In this paper, we provide the design and implementation of UOIT, a text entry method optimized for smartwatches. UOIT uses only one page where a user can see and tap directly for entry without any additional actions, such as zoom-in/zoom-out and swipes, which are required in the existing entry methods. To fully utilize the constrained screen space and to address the “fat finger” problem, we use a technique called “drawing-like typing”, which reduces the 26 small alphabetic keys into 13 large keys with a dual input property. To evaluate the performance of UOIT, we conducted two user studies while varying the learning period. In the short-term experiments (i.e., two days), we observed a fast learning curve of users when using the UOIT keyboard. Moreover, with the long-term experiments (i.e., a month), we show that users can type as fast as QWERTY keyboard but with much less errors. Moreover, UOIT outperforms the state-of-the-art keyboard in both speed and error rate.

Many techniques have been proposed for reducing errors during text input on touchscreens. However, the majority of these techniques suffer from the same limitation, i.e., the keyboard keys are overcrowded on a small screen, resulting in high error rates and slow text inputs. To address this situation and resolve the problems associated with overcrowdedness, we introduce a new text-entry method called the “UOIT keyboard.” The idea behind the UOIT keyboard is to compose letters using “drawing-like typing” on the UOIT keyboard, which has 13 large keys that replace the 26 small keys that exist in the QWERTY keyboard. We describe the design, keys, and mechanism of the UOIT keyboard. A 24-participant user study was conducted to evaluate the speed and accuracy of the proposed entry method as compared with the QWERTY and multitap entry methods. As part of the evaluation, a questionnaire was used to collect participants' preferences. The UOIT keyboard has a mean entry speed of 11.3 words/min. The UOIT keyboard significantly reduces the typing errors with 3.8% total error rate comparing with 11.2% and 16.3% for QWERTY and multitap entry methods, respectively.