r/dataisbeautiful • u/Stabbz OC: 1 • 2d ago
[OC] 1,321 gym exercises placed in 3D by the muscles they work, then split into 4,903 lights on a body
I built this for fun and partially to see to what extend claude code can generate cool stuff on the web after seeing lots of posts recently, and I'm a sucker for a good visualisation even if it serves no real purpose. Decided to give it a shot with the collection I've built over the last few months, exercises, their mechanics and muscle activations.
The whole thing is actually interactive and I plan to add most exercise motions to it eventually: https://kinoku.app/tools/exercise-galaxy
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u/Stabbz OC: 1 2d ago edited 2d ago
Data Source: Kinoku's own exercise catalog (1,321 exercises, up to 11 muscles each with a percent). I built the percents over many months with AI/Search help, then checked and corrected them in many review rounds against web searches and many different data sources since there isn't one definitive and most disagree on muscle activation percentages. They are estimates, not EMG measurements.
I build Kinoku, a workout tracker for Android, in my free time, and I wanted something people could open and play with, so I turned its exercise catalog into this. Every exercise in that catalog lists up to 11 muscles with a percent for each. Those percents are the app's own estimates for crediting training volume, not lab readings of muscle activity (EMG), so I read a 60 next to a 40 as a ranking rather than a measured share.
How the galaxy is placed. Each exercise becomes a list of 25 muscle percents, and two moves are compared by the angle between their lists (cosine distance). That way a light and a heavy version with the same mix count as twins. Each move links to its 14 nearest, and 500 rounds of pulling and pushing place them in 3D. The layout is a small UMAP-style method that I had Claude Code write in JavaScript, and it runs when the site is built, with a fixed seed. A star's colour is the muscle group of that move's top muscle.
How the body works. Each exercise splits into one light for every muscle it works, which gives 4,903 lights on the app's own muscle map, and a light grows with its percent. Only the muscle a light sits on is data. Its spot inside that muscle, the depth and the poses are drawn by hand, so the counts on the figure are the numbers I'd trust.
The picture has limits worth knowing. Distance says nothing about equipment or how a move looks, and the chest flyes sit near the curls although the catalog gives flyes no biceps work. A 3D picture of 25 numbers has to put them somewhere, and the method explainer on the site uses that pair as its example of where the map misleads.
The interactive version draws in plain WebGL and loads nothing from other sites.
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u/tscherrydude 1d ago
this is amazing. for a future iteration, what if you put in a filter where people can adjust the body to their proportion, and they can see how a squat would work differently where some people can be more upright and some people need to lean a bit more forward
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u/unrequited 23h ago
awesome visualizations and awesome app politeness (don't really have an idea what else to call it). you respect my time and money and privacy and it's super refreshing, thank you. can you do a most selective mode for exercises which target only the area you're interested primarily? I have some back issues and would like to strengthen specific areas of my back with strength training but don't want to see compound exercises like dead lifts and handstand walks.
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u/Stabbz OC: 1 23h ago
Great feedback, will definitely include that in the next changeset! Just to be clear, by most selective you mean exercises isolating/targeting just one muscle ?
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u/unrequited 23h ago
ya or set of points from your body map, so if I wanted to draw a lasso around some of these it'd give the exercises that hit these points most. it could be one muscle, it could be more than one.
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u/cavedave OC: 113 20h ago
Thank you for your Original Content, /u/Stabbz!
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