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Design Of A Predictive Model For TCM Pulse Diagnosis In Malaysia Using Machine Learning

Pulse diagnosis is one of the main diagnosis methods used on patients in Traditional Chinese medicine (TCM). TCM pulse is a time series signal which can be sensed using fingers by TCM practitioners in traditional way. In this project, the TCM pulse signal is collected using a pulse-taking system tha...

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Main Author: Ong, Jia Ying
Format: Final Year Project / Dissertation / Thesis
Published: 2020
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utar.edu.my/4042/1/3E_1503356_FYP_report_%2D_Ong_Jia_Ying.pdf
http://eprints.utar.edu.my/4042/
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spelling my-utar-eprints.40422021-06-11T22:12:29Z Design Of A Predictive Model For TCM Pulse Diagnosis In Malaysia Using Machine Learning Ong, Jia Ying TK Electrical engineering. Electronics Nuclear engineering Pulse diagnosis is one of the main diagnosis methods used on patients in Traditional Chinese medicine (TCM). TCM pulse is a time series signal which can be sensed using fingers by TCM practitioners in traditional way. In this project, the TCM pulse signal is collected using a pulse-taking system that consists of amplify spontaneous emissions (ASE), fibre Bragg grating analyser (FBGA) and fibre optic sensor (FBG). In this project, Python is used to build the machine learning models to classify if a person is active in exercising or not through his/her TCM pulse. The machine learning algorithms applied in this project are k-nearest neighbors (KNN), naïve Bayes, random forest, gradient boosting and support vector machine (SVM). People that active in exercising tends to have a slower pulse rate and higher pulse’s height from left ‘Cun’ through the observation of the results in this project. SVM model has the best performance to classify the data set with 315 data samples. 2020 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/4042/1/3E_1503356_FYP_report_%2D_Ong_Jia_Ying.pdf Ong, Jia Ying (2020) Design Of A Predictive Model For TCM Pulse Diagnosis In Malaysia Using Machine Learning. Final Year Project, UTAR. http://eprints.utar.edu.my/4042/
institution Universiti Tunku Abdul Rahman
building UTAR Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tunku Abdul Rahman
content_source UTAR Institutional Repository
url_provider http://eprints.utar.edu.my
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Ong, Jia Ying
Design Of A Predictive Model For TCM Pulse Diagnosis In Malaysia Using Machine Learning
description Pulse diagnosis is one of the main diagnosis methods used on patients in Traditional Chinese medicine (TCM). TCM pulse is a time series signal which can be sensed using fingers by TCM practitioners in traditional way. In this project, the TCM pulse signal is collected using a pulse-taking system that consists of amplify spontaneous emissions (ASE), fibre Bragg grating analyser (FBGA) and fibre optic sensor (FBG). In this project, Python is used to build the machine learning models to classify if a person is active in exercising or not through his/her TCM pulse. The machine learning algorithms applied in this project are k-nearest neighbors (KNN), naïve Bayes, random forest, gradient boosting and support vector machine (SVM). People that active in exercising tends to have a slower pulse rate and higher pulse’s height from left ‘Cun’ through the observation of the results in this project. SVM model has the best performance to classify the data set with 315 data samples.
format Final Year Project / Dissertation / Thesis
author Ong, Jia Ying
author_facet Ong, Jia Ying
author_sort Ong, Jia Ying
title Design Of A Predictive Model For TCM Pulse Diagnosis In Malaysia Using Machine Learning
title_short Design Of A Predictive Model For TCM Pulse Diagnosis In Malaysia Using Machine Learning
title_full Design Of A Predictive Model For TCM Pulse Diagnosis In Malaysia Using Machine Learning
title_fullStr Design Of A Predictive Model For TCM Pulse Diagnosis In Malaysia Using Machine Learning
title_full_unstemmed Design Of A Predictive Model For TCM Pulse Diagnosis In Malaysia Using Machine Learning
title_sort design of a predictive model for tcm pulse diagnosis in malaysia using machine learning
publishDate 2020
url http://eprints.utar.edu.my/4042/1/3E_1503356_FYP_report_%2D_Ong_Jia_Ying.pdf
http://eprints.utar.edu.my/4042/
_version_ 1705060930580119552
score 13.211869

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