Hypertensive Pulse Diagnosis Method Based on Hilbert-Huang Transform and Feature Fusion Dimensionality Reduction
Authors: 
Lin Fan, Ruiling Yao, Zhongmin WangAuthors Info & Claims
Lin Fan, Ruiling Yao, Zhongmin WangAuthors Info & ClaimsPages 509 - 516
Abstract
With the development of artificial intelligence, pulse diagnosis has been standardized and objectified. However, there is a lack of research on the extraction and dimensionality reduction of hypertensive pulse features. We propose two effective features for distinguishing pulses of disease samples and a fusion dimensionality reduction method that combines linear and nonlinear dimensionality reduction. The results show that the proposed features and dimensionality reduction method make the classification accuracy of hypertension pulse feature reach 94.23%, and the training time of the classifier is reduced by 47 seconds, which improves the performance in terms of both accuracy and time.
References
[1]
R. Velik, An objective review of the technological developments for radial pulse diagnosis in traditional Chinese medicine, Euro. J. Integr. Med. 7 (4) (2015) 321–331.
[2]
L. Xu, K. Wang, D. Zhang, Y. Li, Z. Wan, J. Wang, Objectifying researches on traditional Chinese pulse diagnosis, Inform. Med. Sloven. 8 (1) (2003) 56–63.
[3]
Jl A, Qiang W B. Multi-modal bioelectrical signal fusion analysis based on different acquisition devices and scene Settings: overview, challenges, and novel orientation[J]. Information Fusion 79 (2022) 229-247.
[4]
Rosemarie, Velik. An objective review of the technological developments for radial pulse diagnosis in Traditional Chinese Medicine[J]. European Journal of Integrative Medicine, 2015, 7(4):321-331.
[5]
Liu Lei, Wu Qiufeng, Zhang Hongzhi, A review of pulse diagnosis objectification research[J]. Intelligent Computers and Applications, 2013(03):24-28.
[6]
Zhang Z, Zhang Y, Song H, A Sensor-Based Wrist Pulse Signal Processing and Lung Cancer Recognition[J]. Journal of Biomedical Informatics, 2018:S153204641830011X.
[7]
Zj A, Cg A, Jin Z A, Features fusion of multichannel wrist pulse signal based on KL-MGDCCA and decision level combination[J]. Biomedical Signal Processing and Control, 57. STFT
[8]
WANG L, WANG K, XU L. Lempel-ziv decomposition based arrhythmic pulses recognition[C]//Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005.27th Annual International Conference of the. IEEE, 2006: 4606-4609.
[9]
WANG K, XU L, LI Z, Approximate entropy based pulse variability analysis: Computer-based medical systems[C]//2003. Proceedings. 16th IEEE Symposium. IEEE, 2003: 236-241.
[10]
Wang Ke, Xiao Pengfeng, Feng Xuezhi, Improved two-dimensional discrete Hilbert transform-based image edge detection method[J]. Journal of Surveying and Mapping, 2012, 41(3):8.
[11]
Kuang Xue, Li Zhi, Wang Yongjun, An improved HHT-based method for pulse signal analysis[J]. Computer Engineering, 2019, 45(9):6.
[12]
Guo C-L, Chen H-C, Wang Z-F. Research on human pulse feature recognition and classification based on HHT[J]. Electronic Measurement Technology, 2021, 44(19):6.
[13]
Rosemarie, Velik. An objective review of the technological developments for radial pulse diagnosis in Traditional Chinese Medicine[J]. European Journal of Integrative Medicine, 2015, 7(4):321-331.
[14]
Bae J H, Jeon Y J, Lee S, A feasibility study on age-related factors of wrist pulse using principal component analysis[C]//2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2016.
Index Terms
- Hypertensive Pulse Diagnosis Method Based on Hilbert-Huang Transform and Feature Fusion Dimensionality Reduction
Recommendations
Wrist pulse diagnosis of stable coronary heart disease based on acoustics waveforms
Highlights- This paper presented for the first time the stratification of pulse into five layers. In addition, for the first time, acoustic sensors were used to collect ...
Abstract Background and objectiveAs a common pathological pulse, unsmooth pulse has important diagnostic value in traditional Chinese medicine (TCM). In modern pulse diagnosis, unsmooth pulse plays an important role in the diagnosis ...
Feature Extraction for Pulse Waveform in Traditional Chinese Medicine by Hemodynamic Analysis
BIBM '09: Proceedings of the 2009 IEEE International Conference on Bioinformatics and BiomedicinePulse diagnosis is one of important diagnosis methods in Traditional Chinese Medicine(TCM). Feature extraction of TCM pulse has received more and more attention in recent years. While most of previous methods for feature extraction of TCM pulse have no ...
Kernel-based nonlinear dimensionality reduction for electrocardiogram recognition
The human heart is a complex system that reveals many clues about its condition in its electrocardiogram (ECG) signal, and ECG supervising is the most important and efficient way of preventing heart attacks. ECG analysis and recognition are both ...
Comments
Information & Contributors
Information
Published In
September 2022
1221 pages
ISBN:9781450396899
DOI:10.1145/3573942
Copyright © 2022 ACM.
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]
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 16 May 2023
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Funding Sources
- the Xianyang Science and Technology Bureau Project
- National Natural Science Foundation Grant Project
- the Shaanxi Provincial Industrial Field General Project
Conference
AIPR 2022
AIPR 2022: 2022 5th International Conference on Artificial Intelligence and Pattern Recognition
September 23 - 25, 2022
Xiamen, China
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 26Total Downloads
- Downloads (Last 12 months)13
- Downloads (Last 6 weeks)2
Reflects downloads up to 01 Mar 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format