Jump height tests are employed to measure the lower-limb muscle power of athletic and non-athletic populations. The most popular instruments for this purpose are jump mats and, more recently, smartphone apps, which compute jump height through manual annotation of video recordings to extract flight time. This study developed a non-invasive instrument that automatically extracts take-off and landing events from audio recordings of jump executions. An audio signal processing algorithm, specifically developed for this purpose, accurately detects and discriminates the landing and take-off events in real time and computes jump height accordingly. Its temporal resolution theoretically outperforms that of flight-time-based mats (typically 1000 Hz) and high-speed video rates from smartphones (typically 240 fps). A validation study was carried out by comparing 215 jump heights from 43 active athletes, measured simultaneously with the audio-based system and with of a validated, commercial jump mat. The audio-based system produced nearly identical jump heights than the criterion with low and proportional systematic bias and random errors. The developed audio-based system is a trustworthy instrument for accurately measuring jump height that can be readily automated as an app to facilitate its use both in laboratories and in the field.
Keywords: algorithm; audio; instrument; jump; measurement; sports; validation.