  In recent decades, running has become an increasingly popular pastime
activity due to its accessibility, ease of practice, and anticipated health
benefits. However, the risk of running-related injuries is substantial for
runners of different experience levels. Several common forms of injuries result
from overuse -- extending beyond the recommended running time and intensity.
Recently, audio-based tracking has emerged as yet another modality for
monitoring running behaviour and performance, with previous studies largely
concentrating on predicting runner fatigue. In this work, we investigate
audio-based step count estimation during outdoor running, achieving a mean
absolute error of 1.098 in window-based step-count differences and a Pearson
correlation coefficient of 0.479 when predicting the number of steps in a
5-second window of audio. Our work thus showcases the feasibility of
audio-based monitoring for estimating important physiological variables and
lays the foundations for further utilising audio sensors for a more thorough
characterisation of runner behaviour.
