Wrist pulse signal classification for inflammation of appendix, pancreas, and duodenum

Wai Hei Chow, Chung Kit Wu, Kim Fung Tsang, Benjamin Yee Shing Li, Kwok Tai Chui

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)


Wrist pulse signal is believed to contain critical information of the patients' health condition. This project aims to analyze the time series wrist pulse signals in order to distinguish patients suffering from various symptoms with healthy people. In this paper, the four inflammation symptoms tackled in this project are Appendicitis (A), Acute Appendicitis (AA), Pancreatitis (P) and Duodenal Bulb Ulcer (DBU). Moreover, studying the characteristic of blood flow in arteries and cardiac cycle is crucial for the sake of selecting features from the wrist pulse signals. The defined Doppler parameters in the wrist pulse signal are defined as the disease sensitive features. Furthermore, the features extracted are considered as the parameters for training the Support Vector Machine (SVM) classifier. The classification accuracy can reach over 88% in distinguishing patients with healthy persons from Acute Appendicitis and up to 98% from Pancreatitis. These results indicate the methodology proposed in this project can provide an advanced idea for enhancing the research of wrist pulse signal analysis.

Original languageEnglish
Title of host publicationIECON Proceedings (Industrial Electronics Conference)
Number of pages5
ISBN (Electronic)9781479940325
Publication statusPublished - 24 Feb 2014
Externally publishedYes

Publication series

NameIECON Proceedings (Industrial Electronics Conference)


  • appendix
  • classification
  • doppler ultrasound
  • duodenum
  • inflammation
  • pancreas
  • support vector machine
  • wrist pulse


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