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dc.contributor.authorMajidiRad, Amir Hossein
dc.contributor.authorManiar, Prasham
dc.contributor.authorYihun, Yimesker S.
dc.contributor.authorHe, Hongsheng
dc.date.accessioned2020-09-14T14:37:51Z
dc.date.available2020-09-14T14:37:51Z
dc.date.issued2020-04-21
dc.identifier.citationMajidiRad A., Maniar P., Yihun Y., He H. (2020) Human Factors to Develop a Safety Guard Model in Human-Robot Interaction. In: Larochelle P., McCarthy J. (eds) Proceedings of the 2020 USCToMM Symposium on Mechanical Systems and Robotics. USCToMM MSR 2020. Mechanisms and Machine Science, vol 83:pp 271-286. Springer, Cham.en_US
dc.identifier.isbn978-3-030-43928-6
dc.identifier.issn2211-0984
dc.identifier.urihttps://doi.org/10.1007/978-3-030-43929-3_24
dc.identifier.urihttps://soar.wichita.edu/handle/10057/19006
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractIn this research, a strategy to incorporate an assist-as-needed scheme into human-robot collaboration during an object co-lifting and manipulation task is developed. Surface Electromyography (sEMG) signals from the upper-arm muscles are collected and analyzed to quantify fatigue while the subjects are collaborating with a Universal Robot (UR5). Rated perceived fatigue (RPF) is then utilized to quantify fatigue levels based on personal perception of the subject using the intervals of 25%, 50%, 75% and 100%. This perceived information is correlated with the change in interaction load at the object-robot interface to quantify the modifying factor needed to stay in the optimal human-robot collaboration (HRC) condition.en_US
dc.language.isoen_USen_US
dc.publisherSpringeren_US
dc.relation.ispartofseriesMechanisms and Machine Science;v.83
dc.subjectFatigue levelen_US
dc.subjectHuman-robot collaborationen_US
dc.subjectManipulation tasken_US
dc.subjectModifying factorsen_US
dc.subjectPersonal perceptionen_US
dc.subjectRobot interfaceen_US
dc.subjectSafety guardsen_US
dc.subjectSurface electromyographyen_US
dc.titleHuman factors to develop a safety guard model in human-robot interactionen_US
dc.typeConference paperen_US
dc.rights.holder© 2020, Springer Nature Switzerland AGen_US


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