Real-time high productivity inducing application: Building a music provision system for college students based on stress levels
Date of Publication
2013
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Computer Science
Subject Categories
Computer Sciences
College
College of Computer Studies
Department/Unit
Computer Science
Thesis Adviser
Rhia Trogo
Defense Panel Chair
Ethel Ong
Defense Panel Member
Rafael Cabredo
Arturo Caronongan
Abstract/Summary
This project aims to develop the Real-time High productivity Inducing Application, a desktop application that automatically provides music that induces the optimal level of stress in relation to productivity. It focuses on implementation models that interprets and identities the optimal level of stress based on skin conductance. Productivity is labeled low, medium, and high according to the amount of stress the user is feeling. A graphical user interface was also designed to aid the user is feeling. A graphical user interface was also designed to aid the user is feeling. A graphical user interface was also designed to aid the user visually and make the system simple to use and easy to navigate. The system underwent testing to ensure quality and effectiveness of the system. Results have shown that the system was able to induce the optimal level of stress. This project also aims to build a general model derived from an existing stress model which performs at an accuracy of 64.2549% for controlled set-up and 65.4904% for naturalistic setup, that detects stress using only skin conductance gathered from Affectiva Q Sensor. There were 3 different experimental setups conducted: controlled naturalistic and naturalistic with music. The signals gathered were processed using different methods such as of normalization, window-based segmentation and feature extraction. Two pairs of models were built and implemented in the system. The first pair of model built was for the controlled setup with 81.7058% and 56.5405% accuracy for participants with > 8 hours of sleep and < 8 hours of sleep respectively relative to the existing stress model. The second pair of models built was for naturalistic setup with music performing at a relative accuracy of 72.7129% and 84.5620% for participants experiencing high and low stress respectively to the existing stress model.
Abstract Format
html
Language
English
Format
Accession Number
TU18549
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Physical Description
1v. various foliations : illustrations (some colored) ; 28 cm.
Keywords
College students--Mental health; Stress management; Music therapy; Stress tolerance (Psychology)
Recommended Citation
Escalona, M., Laxamana, R., Pagtakhan, K., & Tighe, E. (2013). Real-time high productivity inducing application: Building a music provision system for college students based on stress levels. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/10700
Embargo Period
1-8-2022