2026-07-12T23:15:41Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/102732025-03-04T11:43:51Zcom_10259_5841com_10259_5086com_10259_2604col_10259_5842

00925njm 22002777a 4500 dc Sáez García, Javier author Sáiz Manzanares, María Consuelo author Marticorena Sánchez, Raúl author 2024 The use of eye tracking technology, together with other physiological measurements such as psychogalvanic skin response (GSR) and electroencephalographic (EEG) recordings, provides researchers with information about users’ physiological behavioural responses during their learning process in different types of tasks. These devices produce a large volume of data. However, in order to analyse these records, researchers have to process and analyse them using complex statistical and/or machine learning techniques (supervised or unsupervised) that are usually not incorporated into the devices. The objectives of this study were (1) to propose a procedure for processing the extracted data; (2) to address the potential technical challenges and difficulties in processing logs in integrated multichannel technology; and (3) to offer solutions for automating data processing and analysis. A Notebook in Jupyter is proposed with the steps for importing and processing data, as well as for using supervised and unsupervised machine learning algorithms. http://hdl.handle.net/10259/10273 10.3390/computers13110289 2073-431X Eye tracking Galvanic skin response Behavioural monitoring Learning process Data processing A Proposed Method of Automating Data Processing for Analysing Data Produced from Eye Tracking and Galvanic Skin Response