Real-Time Tracking and Display of Human Limb Segment Motion Using Sourceless Sensors

Tracking and display of human limb segment motions has been the topic of much research and development over many years for purposes as varied as basic human physiological studies, physical rehabilitation, sports training, and the construction of anthropomorphic robots. More recently, a new impetus has been given to such work by the desire to produce a whole body human/computer interface system, which encumbers the wearer to a minimum degree and operates over long distances. The input portion of such an interface can be derived by appropriate processing of signals from a nine-axis sensor package consisting of a three-axis angular rate sensor, a three-axis magnetometer, and a three-axis linear accelerometer. In this paper, such a sensor system is called a MARG (Magnetic field, Angular Rate, and Gravity) sensor. Recent advances in micromachining (MEMS) technology, and magnetometer miniaturization, have allowed the development of MARG sensors of very small size, suitable for attachment to individual human limb segments. At the same time, advances in wearable computers and wireless data communication techniques make it feasible to begin the development of a practical full body tracking system using sourceless MARG sensors. This paper focuses on data processing algorithms for MARG sensors. Since human limb segments are capable of arbitrary motion, Euler angles do not provide an appropriate means for specifying orientation. Instead, quaternions are used for this purpose. Since a quaternion is a four-dimensional vector, and a MARG sensor produces nine signals, this data processing problem is “overspecified”. This fact can be used to discriminate against sensor noise and to reduce the effects of linear acceleration on measurement of the gravity vector by accelerometers. Detailed computer simulation studies and the results of preliminary experiments with a prototype body tracking system confirm the effectiveness of the quaternion body-tracking filter.