Main Article Content
Emotions influence individual behavior and there is no emotional experience that has a stronger influence than stress. Prolonged stress has a direct negative influence on physical and emotional conditions. For that reason, it is important to know a person's mental stress state, so that further action can be taken later, so as not to have a serious impact on physical and mental health. In this study, the photoplethysmograph (PPG) approach is used to recognize mental stress conditions based on Heart Rate Variability (HRV) frequency domain analysis. In this study stress was identified by SVM classifier using LF, HF and LF / HF Ratio from HRV frequency domain analysis. The LF results were increased in mild stress conditions, HF increased in conditions of mild stress and medium stress and the LF / HF Ratio slowly increased from mild stress to severe stress. The training data obtained 80 data with 95% mild stress accuracy from 19 data, medium stress accuracy 96% from 49 data and 99% severe stress accuracy with 12 data.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Please find the rights and licenses in the Journal of Information Technology and Computer Engineering (JITCE).
The non-commercial use of the article will be governed by the Creative Commons Attribution license as currently displayed on Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
2. Author(s)’ Warranties
The author(s) warrants that the article is original, written by stated author(s), has not been published before, contains no unlawful statements, does not infringe the rights of others, is subject to copyright that is vested exclusively in the author and free of any third party rights, and that any necessary permissions to quote from other sources have been obtained by the author(s).
3. User Rights
JITCE adopts the spirit of open access and open science, which disseminates articles published as free as possible under the Creative Commons license. JITCE permits users to copy, distribute, display, and perform the work for non-commercial purposes only. Users will also need to attribute authors and JITCE on distributing works in the journal.
4. Rights of Authors
Authors retain the following rights:
- Copyright, and other proprietary rights relating to the article, such as patent rights,
- the right to use the substance of the article in future own works, including lectures and books,
- the right to reproduce the article for own purposes,
- the right to self-archive the article.
- the right to enter into separate, additional contractual arrangements for the non-exclusive distribution of the article's published version (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal (Journal of Information Technology and Computer Engineering).
If the article was jointly prepared by other authors; upon submitting the article, the author is agreed on this form and warrants that he/she has been authorized by all co-authors on their behalf, and agrees to inform his/her co-authors. JITCE will be freed on any disputes that will occur regarding this issue.
By submitting the articles, the authors agreed that no fees are payable from JITCE.
JITCE will publish the article (or have it published) in the journal if the article’s editorial process is successfully completed and JITCE or its sublicensee has become obligated to have the article published. JITCE may adjust the article to a style of punctuation, spelling, capitalization, referencing and usage that it deems appropriate. The author acknowledges that the article may be published so that it will be publicly accessible and such access will be free of charge for the readers.
 Anonim [Online]. Available: http://digilib.unila.ac.id/2341/10/Bab%202.pdf [Accessed 19 September 2018].
 J.Taelman, "Influence of Mental Stress on Heart Rate and Heart Rate Variability," in IFMBE, Berlin Heidelberg, 2008.
 R. J.Choi, "Using Heart Rate Monitors to Detect Mental Stress," in IEEE Computer Society, United States, 2009.
 N. P. Novani, L. Arief, R. Anjasmara and A. S. Prihatmanto, "Heart Rate Variability Frequency Domain for Detection of Mental Stress Using Support Vector Machine," 2018 International Conference on Information Technology Systems and Innovation (ICITSI), Bandung - Padang, Indonesia, 2018, pp. 520-525.
 M. R. Saputra, "Pemantauan Parameter Fisiologis Pada Pasien Koma," in Fakultas Teknologi Informasi, Universitas Andalas, 2018.
 R. Z. Ikhlas, "Sistem Monitoring Detak Jantung untuk Peringatan Dini dalam Mengantisipasi Kelelahan pada Aktifitas Olahraga Lari," in Fakultas Teknologi Informasi, Universitas Andalas, 2018.
 D. Yolanda, "Mengukur Tingkat Stres Menggunakan Galvanic Skin Respons dengan Metode Jaringan Syaraf Tiruan Berbasis Arduino Uno," in Fakultas Teknologi Informasi, Universitas Andalas, 2014.
 A. Nofrianto, "Identifikasi Tingkat Stres Manusia Menggunakan Metode FUzzy Logic Berbasis Internet of Things (IoT)," in Fakultas Teknologi Informasi, Universitas Andalas, 2016.
 H.Mansor, "Stress Recognition Using Photoplathysmograph Signal," in Indonesian Journal of Electrical Engineer and Computer Science, 2017.
 S. P.M.Mohan, V.Nagarajan, "Stress Measurement from Wearable Photoplethysmographic Sensor Using Heart Rate Variability Data," in International Conference on Communication and Signal Processing , India,
 L.Vanitha, "Hierarchical SVM to Detect Mental Stress in Human Beings Using Heart Rate Variability," in 2nd International Conference on Devices, Circuits and Systems (ICDCS), 2014.
 S.Cohen, "Perceived Stress Scale in a Probability Sample of the United States," Newbury Park: CA : Sage, 1988.