The dynamic AI-powered playlist matching with your heartbeat

If you watched We Are Your Friends, you remember the scene where Zac Efron explains where biology and music converge. Although it was just an average movie, it got me thinking. What if they were right and you, as a DJ, can completely control the crowd by simple bpm adjustments? That’s when I started digging.

  1. Introduction

Maybe you noticed that you love to chill, slow music when you lay in your deckchair on a Sunday morning. On the contrary, you enjoy faster dance music in a local bar on a Friday night. So, there must be some connection between the music tempo, heartbeat, and our mood. Data from Spotify reported the average beat of top 10,000 songs to range between 120 and 130 bpm

[1] (the above-mentioned movie also mentioned the 128 bpm to be the “golden” tempo).

  1. The idea

What if we developed a tool/plug-in for Deezer, Spotify, and other music apps that would track our heartbeat recorded from the smartwatch, bracelet, or any other similar device and adjust the playlist/beat to match our current heartbeat? When you start running, it starts with slower tempo music of your choice (new random songs, favorites, etc), gradually speeding up with your pace increasing. If you slow down due to pain in the spleen, it would also slow down and imperceptibly cross-fade to a slower beat.

  1. Benefits

Combining the existing AI tools to track your favorite genres and artists with physiological signs of current body state, we could develop a strong algorithm able to read and learn from your mood, habits, and daily routines, and deliver the perfect song any time. There would be no need to stop your workout due to a high bpm playlist being interrupted by a slow love ballad.

  1. Implementation

It is not very easy to develop and implement this tool. The easier part is to add the feature of real-time heart rate data tracking to any music app. The harder part would be to dig the beats of all the available songs, check for the beat changes, bpm patterns, and display them as a novel parameter. The toughest part would be to match and combine the developed parameter with the user favorites and new discoveries in real-time.

What do you think?

What other physiological metrics could be used to find a perfect song for the moment?



I should watch friends again. The concept is looking good and would fit to the music apps. Maybe it could work together with the smart-watch to get more data to find the perfect song


Thank you! New ideas and perspectives are welcome. Yes, you should watch FRIENDS again


At first, I like the idea. The problems you mentioned as hardest or toughest part is not that hard = because it’s only data. And a lot of streaming apps have collected them over the years. We can do it

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“Finally, words cannot speak of music; they cannot elucidate nor illuminate. Both sounds enter through the ears, but only music travels throughout and animates the whole body.” - David Bowie
I did some research about that and fully support your idea!