Verification on the Feasibility of A Vision-Based Swallowing Detection Method

被引:0
|
作者
Han, Xuedong [1 ]
Shen, Linyong [1 ]
Song, Wei [1 ]
Zhang, Ya'nan [1 ]
Li, Ji [2 ]
Wang, Shengzi [2 ]
Qian, Jinwu [1 ]
机构
[1] Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai, Peoples R China
[2] Fudan Univ, EYE & ENT Hosp, Shanghai, Peoples R China
关键词
intensity modulated radiation therapy; swallowing detection; vision measurement; template matching;
D O I
10.1109/itaic.2019.8785721
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
During the irradiation of laryngeal cancer, the motion occur from swallowing can cause the area to be irradiated to detach from the clinical target volume. Therefore, it is necessary to detect the number and time of the patient's swallowing during radiotherapy and take corresponding remedial measures afterward. This paper proposes a non-contact swallowing detection method based on the visual sensor which monitors swallowing by detecting the movement of the thyroid cartilage. In our method, first the video images of the thyroid cartilage are taken by a visual sensor, then an improved template matching algorithm is adopted for signals extraction from video images, finally the number of swallowing and the movement time of swallowing can be obtained by analyzing the signals. To verify the feasibility and accuracy of this method, some experiments are made in ten normal subjects. The results show that this method is feasible for detecting the number and time of swallowing movement.
引用
收藏
页码:759 / 763
页数:5
相关论文
共 50 条
  • [21] A Review on Vision-Based Pedestrian Detection
    Zheng, Gang
    Chen, Youbin
    2012 IEEE GLOBAL HIGH TECH CONGRESS ON ELECTRONICS (GHTCE), 2012,
  • [22] A Survey on Vision-based Fall Detection
    Zhang, Zhong
    Conly, Christopher
    Athitsos, Vassilis
    8TH ACM INTERNATIONAL CONFERENCE ON PERVASIVE TECHNOLOGIES RELATED TO ASSISTIVE ENVIRONMENTS (PETRA 2015), 2015,
  • [23] Stereo vision-based vehicle detection
    Bertozzi, M
    Broggi, A
    Fascioli, A
    Nichele, S
    PROCEEDINGS OF THE IEEE INTELLIGENT VEHICLES SYMPOSIUM 2000, 2000, : 39 - 44
  • [24] A Vision-based Approach to Fire Detection
    Gomes, Pedro
    Santana, Pedro
    Barata, Jose
    INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 2014, 11
  • [25] Vision-Based Crowded Pedestrian Detection
    Huang, Shih-Shinh
    Chen, Chun-Yuan
    2015 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - TAIWAN (ICCE-TW), 2015, : 334 - 335
  • [26] Vision-based Road Sign Detection
    Kehl, Manuel
    Enzweiler, Markus
    Froehlich, Bjoern
    Franke, Uwe
    Heiden, Wolfgang
    2015 IEEE 18TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS, 2015, : 505 - 510
  • [27] A Survey of Vision-based Object Detection
    Ge, Naiming
    Yong, Yin
    2022 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, COMPUTER VISION AND MACHINE LEARNING (ICICML), 2022, : 240 - 244
  • [28] Vision-Based Absence Seizure Detection
    Pediaditis, M.
    Tsiknakis, M.
    Koumakis, L.
    Karachaliou, M.
    Voutoufianakis, S.
    Vorgia, P.
    2012 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2012, : 65 - 68
  • [29] A Vision-Based GPS-Spoofing Detection Method for Small UAVs
    Qiao, Yinrong
    Zhang, Yuxing
    Du, Xiao
    2017 13TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY (CIS), 2017, : 312 - 316
  • [30] Vision-Based Intelligent Vehicle Road Recognition and Obstacle Detection Method
    Yang, Fan
    Rao, Yutai
    INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2020, 34 (07)