Touch-Typing On Fingertips? Prototype Says It Could Work

The fingertips are covered in touch sensors, each intended to be tapped by the thumbtip of the same hand.

Touch-typing with thumbs on a mobile phone keyboard is a pretty familiar way to input text, and that is part of what led to BiTipText, a method of allowing bimanual text input using fingertips. The idea is to treat the first segments of the index fingers as halves of a tiny keyboard, whose small imaginary keys are tapped with the thumbs. The prototype shown here was created to see how well the concept could work.

The prototype hardware uses touch sensors that can detect tap position with a high degree of accuracy, but the software side is where the real magic happens. Instead of hardcoding a QWERTY layout and training people to use it, the team instead ran tests to understand users’ natural expectations of which keys should be on which finger, and how exactly they should be laid out. This data led to an optimized layout, and when combined with predictive features, test participants could achieve an average text entry speed of 23.4 words per minute.

Judging by the prototype hardware, it’s understandable if one thinks the idea of fingertip keyboards may be a bit ahead of its time. But considering the increasingly “always on, always with you” nature of personal technology, the goal of the project was more about investigating ways for users to provide input in fast and subtle ways. It seems that the idea has some merit in principle. The project’s paper can be viewed online, and the video demonstration is embedded below.

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Meat Thermometer Using Predictive Filtering

meatthermoafteradjustment

The guys over at NerdKits put together a really informative video on a meat thermometer using predictive filtering which is viewable below. The video, supplemental text, and code is available on their website. The thermometer is constructed of a LM34 temperature sensor attached to a piece of 12 gauge solid copper wire. The thermometer signal is processed on an ATmega168 microcontroller and visualized using the pygame library for python. The real gem in this project is their excellent explanation of predictive filtering, which could easily be utilized for a large number of projects.

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