No-attachment head tracking method of robotic transcranial magnetic stimulation based on vision sensor

Yu Chen; Wang Xin; Lu Zongjie; Su Huanran

doi:10.1109/ICARCV50220.2020.9305357

No-attachment head tracking method of robotic transcranial magnetic stimulation based on vision sensor

Yu Chen
, Wang Xin
, Lu Zongjie
, Su Huanran

Harbin Institute of Technology Shenzhen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

A vision-based head tracking method for robotic transcranial magnetic stimulation (TMS), requiring no attachments to patient, is proposed to track the movements of patient's head during treatment. First, a facial landmark detection method based on Constrained Local Neural Field (CLNF) algorithm is used. Second, a method of head location and pose estimation is presented and a filter for image restoration is used for a higher accuracy. Finally, calibration approaches are proposed based on the coordinates of the robot arm and camera and real-time motion tracking system. Experiment results indicate that the accuracy and real-time performance of this head tracking method satisfy the requirements of TMS treatment.

Original language	English
Title of host publication	16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1366-1371
Number of pages	6
ISBN (Electronic)	9781728177090
DOIs	https://doi.org/10.1109/ICARCV50220.2020.9305357
State	Published - 13 Dec 2020
Externally published	Yes
Event	16th International Conference on Control, Automation, Robotics and Vision, ICARCV 2020 - Virtual, Online, China Duration: 13 Dec 2020 → 15 Dec 2020

Publication series

Name	16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020

Conference

Conference	16th International Conference on Control, Automation, Robotics and Vision, ICARCV 2020
Country/Territory	China
City	Virtual, Online
Period	13/12/20 → 15/12/20

Access to Document

10.1109/ICARCV50220.2020.9305357

Cite this

Chen, Y., Xin, W., Zongjie, L., & Huanran, S. (2020). No-attachment head tracking method of robotic transcranial magnetic stimulation based on vision sensor. In 16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020 (pp. 1366-1371). Article 9305357 (16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICARCV50220.2020.9305357

Chen, Yu ; Xin, Wang ; Zongjie, Lu et al. / No-attachment head tracking method of robotic transcranial magnetic stimulation based on vision sensor. 16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 1366-1371 (16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020).

@inproceedings{ebf3b9d98ad6458ea293dd71bf40ee0f,

title = "No-attachment head tracking method of robotic transcranial magnetic stimulation based on vision sensor",

abstract = "A vision-based head tracking method for robotic transcranial magnetic stimulation (TMS), requiring no attachments to patient, is proposed to track the movements of patient's head during treatment. First, a facial landmark detection method based on Constrained Local Neural Field (CLNF) algorithm is used. Second, a method of head location and pose estimation is presented and a filter for image restoration is used for a higher accuracy. Finally, calibration approaches are proposed based on the coordinates of the robot arm and camera and real-time motion tracking system. Experiment results indicate that the accuracy and real-time performance of this head tracking method satisfy the requirements of TMS treatment.",

author = "Yu Chen and Wang Xin and Lu Zongjie and Su Huanran",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 16th International Conference on Control, Automation, Robotics and Vision, ICARCV 2020 ; Conference date: 13-12-2020 Through 15-12-2020",

year = "2020",

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day = "13",

doi = "10.1109/ICARCV50220.2020.9305357",

language = "英语",

series = "16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Chen, Y, Xin, W, Zongjie, L & Huanran, S 2020, No-attachment head tracking method of robotic transcranial magnetic stimulation based on vision sensor. in 16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020., 9305357, 16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020, Institute of Electrical and Electronics Engineers Inc., pp. 1366-1371, 16th International Conference on Control, Automation, Robotics and Vision, ICARCV 2020, Virtual, Online, China, 13/12/20. https://doi.org/10.1109/ICARCV50220.2020.9305357

No-attachment head tracking method of robotic transcranial magnetic stimulation based on vision sensor. / Chen, Yu; Xin, Wang; Zongjie, Lu et al.
16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 1366-1371 9305357 (16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Chen, Yu

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AU - Huanran, Su

PY - 2020/12/13

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N2 - A vision-based head tracking method for robotic transcranial magnetic stimulation (TMS), requiring no attachments to patient, is proposed to track the movements of patient's head during treatment. First, a facial landmark detection method based on Constrained Local Neural Field (CLNF) algorithm is used. Second, a method of head location and pose estimation is presented and a filter for image restoration is used for a higher accuracy. Finally, calibration approaches are proposed based on the coordinates of the robot arm and camera and real-time motion tracking system. Experiment results indicate that the accuracy and real-time performance of this head tracking method satisfy the requirements of TMS treatment.

AB - A vision-based head tracking method for robotic transcranial magnetic stimulation (TMS), requiring no attachments to patient, is proposed to track the movements of patient's head during treatment. First, a facial landmark detection method based on Constrained Local Neural Field (CLNF) algorithm is used. Second, a method of head location and pose estimation is presented and a filter for image restoration is used for a higher accuracy. Finally, calibration approaches are proposed based on the coordinates of the robot arm and camera and real-time motion tracking system. Experiment results indicate that the accuracy and real-time performance of this head tracking method satisfy the requirements of TMS treatment.

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DO - 10.1109/ICARCV50220.2020.9305357

M3 - 会议稿件

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Chen Y, Xin W, Zongjie L, Huanran S. No-attachment head tracking method of robotic transcranial magnetic stimulation based on vision sensor. In 16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 1366-1371. 9305357. (16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020). doi: 10.1109/ICARCV50220.2020.9305357

No-attachment head tracking method of robotic transcranial magnetic stimulation based on vision sensor

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