Wearable devices will change the way we use and experience technology. Many challenges still need to be solved such as better integration with clothing, better battery lifetime and many questions regarding interaction. These devices can have very small displays or even no display at all. When this happens, common techniques such as keyboards and touch screens are not so useful anymore.
Today many wearables rely on a smartphone companion for internet connection and some advanced tasks, however many understand that decoupling from mobile devices is a necessary step to achieve the vision of a truly omnipresent and invisible technology. Connectivity is already on the way in devices like the Samsung S, which uses a mini-sim for direct 3G access. A good interaction technique would impact a lot the use of these devices. Apple has recognized that we need to come up with different ideas so it recently proposed using the watch crown as an interaction device.
The main problem is that we usually want to increase the expressiveness of input not to narrow it. For this reason along the years we have supplemented keyboards with mouses, tablets and touch screens. By making smaller devices we inadvertently tend to scale down the interaction possibilities too. Two exceptions to this are voice and gestural input: since they are not physically attached to the input target they can maintain their power regardless of the device size. Voice recognition, unfortunately, has some obvious disadvantages if you are in a noise environment or don't want to bother nearby fellows.
Together with Ayshwarya, I have been studying the possibility of developing a gesture-based text input technique as part of our work for a Natural User Interface class at Virginia Tech. We decided to go along a selection technique for letters instead of drawing/handwriting. We believe that selection has the potential of being much faster since you can create methods to choose a letter in constant time. In fact, with a few exceptions, most of the current input systems go in this way. Another trend is to use some kind of prediction or correction algorithm to minimize mistakes and effort during input.
For selection, we noticed that three main actions are required:
1-Highlight a specific letter
2-Select the letter
3-Finish the word
Touch based techniques implicitly highlight letters, since the user can tell from his hand position and tactile perception when no letter has been selected. Other input devices, however, may require an explicit designed disambiguation mechanism (such as a button) or use a technique that combines both highlighting and selection. Joysticks are a good example of the first group. They generally use a specific button to selected a highlighted item. On the other hand, Swype unifies the two actions: the drawing of the curve is used determine probable letters and then words. Another classic technique that combines highlighting and selection is the Dasher. In this technique the user continuously steer a cursor, which run over letters selecting them. Finally, the purpose of the last action is to enable the user to prematurely end the word input, based on suggestions from an autocomplete system.
Regarding the input device, our first idea was to use Myo. This would theoretically allow users to input information using gestures and hand poses without the support of a desktop or computer, something more close to the wearable ideal.
Myo works by analyzing signals captured from your arms in a process called electromyography. The signals are processed by a classifier that can distinguish 5 different hand poses. The armband also contains an IMU (gyroscope, accelerometer and magnetometer) that can be used to track the relative position to the ground and the acceleration of the arm.
Next steps involve generating some options for input mapping and some way of evaluating them.