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Recommended biometric stress management system

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Date
2011
Author
Kaklauskas, Artūras
Zavadskas, Edmundas Kazimieras
Pruskus, Valdas
Vlasenko, Andrej
Bartkienė, Lina
Pališkienė, Rasa
Pečiūrė, Lina
Gerstein, V.
Dzemyda, Gintautas
Tamulevičius, Gintautas
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Abstract
The experiences of undergoing economic crises attest that the loss of employment prompts an outbreak of mental illnesses and suicides, increases the numbers of heart attacks and strokes and negatively affects other illnesses suffered by individuals under stress. Negative stress can devastate a person, cause depression, lower productivity on the job and the competitiveness of businesses and damage the quality of life. The Recommended Biometric Stress Management System, which the aforementioned authors of this article have developed, can assist in determining the level of negative stress and resolve the problem for lessening it. The system can help to manage current stressful situation and to minimise future stress by making the level of future need satisfaction more rational. In the first case, the system facilitates individuals to make a real-time assessment of their stress level and, after they fill in a stress management questionnaire, to get rational tips for the reduction of current stress based on the best global practice accumulated in the system. The multi-variant design and multiple criteria analysis methods are used for that purpose. The generation of recommendations and the selection of the most rational are based on criteria systems and on Maslow’s Hierarchy of Needs. Since this is an interdisciplinary area of research, psychologists, philosophers and experts in information management and decision-making theories and intelligent and biometric technologies participated in the development of this system. Over the course of this system’s development, the biometric technologies of information, intelligence and voice were integrated. The case study submitted in this article demonstrates this developed system.
Issue date (year)
2011
URI
https://etalpykla.vilniustech.lt/handle/123456789/129900
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  • Straipsniai Web of Science ir/ar Scopus referuojamuose leidiniuose / Articles in Web of Science and/or Scopus indexed sources [7946]

 

 

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