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We have developed a new method for detecting microsaccades in eye-movement data. The impetus was the review of the literature on microsaccades presented in this paper, which revealed (1) large changes in the size and speed of reported microsaccades over the last 70 years and (2) references to monocular microsaccades, which have recently been shown to be artefacts of analysis methods (Nyström et al, 2017; Fang et al, 2018). The changes in reported microsaccade characteristics, such as size and speed, must be due to experimental factors, such as methods of recording and analysis, and different levels of experience of the participants in the task: They cannot represent a change in the fundamental characteristics of microsaccades. In this paper we present a review of reported microsaccade properties between the 1940s and today and we determine the range within which certain physical parameters of microsaccades are thought to occur. These parameters drive our new microsaccade detection method. We have validated this method on two datasets of binocular eye-movements recorded using video-based systems: one from within our lab, and one from Nyström et al, 2017. We have additionally applied our method to eye-movement data collected using an adaptive optics scanning laser ophthalmoscope (AOSLO), to show its adaptability to a fundamentally different method of data capture. This confirmed that the microsaccade detection method produces microsaccade detection rates within expected limits across very different methods of recording. Our new microsaccade detection method is easy to implement and intuitive to understand, and affords researchers flexibility in adjusting it to their experimental set-up.

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