Encouraging Spontaneous Synchronisation with D-Jogger, an Adaptive Music Player That Aligns Movement and Music

Abstract

In this study we explore how music can entrain human walkers to synchronise to the musical beat without being instructed to do so. For this, we use an interactive music player, called D-Jogger, that senses the user's walking tempo and phase. D-Jogger aligns the music by manipulating the timing difference between beats and footfalls. Experiments are reported that led to the development and optimisation of four alignment strategies. The first strategy matched the music's tempo continuously to the runner's pace. The second strategy matched the music's tempo at the beginning of a song to the runner's pace, keeping the tempo constant for the remainder of the song. The third alignment starts a song in perfect phase synchrony and continues to adjust the tempo to match the runner's pace. The fourth and last strategy additionally adjusts the phase of the music so each beat matches a footfall. The first two strategies resulted in a minor increase of steps in phase synchrony with the main beat when compared to a random playlist, the last two strategies resulted in a strong increase in synchronised steps. These results may be explained in terms of phase-error correction mechanisms and motor prediction schemes. Finding the phase-lock is difficult due to fluctuations in the interaction, whereas strategies that automatically align the phase between movement and music solve the problem of finding the phase-locking. Moreover, the data show that once the phase-lock is found, alignment can be easily maintained, suggesting that less entrainment effort is needed to keep the phase-lock, than to find the phase-lock. The different alignment strategies of D-Jogger can be applied in different domains such as sports, physical rehabilitation and assistive technologies for movement performance.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 90 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.