Engram keyboard layout optimization study just published in peer-reviewed journal (IJHCI)

[binarybottle]

Hi — I'm the author of the Engram layout. After years of work, my open-access paper has just been published in the peer-reviewed International Journal of Human-Computer Interaction: "Optimizing comfortable keyboard layouts using human typing preferences and language-dependent n-grams: the Engram Study" (http://dx.doi.org/10.1080/10447318.2026.2665409) describing a new approach to optimizing keyboard layouts in different languages. Instead of assuming speed equals comfort (the paper shows speed explains only ~5.7% of preference variance, a poor proxy), I crowdsourced typing preference data from >500 people and used it to empirically derive ergonomics scoring criteria such as row separation, finger sequence, lateral stretch, and key preferences. I also validated which of Dvorak's original 1936 principles actually correlate with typing speed (spoiler: only 4 of 7 do). These preferences drove multi-objective optimization over English and Spanish n-gram frequencies to produce new Engram-en and Engram-es layouts (https://engram-layouts.xyz/). All data, code, and layouts are fully open source. Please check out the article (and the Supplementary Material for my Engram Halloween costume!). Happy to answer questions.

Cheers,
Arno
arnoklein.info

[precondition]

Oh interesting. I just so happened to fall down the rabbit hole of keyboard layout optimizers recently. As a matter of fact, I'm currently destroying all my prior Colemak muscle memory to learn a very unconventional keyboard layout optimized based on a corpus of 5M logged keystrokes (so I actually have data on non-printable keys like arrow keys and modifiers).

[binarybottle]

All the best!
I used “Process 136M keystrokes” Python code to extract bigram typing speed data from the 136 Million Keystrokes Dataset:

• GitHub: https://github.com/binarybottle/process_136M_keystrokes
• OSF: https://osf.io/6t9dn/ (DOI: 10.17605/OSF.IO/6T9DN)