Usability evaluations are important to the development of augmented reality systems. However, conducting large-scale longitudinal studies remains challenging because of the lack of inexpensive but appropriate methods. In response, we propose a method for implicitly estimating usability ratings based on readily available sensor logs. To demonstrate our idea, we explored the use of features of accelerometer data in estimating usability ratings in an annotation task. Results show that our implicit method corresponds with explicit usability ratings at 79% and 84%. These results should be investigated further in other use cases, with other sensor logs.