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Pulse localization networks with infrared camera

Published: 03 May 2021 Publication History

Abstract

Pulse localization is the basic task of the pulse diagnosis with robot. More accurate location can reduce the misdiagnosis caused by different types of pulse. Traditional works usually use a collection surface with a certain area for contact detection, and move the collection surface to collect changes of power for pulse localization. These methods often require the subjects place their wrist in a given position. In this paper, we propose a novel pulse localization method which uses the infrared camera as the input sensor, and locates the pulse on wrist with the neural network. This method can not only reduce the contact between the machine and the subject, reduce the discomfort of the process, but also reduce the preparation time for the test, which can improve the detection efficiency. The experiments show that our proposed method can locate the pulse with high accuracy. And we have applied this method to pulse diagnosis robot for pulse data collection.

References

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Cited By

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  • (2024)Perceptual Quality Assessment of Omnidirectional Images: A Benchmark and Computational ModelACM Transactions on Multimedia Computing, Communications, and Applications10.1145/364034420:6(1-24)Online publication date: 8-Mar-2024
  • (2023)A Protocol for Digitalized Collection of Traditional Chinese Medicine (TCM) Pulse Information Using Bionic Pulse Diagnosis EquipmentPhenomics10.1007/s43657-023-00104-23:5(519-534)Online publication date: 27-Jul-2023
  • (2022)Palpation localization of radial artery based on 3-dimensional convolutional neural networksJournal on Image and Video Processing10.1186/s13640-022-00587-52022:1Online publication date: 18-Jul-2022
  • Show More Cited By

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Published In

cover image ACM Conferences
MMAsia '20: Proceedings of the 2nd ACM International Conference on Multimedia in Asia
March 2021
512 pages
ISBN:9781450383080
DOI:10.1145/3444685
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

Publication History

Published: 03 May 2021

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Author Tags

  1. datasets
  2. neural networks
  3. pulse detection
  4. pulse localization

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  • Research-article

Funding Sources

  • Shanghai Municipal Science and Technology Major Project
  • Key Area Support Plan of Guangdong Province for Jihua Laboratory

Conference

MMAsia '20
Sponsor:
MMAsia '20: ACM Multimedia Asia
March 7, 2021
Virtual Event, Singapore

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Overall Acceptance Rate 59 of 204 submissions, 29%

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Cited By

View all
  • (2024)Perceptual Quality Assessment of Omnidirectional Images: A Benchmark and Computational ModelACM Transactions on Multimedia Computing, Communications, and Applications10.1145/364034420:6(1-24)Online publication date: 8-Mar-2024
  • (2023)A Protocol for Digitalized Collection of Traditional Chinese Medicine (TCM) Pulse Information Using Bionic Pulse Diagnosis EquipmentPhenomics10.1007/s43657-023-00104-23:5(519-534)Online publication date: 27-Jul-2023
  • (2022)Palpation localization of radial artery based on 3-dimensional convolutional neural networksJournal on Image and Video Processing10.1186/s13640-022-00587-52022:1Online publication date: 18-Jul-2022
  • (2022)RARN: A Real-Time Skeleton-based Action Recognition Network for Auxiliary Rehabilitation Therapy2022 IEEE International Symposium on Circuits and Systems (ISCAS)10.1109/ISCAS48785.2022.9937262(2482-2486)Online publication date: 28-May-2022
  • (2022)3DCNN-Based Palpation Localization with Temporal Attention Module2022 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP46576.2022.9897934(871-875)Online publication date: 16-Oct-2022

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