Noncontact multi-modal sensor fusion for sleep stage detection

被引:0
|
作者
Yang, Xiaohui [1 ]
Xue, Biao [2 ]
Zhang, Li [2 ]
Liu, Xin [1 ]
Hong, Hong [2 ]
机构
[1] Nanjing Integrated Tradit Chinese & Western Med H, Nanjing 210014, Peoples R China
[2] Nanjing Univ Sci & Technol, Nanjing, Peoples R China
来源
2019 IEEE MTT-S INTERNATIONAL MICROWAVE BIOMEDICAL CONFERENCE (IMBIOC 2019) | 2019年
关键词
D O I
10.1109/imbioc.2019.8777863
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Non-contact monitoring of sleep quality and early diagnosis of sleep disorders have become hot topics in recent years. We propose a new method to extract sleep related vital signals through low-cost and non-contact multi-modal sensor fusion method with Doppler radar and microphone. Based on the PSG data of patients with sleep disorders, this work has been recognized and certified by professionals in Nanjing Integrated Traditional Chinese and Western Medicine Hospital with unique design. By comparing the sleep stage classification performance of single sensor and sensor fusion algorithm, the effectiveness of the algorithm is validated.
引用
收藏
页数:3
相关论文
共 50 条
  • [21] MULTI-VIEW AND MULTI-MODAL EVENT DETECTION UTILIZING TRANSFORMER-BASED MULTI-SENSOR FUSION
    Yasuda, Masahiro
    Ohishi, Yasunori
    Saito, Shoichiro
    Harado, Noboru
    2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2022, : 4638 - 4642
  • [22] Multi-modal Fusion Network for Rumor Detection with Texts and Images
    Li, Boqun
    Qian, Zhong
    Li, Peifeng
    Zhu, Qiaoming
    MULTIMEDIA MODELING (MMM 2022), PT I, 2022, 13141 : 15 - 27
  • [23] Attention-based multi-modal fusion sarcasm detection
    Liu, Jing
    Tian, Shengwei
    Yu, Long
    Long, Jun
    Zhou, Tiejun
    Wang, Bo
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2023, 44 (02) : 2097 - 2108
  • [24] Multi-Modal Sarcasm Detection in Twitter with Hierarchical Fusion Model
    Cai, Yitao
    Cai, Huiyu
    Wan, Xiaojun
    57TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2019), 2019, : 2506 - 2515
  • [25] MULTI-MODAL CHARACTERISTICS ANALYSIS AND FUSION FOR TV COMMERCIAL DETECTION
    Liu, Nan
    Zhao, Yao
    Zhu, Zhenfeng
    Lu, Hanqing
    2010 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO (ICME 2010), 2010, : 831 - 836
  • [26] Leveraging Multi-Modal Saliency and Fusion for Gaze Target Detection
    Mathew, Athul M.
    Khan, Arshad Ali
    Khalid, Thariq
    AL-Tam, Faroq
    Souissi, Riad
    GAZE MEETS MACHINE LEARNING WORKSHOP, 2023, 226 : 161 - 179
  • [27] MULTIPHISH: MULTI-MODAL FEATURES FUSION NETWORKS FOR PHISHING DETECTION
    Zhang, Lei
    Zhang, Peng
    Liu, Luchen
    Tan, Jianlong
    2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021), 2021, : 3520 - 3524
  • [28] Automated detection of sleep apnea in infants: A multi-modal approach
    Cohen, Gregory
    de Chazal, Philip
    COMPUTERS IN BIOLOGY AND MEDICINE, 2015, 63 : 118 - 123
  • [29] A Minimal Gated Multi-Modal Unit for Sensor Fusion in Insurance Telematics
    Narvaez, Aaron H.
    Gonzalez, Luis C.
    Wahlstrom, Johan
    Lopez-Monroy, A. Pastor
    Reyes, Fernando Martinez
    IEEE ACCESS, 2023, 11 : 93574 - 93586
  • [30] Heterogeneous Multi-Modal Sensor Fusion with Hybrid Attention for Exercise Recognition
    Wijekoon, Anjana
    Wiratunga, Nirmalie
    Cooper, Kay
    2020 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2020,