Real-time accurate human posture tracking in unconstrained environments provides an enabling technology for physicians and other care providers to monitor the movements of their patients in real-life situations. Constructing a posture tracking system with the form factor suitable for human wear requires the development of miniature units that can be attached to the limb segments of interest in an unobtrusive way. Simultaneously, fast algorithms that can produce real-time posture estimates at sufficient rates are needed. In this paper, we focus on the development of efficient and accurate algorithms that compute the human posture information from low-cost miniature inertial and magnetic sensors. We present a new technique that computes posture estimates from the sensor data 23.8 times faster than the most efficient previously proposed technique, and simultaneously increases the accuracy of the estimates.
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Gallagher et al. (2005) studied this question.
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