153 related articles for article (PubMed ID: 36446009)
21. Predicting Emotion with Biosignals: A Comparison of Classification and Regression Models for Estimating Valence and Arousal Level Using Wearable Sensors.
Siirtola P; Tamminen S; Chandra G; Ihalapathirana A; Röning J
Sensors (Basel); 2023 Feb; 23(3):. PubMed ID: 36772638
[TBL] [Abstract][Full Text] [Related]
22. Harnessing Wearable Devices for Emotional Intelligence: Therapeutic Applications in Digital Health.
Arabian H; Abdulbaki Alshirbaji T; Schmid R; Wagner-Hartl V; Chase JG; Moeller K
Sensors (Basel); 2023 Sep; 23(19):. PubMed ID: 37836923
[TBL] [Abstract][Full Text] [Related]
23. Fused CNN-LSTM deep learning emotion recognition model using electroencephalography signals.
Ramzan M; Dawn S
Int J Neurosci; 2023 Jun; 133(6):587-597. PubMed ID: 34121598
[No Abstract] [Full Text] [Related]
24. Interpretable Cross-Subject EEG-Based Emotion Recognition Using Channel-Wise Features.
Jin L; Kim EY
Sensors (Basel); 2020 Nov; 20(23):. PubMed ID: 33255374
[TBL] [Abstract][Full Text] [Related]
25. Affective computing in virtual reality: emotion recognition from brain and heartbeat dynamics using wearable sensors.
Marín-Morales J; Higuera-Trujillo JL; Greco A; Guixeres J; Llinares C; Scilingo EP; Alcañiz M; Valenza G
Sci Rep; 2018 Sep; 8(1):13657. PubMed ID: 30209261
[TBL] [Abstract][Full Text] [Related]
26. CorrNet: Fine-Grained Emotion Recognition for Video Watching Using Wearable Physiological Sensors.
Zhang T; El Ali A; Wang C; Hanjalic A; Cesar P
Sensors (Basel); 2020 Dec; 21(1):. PubMed ID: 33374281
[TBL] [Abstract][Full Text] [Related]
27. Heart sound signals can be used for emotion recognition.
Xiefeng C; Wang Y; Dai S; Zhao P; Liu Q
Sci Rep; 2019 Apr; 9(1):6486. PubMed ID: 31019217
[TBL] [Abstract][Full Text] [Related]
28. Online Learning for Wearable EEG-Based Emotion Classification.
Moontaha S; Schumann FEF; Arnrich B
Sensors (Basel); 2023 Feb; 23(5):. PubMed ID: 36904590
[TBL] [Abstract][Full Text] [Related]
29. A novel signal to image transformation and feature level fusion for multimodal emotion recognition.
Hatipoglu Yilmaz B; Kose C
Biomed Tech (Berl); 2021 Aug; 66(4):353-362. PubMed ID: 33823091
[TBL] [Abstract][Full Text] [Related]
30. Emotion recognition using spatial-temporal EEG features through convolutional graph attention network.
Li Z; Zhang G; Wang L; Wei J; Dang J
J Neural Eng; 2023 Feb; 20(1):. PubMed ID: 36720164
[No Abstract] [Full Text] [Related]
31. Emotion Assessment Using Feature Fusion and Decision Fusion Classification Based on Physiological Data: Are We There Yet?
Bota P; Wang C; Fred A; Silva H
Sensors (Basel); 2020 Aug; 20(17):. PubMed ID: 32825624
[TBL] [Abstract][Full Text] [Related]
32. Automated Affective Computing Based on Bio-Signals Analysis and Deep Learning Approach.
Filippini C; Di Crosta A; Palumbo R; Perpetuini D; Cardone D; Ceccato I; Di Domenico A; Merla A
Sensors (Basel); 2022 Feb; 22(5):. PubMed ID: 35270936
[TBL] [Abstract][Full Text] [Related]
33. Graph Theoretical Analysis of EEG Functional Connectivity Patterns and Fusion with Physiological Signals for Emotion Recognition.
Xefteris VR; Tsanousa A; Georgakopoulou N; Diplaris S; Vrochidis S; Kompatsiaris I
Sensors (Basel); 2022 Oct; 22(21):. PubMed ID: 36365896
[TBL] [Abstract][Full Text] [Related]
34. K-EmoCon, a multimodal sensor dataset for continuous emotion recognition in naturalistic conversations.
Park CY; Cha N; Kang S; Kim A; Khandoker AH; Hadjileontiadis L; Oh A; Jeong Y; Lee U
Sci Data; 2020 Sep; 7(1):293. PubMed ID: 32901038
[TBL] [Abstract][Full Text] [Related]
35. SAE+LSTM: A New Framework for Emotion Recognition From Multi-Channel EEG.
Xing X; Li Z; Xu T; Shu L; Hu B; Xu X
Front Neurorobot; 2019; 13():37. PubMed ID: 31244638
[TBL] [Abstract][Full Text] [Related]
36. EEG-Based Emotion Classification Using Long Short-Term Memory Network with Attention Mechanism.
Kim Y; Choi A
Sensors (Basel); 2020 Nov; 20(23):. PubMed ID: 33255539
[TBL] [Abstract][Full Text] [Related]
37. Emotion recognition from single-trial EEG based on kernel Fisher's emotion pattern and imbalanced quasiconformal kernel support vector machine.
Liu YH; Wu CT; Cheng WT; Hsiao YT; Chen PM; Teng JT
Sensors (Basel); 2014 Jul; 14(8):13361-88. PubMed ID: 25061837
[TBL] [Abstract][Full Text] [Related]
38. Multiple-output support vector machine regression with feature selection for arousal/valence space emotion assessment.
Torres-Valencia CA; Álvarez MA; Orozco-Gutiérrez AA
Annu Int Conf IEEE Eng Med Biol Soc; 2014; 2014():970-3. PubMed ID: 25570122
[TBL] [Abstract][Full Text] [Related]
39. Spatial-frequency-temporal convolutional recurrent network for olfactory-enhanced EEG emotion recognition.
Xing M; Hu S; Wei B; Lv Z
J Neurosci Methods; 2022 Jul; 376():109624. PubMed ID: 35588948
[TBL] [Abstract][Full Text] [Related]
40. A EEG-based emotion recognition model with rhythm and time characteristics.
Yan J; Chen S; Deng S
Brain Inform; 2019 Sep; 6(1):7. PubMed ID: 31549331
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
