Karya
Judul/Title Mental stress detection via heart rate variability using machine learning
Penulis/Author Dr. Bimo Sunarfri Hantono, S.T., M.Eng. (1) ; Prof. Ir. Lukito Edi Nugroho, M.Sc., Ph.D. (2); Prof. Ir. Paulus Insap Santosa, M.Sc., Ph.D., IPU. (3)
Tanggal/Date 2020
Kata Kunci/Keyword
Abstrak/Abstract Mental stress is an undesirable condition for everyone. Increased stress can cause many problems, such as depression, heart attacks, and strokes. Psychophysiological conditions possible use as a reference to a person’s mental state of stress. The development of mobile device technology, along with the accompanying sensors, can be used to measure the psychophysiological condition of its users. Heart rate allows measured from the photoplethysmography signal utilizing a smartphone or smartwatch. The heart rate variability is currently one of the most studied methods for assessing mental stress. Our objective is to analyze stress levels on the subjects when performing tasks on the smartphone. This study involved 41 students as respondents. Their heart rate was recorded using a smartphone while they were doing the n-back tasks. The n-back task is one of the performance tasks used to measure working memory and working memory capacity. In this study, the n-back task was also used as a stressor. The heart rate dataset and n-back task results are then processed and analyzed using machine learning to determine stress levels. Compared with three other algorithms (neural network, discriminant analysis, and naïve Bayes), the k-nearest neighbor algorithm is most appropriate to use in the classification of time and frequency domain analysis.
Rumpun Ilmu Teknologi Informasi
Bahasa Asli/Original Language English
Level Internasional
Status
Dokumen Karya
No Judul Tipe Dokumen Aksi
102 Mental stress detection via heart rate variability using machine learning.pdf[PAK] Full Dokumen
202 Similarity Mental stress detection via heart rate variability using machine learning.pdf[PAK] Cek Similarity
3Mental Stress Detection via Heart Rate Variability using Machine Learning.pdf[PAK] Full Dokumen
4PEER REVIEW_LUKITO EDI N T1.pdf[PAK] Peer Review
5IJEEI.pdf[PAK] Bukti Korespondensi Penulis