving (foot) motion of a sprinter, which would be useful for coaching support. In this paper, we present our on-body wireless inertial sensing system, and analyse our system in three aspects: a) a foot motion analysis using the collected inertial data of sprinters; b) the system's physical characteristics (i.e. weight and operational behaviour); and c) the system's wireless performances.

Analysis of Wireless Inertial Sensing for Athlete Coaching Support

Towards real-time profiling of sprints using wearable pressure sensors

This paper describes the design, implementation and deployment of a wireless sensor system for athletes. The system is designed to profile sprints based on input from on-body sensors that are wirelessly connected to a nearby infrastructure. We discuss the choice and use of inexpensive Force Sensitive Resistors (FSRs) to measure foot event timings and provide a detailed analysis of the profiling method used to represent high-level information to the coaches and athletes. In this profiling method, we detect sprinting intervals from high-resolution sensor data, and compute the ground contact times for sprinting performances. We validate our results using force plates and show that the system achieves comparable accuracy in measuring the foot contact times (millisecond accuracy) without the limitations of one or few steps.

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Profiling sprints using on-body sensors

Next generation wireless networks are integrated the multiple wireless access technologies in order to provide the users with the best connection. The vertical handover decision algorithm is an important role to guarantee the seamless mobility in single mobile terminal. In this paper, we apply the radial basis function neural network (RBFNN) for the decision making process in vertical handover based on received signal strength, mobile speed and monetary cost metrics. The simulation results indicate that the proposed approach outperforms in reducing the unnecessary handover and connection dropping but increasing the grade of service with comparing the other two methods as threshold and back propagation neural network.

Vertical Handover Decision Based on RBF Approach for Ubiquitous Wireless Networks

This work illustrates a complete design flow of an electronic system developed to support applications in which there are the need to measure motion parameters and transmit them to a remote unit for real-time teleprocessing. In order to be useful in many operative contexts, the system is flexible, compact, and lightweight. It integrates a tri-axial inertial sensor, a GPS module, a wireless transceiver and can drive a pocket camera. Data acquisition and packetization are handled in order to increase data throughput on Radio Bridge and to minimize power consumption. A trajectory reconstruction algorithm, implementing the Kalman-filter technique, allows obtaining real-time body tracking using only inertial sensors. Thanks to a graphical user interface it is possible to remotely control the system operations and to display the motion data.

A Complete Design Flow of a General Purpose Wireless GPS/Inertial Platform for Motion Data Monitoring

In recent years, the use of inertial sensing for body motion recognition has been demonstrated. However, existing work generally focuses on upper-body movements, which involve smaller scale movements and are less rapid. In this paper, we present two distinctive types of demonstration that show how on-body wireless inertial sensing can be used to capture detail inertial information of the more rapidly moving lower-body segments (e.g. the foot). The first demonstration shows how useful coaching support information for a sprinting exercise are captured; the second demonstration shows how inertial information of the lower segments are used to support football computer game applications, through which the users may trigger the appropriate on-screen actions by their foot motion, instead of using the current hand-held inertial sensing controllers.

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L. Cheng

Papers

On-body wireless inertial sensing foot control applications