Аннотация:The processing of eye-tracking signals could berelevant in multiple fields. The report presents a description ofpilot software for eye-tracking analysis based on python libraries.The outlines the various applications of the software, including itsprocessing of input data of eye-tracking studies, variety ofvisualization tools, as well as features evaluation for assessment ofeye-tracking signals. Overview of the basic pipeline was presented,which includes data calibration, demonstration of keyvisualizations graphs as well as features extraction in table format.Furthermore, the software was used to process data of pilot studyinvolving healthy subjects and patients after a hemispheric stroke.Research has shown that when comparing target hit statistics, aswell comparing as extracted data from static and dynamic tests fora group of healthy subjects and patients, the parameters aresignificantly different for the two groups, in particular amount offixation events and misses of target is lower for healthy subjects,while successful hit of target is higher. Based on the extracted data,it can be noted that for the observed group of data, simple statisticsof hitting the target, using the angular velocity algorithm to divideinto fixations and saccades may be enough to divide the subjectsinto healthy and patients. Presented results revealed multipleinformative features to discriminate subjects from differentgroups. Future development of the presented software includesincrease of the extracted features to make it possible not only inbinary classification but also for a multi-class tasks to distinguishpatients with different pathologies.