Alexander D. Young

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A realtime posture tracking system has been developed using a network of compact wireless sensor devices worn by the user. Each device is a complete inertial/magnetic tracking unit which performs <i>in situ</i> orientation estimation based on its own sensor readings, using a complementary quaternion-based filter. Compared to existing systems which transmit(More)
Presents simulations of an algorithm for estimating linear acceleration of wireless inertial measurement units based on body model constraints. The behaviour of the proposed algorithm is compared to existing algorithms based on motion capture data from the Carnegie Mellon University motion capture corpus. The new algorithm is demonstrated to be capable of(More)
Advances in the miniaturisation of inertial sensors have allowed the design of compact wireless inertial orientation trackers. Such devices require data fusion algorithms to process sensor data into estimated orientations. This paper examines the problem of inertial sensor data fusion and compares two alternative methods for orientation estimation:(More)
The use of wireless devices with accelerometers and gyroscopes to measure the movements of humans and objects is a growing area of interest. Applications range from simple activity detection to detailed full-body motion capture using networks of sensors worn on the body. A variety of algorithms have been proposed for these applications, but opportunities(More)
Networks of Wireless Inertial Measurement Units (WIMUs) allow for the real time capture of orientation data from multiple devices. Combining data from WIMUs with a rigid body model allows estimation of subject posture. However, posture information is not sufficient for full-body motion capture, the position of the subject in space must also be tracked. In(More)
Motion capture using wireless inertial measurement units (IMUs) has many advantages over other techniques. Achieving accurate tracking with IMUs presents a processing challenge, especially for real time tracking. Centralised approaches are bandwidth-intensive and prone to error from packet loss. Methods based solely on local knowledge have poor dynamic(More)
The use of local processing to reduce data transmission rates, and thereby power and bandwidth requirements, is common in wireless sensor networks. Achieving the minimum possible data rate, however, is not always the optimal choice when the effects of packet loss on overall measurement error are considered. This paper presents a case study from the area of(More)
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