This thesis explores the complex relationship between facial electromyography (fEMG), a technique that measures muscle activity by detecting and amplifying the tiny electrical impulses generated by the muscle fibres of the zygomaticus major muscle, and the self-assessment of the subject.
Facial electromyography is used in many fields for various purposes. It provides a valuable reference in clinical diagnostics and biomedical techniques, where it is used to study emotions and their expressions under the influence of various stimuli. Facial electromyography is also a key technique used in the study of human speech. In recent times, it has been widely used for commercial or marketing purposes and video game development.
In the thesis, facial electromyography will be used as a tool to measure emotional responses to a stimulus by detecting micro or subtle expressions that last only a fraction of a second and are more difficult to detect with the naked eye.
To achieve this, we have reviewed many studies on the use and performance of facial electromyography, as well as studies related to the very beginnings of facial electromyography and subsequent advances in the field. We chose an appropriate type of stimulus that evoked positive emotions during the measurement of the activation of the zygomaticus major muscle. We gained knowledge of the operation of the Biopac MP150 multiparametric physiology meter and the EMG100C electromyogram amplifier, as well as the AcqKnowledge software. Finally, we interpreted all the findings, captured signals, cues and observations.
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