Please use this identifier to cite or link to this item:
https://scholarhub.balamand.edu.lb/handle/uob/4125
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Mezannar, Nay | en_US |
dc.contributor.author | Chehade, Charbel | en_US |
dc.date.accessioned | 2020-12-23T14:40:28Z | - |
dc.date.available | 2020-12-23T14:40:28Z | - |
dc.date.issued | 2019 | - |
dc.identifier.uri | https://scholarhub.balamand.edu.lb/handle/uob/4125 | - |
dc.description | Includes bibliographical references (p. 50-51). | en_US |
dc.description | Supervised by Dr. Nay Mezannar. | en_US |
dc.description.abstract | Nowadays machines have reached a high level of reliability. The main failures in human-machine interaction are rising from the human factors side. Studies showed that emotions and sensory perception are strongly correlated: they can affect how a user perceives the senses. Emotions can hence alter the situation awareness of the user affecting the decision-making process and thus leading to fatalities in safety-critical fields. Being able to monitor and enhance the situation awareness in critical tasks, will influence the decisionmaking process. This paper presents the results of innovative research combining emotions measured through electroencephalography (EEG) with the concept of chromotherapy. Emotions could be identified through brain scans while monitoring brain activity. Their affiliation with colors is demonstrated in previous studies (Nijdam, 2010). In addition, these measured parameters can be successfully correlated to the different levels of situation awareness of the user. Being able to adjust the emotions of the user based on chromotherapy will improve the situation awareness, hence the decision-making process. Based on the Mixed-group experimental design, users from the same age and demography undertook a puzzle-solving task. Using a non-invasive neuroheadset, the emotions were measured, and the dependent variables recorded: level accomplished during a fixed interval of time, and result. The experimental two groups had the room wall colors varying (blue for group 1 and red for group 2). By retrieving the raw data recorded for both groups from the neuroheadset, results of group 1 tested in the blue room, showed an optimization of the users alertness and situation awareness resulting in a more efficient decision-making process. This improvement was manifested by the fact that the majority members of group 1 (subjected to blue lighting) scored higher levels of that of members of group 2 (subjected to red lighting) for an identical interval of time. | en_US |
dc.description.statementofresponsibility | by Charbel Chehade | en_US |
dc.format.extent | vi, 54 p. :ill., tables ;30 cm | en_US |
dc.language.iso | eng | en_US |
dc.rights | This object is protected by copyright, and is made available here for research and educational purposes. Permission to reuse, publish, or reproduce the object beyond the personal and educational use exceptions must be obtained from the copyright holder | en_US |
dc.subject.lcsh | Electroencephalography | en_US |
dc.subject.lcsh | Emotions | en_US |
dc.subject.lcsh | Pattern recognition systems | en_US |
dc.title | Emotions influenced by colors and its impact on the decision-making process | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Mechanical Engineering | en_US |
dc.contributor.faculty | Faculty of Engineering | en_US |
dc.contributor.institution | University of Balamand | en_US |
dc.date.catalogued | 2019-07-01 | - |
dc.description.degree | MS in Mechanical Engineering | en_US |
dc.description.status | Published | en_US |
dc.identifier.ezproxyURL | http://ezsecureaccess.balamand.edu.lb/login?url=http://olib.balamand.edu.lb/projects_and_theses/GP-Mec-196.pdf | en_US |
dc.identifier.OlibID | 192576 | - |
dc.provenance.recordsource | Olib | en_US |
Appears in Collections: | UOB Theses and Projects |
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