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A real-time fuzzy logic biofeedback controller for freestyle swimming body posture adjustment

Wearable body area networks (BANs) have been widely used in activity measurements for kinematic information collection. This paper presents the design and implementation of a wearable device used as a training tool in freestyle swimming. The device supplies a close-loop control mechanism via a fuzzy logic controller. Swimming posture data is collected quantitatively and audibly fed back to swimmers in real time through bone conductors. Two recreational swimmers were invited to participate in a series of experiments including 7 days of baseline capability test (no feedback), 7 days of feedback training, and 2 days of retention test. It was found that both swimmers could well adapt to the feedback instructions. A maximum of 7.62% of lap time improvement and 29.64% of trunk roll improvement were observed in FB training, and such pattern was maintained after feedback was removed. We conclude that real-time fuzzy logic feedback can be used to improve recreational swimmers performance.