Name
Title | ||
|---|---|---|
Wrist pulse signal classification for inflammation of appendix, pancreas, and duodenum |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/IECON.2014.7048853 | IECON |
Keywords | DocType | ISSN |
doppler measurement,biomedical measurement,blood flow measurement,diseases,feature extraction,feature selection,medical signal processing,signal classification,support vector machines,aa symptoms,dbu symptoms,doppler parameters,p symptoms,svm classifier training,acute appendicitis patients,acute appendicitis symptoms,appendix inflammation,arterial blood flow,blood flow characteristics,cardiac cycle,classification accuracy,disease sensitive features,duodenal bulb ulcer symptoms,duodenum inflammation,inflammation symptoms,pancreas inflammation,pancreatitis patients,pancreatitis symptoms,patient health condition information,support vector machine,time series wrist pulse signals,wrist pulse signal analysis research,wrist pulse signal classification,wrist pulse signal features,appendix,classification,doppler ultrasound,duodenum,inflammation,pancreas,wrist pulse,doppler effect,blood flow,accuracy,kernel | Conference | 1553-572X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| wai hei chow | 1 | 0 | 0.34 |
| Chung Kit Wu | 2 | 18 | 8.49 |
| Kim Fung Tsang | 3 | 61 | 26.02 |
| Benjamin Yee Shing Li | 4 | 1 | 1.02 |
| Kwok Tai Chui | 5 | 46 | 7.41 |