EN
TR
EVALUATING THE EFFECTS OF THE AUTONOMIC NERVOUS SYSTEM AND SYMPATHETIC ACTIVITY ON EMOTIONAL STATES
Öz
Emotion recognition has attracted more interest by being applied in many application areas from different domains such as medical diagnosis, e-commerce, and robotics. This research quantifies the stimulated short-term effect of emotions on the autonomic nervous system and sympathetic activity. The primary purpose of this study is to investigate the responses of 21 adults by attaching a wearable system to measure physiological data such as an electrocardiogram and electrodermal activity in a controlled environment. Cardiovascular effects were evaluated with heart rate variability indices that included HR, HRV triangular-index, rMSSD (ms), pNN5O (%); frequency analysis of the very low frequency (VLF: 0-0,04 Hz), low frequency (LF: 0,04-0,15 Hz), and high frequency (HF: 0,15-0,4 Hz) components; nonlinear analysis. The sympathetic activity was evaluated with time-varying and time-invariant spectral analysis results of the EDA. The participants who experience calmness had a 4,8% lower heart rate (75,06±16,76 and 78,72±16,52) observed compared to happiness. Negative valance with high-arousal emotions like anger was invariably responded to with a peak in skin conductance level. Besides, negative valance with low-arousal emotions like sadness was allied with a drop in conductance level. Anger, in addition to being the most well-known emotion, elicited coherent time-varying spectral responses.
Anahtar Kelimeler
Kaynakça
- Adha, M.S. & Igasaki, T. (2020, July, 20-24). Concurrent model for three negative emotions using heart rate variability in a driving simulator environment. 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society. 718–721.
- Albraikan, A., Tobón, D.P. & El Saddik, A. (2018). Toward user-independent emotion recognition using physiological signals. IEEE Sensors Journal. 19(19), 8402-8412.
- Balogh, S., Fitzpatrick, D.F., Hendricks, S.E. & Paige, S.R. (1993). Increases in heart rate variability with successful treatment in patients with major depressive disorder. Psychopharmacology Bulletin. 29(2), 201-206.
- Barrett, H. & Popovi, N. (2015). A meta-synthesis on the effects of combining heart rate variability biofeedback and positive emotion on workplace performance. International Journal of Social Science Studies. 3(5), 61-68.
- Berntson, G.G., Thomas Bigger, J., Eckberg, D.L., Grossman, P., Kaufmann, P.G., et al. (1997). Heart rate variability: Origins, methods, and interpretive caveats. Psychophysiology. 34 (6), 623–648.
- Boashash, B. (2015). Time-frequency signal analysis and processing: A comprehensive reference. Academic Press. Cambridge.
- Cosoli, G., Poli, A., Scalise, L. & Spinsante, S. (2021, May, 17-20). Heart rate variability analysis with wearable devices: Influence of artifact correction method on classification accuracy for emotion recognition. IEEE International Instrumentation and Measurement Technology Conference. Scotland. 1–6.
- Domínguez-Jiménez, J.A., Campo-Landines, K.C., Martínez-Santos, J.C., Delahoz, E. J. & Contreras-Ortiz, S.H. (2020). A machine learning model for emotion recognition from physiological signals. Biomedical Signal Processing and Control, 55, 1-11.
Ayrıntılar
Birincil Dil
İngilizce
Konular
Mühendislik
Bölüm
Araştırma Makalesi
Yazarlar
Yayımlanma Tarihi
28 Haziran 2022
Gönderilme Tarihi
2 Haziran 2022
Kabul Tarihi
23 Haziran 2022
Yayımlandığı Sayı
Yıl 2022 Cilt: 21 Sayı: 41
APA
Patlar Akbulut, F. (2022). EVALUATING THE EFFECTS OF THE AUTONOMIC NERVOUS SYSTEM AND SYMPATHETIC ACTIVITY ON EMOTIONAL STATES. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi, 21(41), 156-169. https://doi.org/10.55071/ticaretfbd.1125431
AMA
1.Patlar Akbulut F. EVALUATING THE EFFECTS OF THE AUTONOMIC NERVOUS SYSTEM AND SYMPATHETIC ACTIVITY ON EMOTIONAL STATES. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi. 2022;21(41):156-169. doi:10.55071/ticaretfbd.1125431
Chicago
Patlar Akbulut, Fatma. 2022. “EVALUATING THE EFFECTS OF THE AUTONOMIC NERVOUS SYSTEM AND SYMPATHETIC ACTIVITY ON EMOTIONAL STATES”. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi 21 (41): 156-69. https://doi.org/10.55071/ticaretfbd.1125431.
EndNote
Patlar Akbulut F (01 Haziran 2022) EVALUATING THE EFFECTS OF THE AUTONOMIC NERVOUS SYSTEM AND SYMPATHETIC ACTIVITY ON EMOTIONAL STATES. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi 21 41 156–169.
IEEE
[1]F. Patlar Akbulut, “EVALUATING THE EFFECTS OF THE AUTONOMIC NERVOUS SYSTEM AND SYMPATHETIC ACTIVITY ON EMOTIONAL STATES”, İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi, c. 21, sy 41, ss. 156–169, Haz. 2022, doi: 10.55071/ticaretfbd.1125431.
ISNAD
Patlar Akbulut, Fatma. “EVALUATING THE EFFECTS OF THE AUTONOMIC NERVOUS SYSTEM AND SYMPATHETIC ACTIVITY ON EMOTIONAL STATES”. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi 21/41 (01 Haziran 2022): 156-169. https://doi.org/10.55071/ticaretfbd.1125431.
JAMA
1.Patlar Akbulut F. EVALUATING THE EFFECTS OF THE AUTONOMIC NERVOUS SYSTEM AND SYMPATHETIC ACTIVITY ON EMOTIONAL STATES. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi. 2022;21:156–169.
MLA
Patlar Akbulut, Fatma. “EVALUATING THE EFFECTS OF THE AUTONOMIC NERVOUS SYSTEM AND SYMPATHETIC ACTIVITY ON EMOTIONAL STATES”. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi, c. 21, sy 41, Haziran 2022, ss. 156-69, doi:10.55071/ticaretfbd.1125431.
Vancouver
1.Fatma Patlar Akbulut. EVALUATING THE EFFECTS OF THE AUTONOMIC NERVOUS SYSTEM AND SYMPATHETIC ACTIVITY ON EMOTIONAL STATES. İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi. 01 Haziran 2022;21(41):156-69. doi:10.55071/ticaretfbd.1125431
Cited By
Multi-modal fusion learning through biosignal, audio, and visual content for detection of mental stress
Neural Computing and Applications
https://doi.org/10.1007/s00521-023-09036-4Assessing Feasibility of Cognitive Impairment Testing Using Social Robotic Technology Augmented with Affective Computing and Emotional State Detection Systems
Biomimetics
https://doi.org/10.3390/biomimetics8060475Biosignal based emotion-oriented video summarization
Multimedia Systems
https://doi.org/10.1007/s00530-023-01071-4Biosignals, facial expressions, and speech as measures of workplace stress: Workstress3d dataset
Data in Brief
https://doi.org/10.1016/j.dib.2024.110303
