Abstract
Several projects have tracked the movement of swimmers in pools using body worn inertial measurement units. In swimming, inertial sensing is subject to large amounts of drift and accumulated error which can only be corrected for after a complete length has been swum. In this article, we present a new method for tracking swimmers by detecting variations in the magnetic field caused by the structure of pools. This method is complementary to inertial positioning, as it allows the direct extraction of position without requiring post-processing, and unlike inertial sensing which loses accuracy over time, magnetic field tracking becomes increasingly accurate towards the end of a length.
Highlights
Technology is commonplace in elite swim training and research, most commonly video capture, and body mounted inertial measurement units (IMUs) [1]–[5], tethering of swimmers to speed detector reels [6] and pools with embedded networks of sensors [7], [8]
IMUs have a major accessibility advantage in two respects, firstly, they are unobtrusive and can be used in public pool sessions, and secondly, inertial sensing suitable for sports analysis is widely available in the form of consumer smartphones [12]
The algorithm used is a dynamic programming algorithm in which at each timestep the recent history of sensed magnetic field strength is compared against areas of the magnetic signature which it plausibly could represent, with plausibility defined by the output of previous time steps and constraints on how fast swimmers can realistically move
Summary
Technology is commonplace in elite swim training and research, most commonly video capture, and body mounted inertial measurement units (IMUs) [1]–[5], tethering of swimmers to speed detector reels [6] and pools with embedded networks of sensors [7], [8]. A few IMU based systems have demonstrated real-time feedback to swimmers of body rotation and arm movement [5], [9], or stroke rate [10]. We believe that a combination of this tracking with inertial sensing may provide the basis for a wide range of swimmer aware real-time feedback systems. The tracking system is evaluated with reference to position measurements taken from synchronised video recordings of swimmers, to demonstrate that it provides a drift free position measurement which is possible to calculate in real time
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