Body Mass Index (BMI) Of Normal and Overweight/Obese Individuals Based on Speech Signals

Authors

  • C. C. Lim Biomedical Electronic Engineering Programme, School of Mechatronics, Pauh Putra Campus, Universiti Malaysia Perlis, Malaysia
  • C. Y. Fook Biomedical Electronic Engineering Programme, School of Mechatronics, Pauh Putra Campus, Universiti Malaysia Perlis, Malaysia
  • V. Vikneswaran Biomedical Electronic Engineering Programme, School of Mechatronics, Pauh Putra Campus, Universiti Malaysia Perlis, Malaysia
  • M. A. H. Abdul Rahim Biomedical Electronic Engineering Programme, School of Mechatronics, Pauh Putra Campus, Universiti Malaysia Perlis, Malaysia
  • M. Hariharan Department of Biomedical Engineering, SRM University, Chennai, India.

Keywords:

Estimate BMI Using Speech, MFCC, LPCC, WPT, kNN, PNN,

Abstract

Conventional method for measuring Body Mass Index (BMI) for individuals are using calibrated weight scale and measuring tape. However, there are certain cases in which the conventional method of measuring the BMI is not accessible. Thus, this experiment was proposed to overcome the problem using speech approach. In order to develop an effective BMI measuring system, speech signals of 30 subjects were recorded using a microphone. The dimension of the speech signal was reduced by extracting the relevant features using LPCC, MFCC and WPT based energy and entropy features. Lastly, both kNearest Neighbour (kNN) and Probabilistic Neural Network (PNN) were used to measure the BMI of an individual. The kNN classifier (97.50%) gives promising accuracy compared to PNN classifier (96.33%).

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Published

2018-05-30

How to Cite

Lim, C. C., Fook, C. Y., Vikneswaran, V., Abdul Rahim, M. A. H., & Hariharan, M. (2018). Body Mass Index (BMI) Of Normal and Overweight/Obese Individuals Based on Speech Signals. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(1-16), 57–61. Retrieved from https://jtec.utem.edu.my/jtec/article/view/4095

Issue

Vol. 10 No. 1-16: Recent Trends in Biomedical Engineering Systems and Technologies I

Section

Articles

License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)

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