Rodyti trumpą aprašą

dc.contributor.authorMažeika, Dalius
dc.contributor.authorDunovski, Kšyštof
dc.date.accessioned2023-09-18T20:16:40Z
dc.date.available2023-09-18T20:16:40Z
dc.date.issued2019
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/148491
dc.description.abstractMost of the computer users suffer from mental and physical fatigue. A tired person can make mistakes and violate sensitive data integrity or cause other problems in IT systems. Thus it is vital to keep the exhaustion of the user in check. In this research, we address the problem of identifying user fatigue level through the analysis of input behavior from the mouse and keyboard. Firstly, a specialized tool was developed, which was used to gather data about the keystroke dynamics and mouse motion characteristics. The following data were acquired from the keyboard: up-down, down-down, and holding time of the keys as well as keystroke frequency. Motion speed and hold time of the mouse key were gathered from the mouse. After the tool was created, a static text, as well as a combination of mouse inputs, were given for the volunteered users to make inputs. Corresponding data was gathered and labeled according to the user fatigue level. Neural network, K-Means as well as classification and regression tree algorithms were used to build user fatigue prediction models. Investigation on different datasets was performed, and the correlation between results obtained from keyboard and mouse datasets was analyzed. Analysis of the resulting accuracies of the models was performed as well, and corresponding conclusions about the capability of predicting user fatigue based on input behavior were made.eng
dc.formatPDF
dc.format.extentp. 53
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.source.urihttps://www.mii.lt/datamss/files/DAMSS_2019.pdf
dc.source.urihttp://www.mii.vu.lt/DAMSS
dc.titleInvestigation of user fatigue based on input behavior
dc.typeKonferencijos pranešimo santrauka / Conference presentation abstract
dcterms.references0
dc.type.pubtypeT2 - Konferencijos pranešimo tezės / Conference presentation abstract
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.facultyFundamentinių mokslų fakultetas / Faculty of Fundamental Sciences
dc.contributor.facultyInformacinių technologijų ir sistemų centras / The Centre of Information Technology and Systems
dc.contributor.departmentProgramavimo skyrius / Programming Centre
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics engineering
dc.subject.vgtuprioritizedfieldsIK0303 - Dirbtinio intelekto ir sprendimų priėmimo sistemos / Artificial intelligence and decision support systems
dc.subject.ltspecializationsL106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies
dc.subject.enfatigue measurement
dc.subject.ensupervised data mining
dc.subject.enclassification
dcterms.sourcetitle11th international workshop on data analysis methods for software systems (DAMSS 2019), Druskininkai, Lithuania, November 28-30, 2019 / Lithuanian Computer Society, Vilnius University Institute of Data Science and Digital Technologies, Lithuanian Academy of Sciences
dc.publisher.nameVilnius University
dc.publisher.cityVilnius
dc.identifier.doi10.15388/damss.11.2019
dc.identifier.elaba45282625


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