Tu.P17.B-50
EXTRACTING CARDIORESPIRATORY MEASUREMENTS FROM A BALLISTOCARDIOGRAM TO ANALYZE CARDIOPULMONARY COUPLING DURING SLEEP
Dominic Jaworski, Tae-Ho Kim, Bohyung Choi, Edward Park, Simon Fraser University
Session:
Tu.P17: Sleep Poster
Track:
Cardiopulmonary Systems and Physiology-based Engineering
Location:
Hall E; Bay B, Board #50
Presentation Time:
Tuesday, 28 July, 16:30 - 18:30
Presentation
Discussion
Resources
No resources available.
Session Tu.P17
Tu.P17.B-45: Coupling-Aware Evidential Transfer Learning for Motor Imagery EEG Decoding
Dekui Wang, Taoyuan Liu, Yunzhi Tian, Qirong Bo, Wei Zhou, Jun Feng, Northwest University
Tu.P17.B-46: EviSleep: Cross-Domain Evidential Learning for Sleep Stage Classification
Yunzhi Tian, Dekui Wang, Qirong Bo, Jun Feng, Northwest University
Tu.P17.B-47: Au Automatic Sleep Staging Framework Using SHAP-Guided Feature Selection and Cuckoo Search Optimization
Tatiana Klimenko, Yu Sun, Zhejiang University
Tu.P17.B-48: Associations Between Maternal Sleep-Disordered Breathing and Fetal Heart Rate Variability in Late Pregnancy
Md Ariful Islam, Sajib Biswas Shuvo, Arizona State University; Umesh Goswami, Chad M Ruoff, Mayo Clinic; Tabitha Moe, HonorHealth; Md Mobashir Hasan Shandhi, Arizona State University
Tu.P17.B-49: Application of Wavelet Quantization Normalization and Catch22 Features in Automatic Sleep Staging
Bokai Zhang, Dalian University of Technology; Yongxuan Wang, Dalian University; Hongyu Liang, Zengyun Gong, Yuxin Li, Rong Liu, Dalian University of Technology
Tu.P17.B-50: EXTRACTING CARDIORESPIRATORY MEASUREMENTS FROM A BALLISTOCARDIOGRAM TO ANALYZE CARDIOPULMONARY COUPLING DURING SLEEP
Dominic Jaworski, Tae-Ho Kim, Bohyung Choi, Edward Park, Simon Fraser University
Tu.P17.B-51: END-TO-END MACHINE LEARNING FOR DEPRESSIVE STATE CLASSIFICATION VIA EEG AND FNIRS
Riki Sakurai, Shibaura Institute of Technology; Simon Kojima, University of Bordeaux; Mihoko Otake-Matsuura, RIKEN; Shin’ichiro Kanoh, Shibaura Institute of Technology; Tomasz M. Rutkowski, The University of Tokyo
Tu.P17.B-52: Subject-Adaptive Adapters for Parameter-Efficient Source-Free EEG Sleep Staging
Roufang Yao, Chung Tin, City University of Hong Kong
Tu.P17.B-53: SLEEP EEG SIGNAL CRITICALITY AS A NON-INVASIVE PREDICTOR OF COGNITIVE DECLINE IN DEMENTIA
Stanisław Narębski, Tomasz Komendziński, Nicolaus Copernicus University; Tomasz M. Rutkowski, The University of Tokyo
Tu.P17.B-54: AUTOMATED NEONATAL SLEEP STAGING BASED ON CARDIORESPIRATORY SIGNALS
Yilin Guan, Chuchu Liao, Southern University of Science and Technology; Liping Pan, The Third People's Hospital of Shenzhen; Zhenlang Lin, Jingyun Mai, The Second Affiliated Hospital of Wenzhou Medical University; Wenjin Wang, Southern University of Science and Technology
Tu.P17.B-55: QUANTIFYING NIGHT-TO-NIGHT SLEEP ARCHITECTURE STABILITY USING FOUNDATION MODEL EMBEDDINGS
Aravind Ravi, Maurice Abou Jaoude, Taha Morshedzadeh, Jiansheng Niu, Nicolas Florez Torres, David Marcel Baum, Christopher Aimone, InteraXon Inc.
Tu.P17.B-56: CROSS-ATTENTION FUSION OF MULTI-VIEW ECG AND SLEEP-STAGE RARITY FOR AUTOMATED APNEA DETECTION
Aisha Hamad Hassan, IIT MADRAS ZANZIBAR CAMPUS; RITIKA JAIN, IIT GUWAHATI
Tu.P17.B-57: UBIQUITOUS SLEEP APNEA SCREENING DURING WAKEFULNESS USING TRANSFER LEARNING ON CRANIOFACIAL VIDEOS
Behrad Taghibeyglou, University of Toronto; Devin Brown, University of Michigan; Azadeh Yadollahi, University of Toronto
Tu.P17.B-58: A MULTIMODAL FRAMEWORK FOR VARIABLE-LENGTH SLEEP STAGING IN WEARABLE APPLICATIONS
Hyeonjeong Lee, Minseong Kim, Hwi-Gang Kim, Borum Nam, Kwang-Yong Kim, Electronics and Telecommunications Research Institute (ETRI)
Resources
No resources available.