Mo.1.2.5
Predicting Depression Using Physical Activity, Sleep, and Demographic Factors in NHANES: A Fairness-Centred Machine Learning Approach
Mackenzie Wallich, Mariana Bento, Sayeh Bayat, University of Calgary
Session:
Mo.1.2: Emotion and Affective Signal Processing I Oral
Track:
Biomedical Signal Processing
Location:
Room 714A
Presentation Time:
Monday, 27 July, 12:45 - 13:00
Session Co-Chairs:
Camilo Valderrama and Marisa Pesola
Presentation
Discussion
Resources
No resources available.
Session Mo.1.2
Mo.1.2.1: A HIERARCHICAL GRAPH-BASED FRAMEWORK FOR CROSS-SUBJECT EMOTION RECOGNITION USING MULTIMODAL PHYSIOLOGICAL SIGNALS
Yufan Du, Yiting Wei, Chenpei Xie, Mostafa Haghi, Nima TaheriNejad, Heidelberg University
Mo.1.2.2: Local-Global Feature Fusion for Subject-Independent Electroencephalography (EEG) Emotion Recognition
Zheng Zhou, Beijing Jiaotong University; Isabella McEvoy, Camilo E. Valderrama, University of Winnipeg
Mo.1.2.3: FLOW EXPERIENCE RECOGNITION USING ENSEMBLE AND LINEAR CLASSIFIERS ON HEART RATE VARIABILITY INDICES
Szymon Siecinski, AGH University of Cracow; Ewaryst Tkacz, Academy of Silesia; Marcin Grzegorzek, University of Luebeck
Mo.1.2.4: Instantaneous Phase Coupling Between EEG and Heartbeat Dynamics in Emotional Processing
Martina Bianco, Vincenzo Catrambone, University of Pisa; Beatrice Cairo, Vlasta Bari, Alberto Porta, University of Milan; Gaetano Valenza, University of Pisa
Mo.1.2.5: Predicting Depression Using Physical Activity, Sleep, and Demographic Factors in NHANES: A Fairness-Centred Machine Learning Approach
Mackenzie Wallich, Mariana Bento, Sayeh Bayat, University of Calgary
Mo.1.2.6: MULTI-SOURCE DOMAIN ADAPTATION VIA MULTI-GRANULARITY ALIGNMENT FOR CROSS-SUBJECT EEG EMOTION RECOGNITION
Ying Tan, Nankai University; Binghua Li, Juntendo University; Hao Jia, Nankai University; Zhe Sun, Juntendo University; Feng Duan, Nankai University
Resources
No resources available.