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

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

doi:10.1109/iecon.2014.7048853

Cited by 7 publications

(15 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Wang Nanyue et al observed variations of time domain, frequency domain parameters of Zuoguan and Zuochi are used to identify the healthy subject or cirrhosis subject. Also able to distinguished Fatty Liver Disease (FLD) and cirrhosis subject depending upon the parameters of Youguan and Youchi [54][55][56][57][58][59][60]. Thakker et al observed suppression of dicrotic notch at deep pressure in prostate enlargement urinary tract disorder which occurs in male subject [33].…”

Section: Inflammation and Urinary Tract Infection Disordermentioning

confidence: 99%

A review of wrist pulse analysis

Gc¹,

Veerabhadrappa²

2019

biomedicalresearch

View full text Add to dashboard Cite

In present scenario, the human health condition is being diagnosed by various advanced sophisticated equipments. Moreover, the process of diagnosis is becoming expensive and painful. In ancient Indian Ayurveda and Traditional Chinese Medicine (TCM), wrist pulse was used to diagnose the health status of the subject and to envision the root cause of a disease. According to Ayurveda, a person's health status depends on three essential components and the imbalance of a component is the symptom of a disease. Practitioner determines the unhealthiness of a subject, based on the wrist pulse parameters such as pulse strength, amplitude shape, vega, rhythm, pulse width and transition period. Evaluation of the vital information of the components depends exclusively upon the perception of the practitioner and varies from practitioner to practitioner based on his/her expertise or experience. No modern technique can determine the pathological condition of a subject. The paper presents a review of wrist pulse parameters for diseases like diabetics, hypertension, gastritis, etc.

show abstract

Section: Inflammation and Urinary Tract Infection Disordermentioning

confidence: 99%

A review of wrist pulse analysis

Gc¹,

Veerabhadrappa²

2019

biomedicalresearch

View full text Add to dashboard Cite

show abstract

“…In this paper, Wrist pulse signal (WPS) of human is considered which provides key information regarding health conditions. In the literature, WPS can be utilized for various applications, for instance, pre-meal and post-meal classification [4], physical exercise [5], diabetes classification [6], hypertension association [7,8], lung cancer recognition [9], and inflammation classification [10,11]. Various signal processing techniques on WPS can be found in [12][13][14], for instance, dynamic time warping, wavelet analysis, periodic decomposition, principal component analysis, and linear discriminant analysis.…”

Section: Introductionmentioning

confidence: 99%

“…There have been more than million of sufferers and thus it is necessary to have a reliable and accurate method for the diagnosis of organ inflammations. Based on literature finding, there are a few publications working on binary classification of healthy, appendicitis, acute appendicitis, duodenitis, and pancreatitis sufferers [10,11]. In [10], the features extraction process, an auto-regression (AR) based model was proposed.…”

Section: Introductionmentioning

confidence: 99%

“…With regard to the classification, the support vector machine (SVM) with linear kernel was adopted for the binary classification, which yields an accuracy of 77.8-91.2%. For further improvement, a radial basis kernel (RBF) has been utilized to replace the linear kernel [11]. The idea is that most of the classification problems are not linearly separable.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Novel MOGA-SVM Multinomial Classification for Organ Inflammation Detection

Chui

Lytras

2019

Applied Sciences

View full text Add to dashboard Cite

Wrist pulse signal (WPS) contains crucial information of humans’ health condition. It can serve as an alternative method for diagnosing of organ inflammation instead of traditional clinical measurement. In this paper, a novel multi-objective genetic algorithm based support vector machine (MOGA-SVM) has been proposed for the multinomial classification of the inflammations of appendix, pancreas, and duodenum. A customized similarity kernel (KCS) has been optimally designed. The performance of multinomial classification using KCS is compared with five types of kernels, linear, radial basis function (RBF), polynomial and sigmoid kernel, as well as mixtures of polynomial and RBF, to verify the effectiveness of KCS. The sensitivity, specificity and accuracy (Acc) of the proposed method are 92%, 91.2%, and 91.6% respectively. The results have demonstrated that KCS improves the accuracy of classification from 8.9% to 59.6%. When compared to related work, the proposed method increases the performance by more than 10%. It is believed that WPS can serve as alternative measures to diagnose organ inflammations.

show abstract

“…Chow et al [14] defined the Doppler parameters to be the disease sensitive features and applied the Support Vector Machine to distinguish between Acute Appendicitis patients and healthy individuals. Gong et al [15] designed a wrist pulse sensing and analyzing system for recognition of cirrhosis patients with an accuracy of 87.09%.…”

Section: Introductionmentioning

confidence: 99%