TY - GEN
T1 - A Review on Human Stress Detection using Biosignal Based on Image Processing Technique
AU - Hendryani, Atika
AU - Rizkinia, Mia
AU - Gunawan, Dadang
N1 - Funding Information:
ACKNOWLEDGMENT The author would like to thank the financial support provided by Kementerian Pendidikan, Kebudayaan, Riset dan Teknologi through PDD 2022 funding scheme under grant number 091/E5/PG.02.00PT/2022
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Stress is a problem in human life today. The pandemic caused by COVID-19 has also caused increased stress. Some people are aware of the stress they are experiencing and can control it, but some are unaware. Subsequently, it is vital to identify it early to anticipate worsening the condition. A noninvasive, easy, and convenient method is needed to predict daily life stress. One widely developed noninvasive stress detection method is the image processing technique. This technique uses images captured by cameras. Various image processing techniques are applied, i.e., extracting temperature, biosignal, and respiration parameters. This study investigated research on stress detection using biosignals based on image processing techniques. This research found that stress detection can be done using a webcam, a cheap and easy method to implement. Several limitations, such as accuracy and minimizing environmental influences, are still challenging to improve.
AB - Stress is a problem in human life today. The pandemic caused by COVID-19 has also caused increased stress. Some people are aware of the stress they are experiencing and can control it, but some are unaware. Subsequently, it is vital to identify it early to anticipate worsening the condition. A noninvasive, easy, and convenient method is needed to predict daily life stress. One widely developed noninvasive stress detection method is the image processing technique. This technique uses images captured by cameras. Various image processing techniques are applied, i.e., extracting temperature, biosignal, and respiration parameters. This study investigated research on stress detection using biosignals based on image processing techniques. This research found that stress detection can be done using a webcam, a cheap and easy method to implement. Several limitations, such as accuracy and minimizing environmental influences, are still challenging to improve.
KW - image analysis
KW - physiological signal
KW - remote photoplethysmograph
KW - stress detection
UR - http://www.scopus.com/inward/record.url?scp=85166666405&partnerID=8YFLogxK
U2 - 10.1109/ICHE55634.2022.10179880
DO - 10.1109/ICHE55634.2022.10179880
M3 - Conference contribution
AN - SCOPUS:85166666405
T3 - 2022 International Conference on Healthcare Engineering, ICHE 2022 - Proceedings
BT - 2022 International Conference on Healthcare Engineering, ICHE 2022 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 International Conference on Healthcare Engineering, ICHE 2022
Y2 - 23 September 2022 through 25 September 2022
ER -