"Can I Annoy you into Modifying your Running Behaviour?": Investigating the Validity of using Drone Noises to Modify Running Motor Behaviour

We investigate drone noise as a novel auditory concurrent biofeedback to “annoy” runners into increasing and then decreasing stride length by 10%. Our exploratory work validates drone noise by comparing it to a filtered less annoying “pure tone” condition, both played alongside runners’ preferred music, to signal the magnitude (noise intensity) and direction (spectral characteristics) of stride adjustments. Seated experiments revealed most participants could distinguish noise intensity levels (correlation=0.72) and interpret adjustment directions (kappa > 0.6) indicated in both noise conditions. Similarly, during treadmill running, this transferred successfully, with most participants modifying stride length by ± 10% (increase-drone: 109% ± 7%, pure: 110% ± 9.4%; decrease-drone: 101% ± 9%, pure: 96% ± 9.8%). These results demonstrate how drone-generated auditory feedback, designed using movement error sonification and reinforcement learning principles, can modify motor behavior in real-time. Post-run measures and interviews about runners’ experience informed design considerations for similar auditory biofeedback systems for running.