Please use this identifier to cite or link to this item: http://repository.psa.edu.my/handle/123456789/3858
Full metadata record
DC FieldValueLanguage
dc.contributor.authorIlya Ismail-
dc.contributor.authorAbdul Rahim.NB-
dc.contributor.authorDin-
dc.contributor.authorMusa-
dc.date.accessioned2023-01-11T06:51:20Z-
dc.date.available2023-01-11T06:51:20Z-
dc.date.issued2022-
dc.identifier.urihttp://repository.psa.edu.my/handle/123456789/3858-
dc.description.abstractLearning norms are now implemented either online or offline at any level of learning institution, whereby students are required to demonstrate continuous progress and skills in a variety of subjects. The need for students to adapt learning in this hybrid way allows for the construction of depression, anxiety, and stress. Before this, the DASS-42 scale was used to measure the level of depression, anxiety, and stress. Yet in line with the IR4.0 era, a tool needs to be developed to enable faster and more efficient detection. This study aims to develop a device that can detect user stress levels across a touchpad using an Arduino module and subsequently play audio that can reduce student stress levels. The developed prototype will detect stress levels based on the level of blood supply to the skin. Based on Ohm’s Law which says that the voltage is directly proportional to the resistance, the value of the voltage will also increase as the resistance increases. Referring to this, it can be attributed that when students are in a state of stress, skin resistance will also increase. This situation increases the permeability of the skin and in turn its conductivity to electrical current. From the detection, the prototype Stress Meter can be used by students as a medium of self-assessment apart from using the DASS-42 self-report scale and facilitate in identifying and controlling the level of academic stress experienced by students. This can certainly improve the quality of life of a student.en_US
dc.language.isoenen_US
dc.publisherUNIT PENERBITAN Politeknik Sultan Salahuddin Abdul Aziz Shahen_US
dc.subjectDASS-42en_US
dc.subjectStress detectionen_US
dc.subjectSkin resistanceen_US
dc.subjectArduinoen_US
dc.titleThe Development of Skin Resistance Arduino-Based Module for Stress Monitoringen_US
dc.title.alternativeCiE-TVET 2022en_US
dc.typeArticleen_US
Appears in Collections:Conference Paper

Files in This Item:
File Description SizeFormat 
CIE TVET 5 2022.pdf1.44 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.