If you just want to try it out, the demo is live at: http://davehowcroft.com/files/examples/word-mcr.html
This exercise was inspired by the work of Zarieß et al. (2015). They presented a whole-document, sentence-by-sentence approach to mouse-contingent reading. While the approach presented here does not yet include mouse-position tracking, it does provide word- or phrase-level text views, allowing in principle for finer grained reading time measures.
If you decide to develop this idea further, please let me know—I'd love to use your code! An acknowledgement might also be nice, if this is actually helpful :)
Thanks to @VerbingNouns for creating the animated GIF shown above.
Now that I am at Heriot-Watt University I am working with Verena Rieser and several students to develop a useful implementation of this interface. Get in touch if you want to help validate this experimental paradigm!
Zarrieß, Sina, Sebastian Loth, and David Schlangen. 2015. "Reading Times Predict the Quality of Generated Text Above and Beyond Human Ratings". In Proceedings of the 15th European Workshop on Natural Language Generation (ENLG), pages 38–47, Brighton, September 2015. Published by the Association for Computational Linguistics.