Estimation of Heart Rate from Vocal Frequency Based on Support Vector Machine

Habitus

View Publication Info
 
 
Field Value
 
Title Estimation of Heart Rate from Vocal Frequency Based on Support Vector Machine
 
Creator Sakai, Motoki
 
Subject Information Environment
Heart rate, vocal frequency, support vector machine, kernel function
 
Description Heart rate (HR) is one of the vital signs used to assess our physical condition; it would be beneficial if HR could easily be obtained without special medical instruments. In this study, a feature of vocal frequency was used to estimate HR, because it can easily be recorded with a common device such as a smartphone. Previous studies proposed that a support vector machine (SVM) that adopted the inner product as the kernel function was efficient for estimating HR to a certain extent. However, these studies did not present the effectiveness of other kernel functions, such as the hyperbolic tangent function. Therefore, this study identified a combination of kernel functions of the kernel ridge regression (KRR). In addition, features of vocal frequency to effectively estimate HR were investigated. To evaluate the effectiveness, experiments were conducted with two subjects. In the experiment, 60 sets of HRs and voice data were measured per subject. To identify the most effective kernel function, four kernel functions (the inner function, Gaussian function, polynomial function, and hyperbolic tangent function) were compared. Moreover, effective features of vocal frequency were selected with the sequential feature selection (SFS) method. As a consequence, the hyperbolic tangent function worked best, and high-frequency components of voice were efficient. However, results of this research indicated that effective vocal spectrum components to estimate HR differ depending on prediction models.
 
Publisher Scholar Science Journals
 
Contributor
 
Date 2016-01-30
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Research
 
Format application/pdf
 
Identifier http://ssjournals.com/index.php/ijasr/article/view/2849
10.7439/ijasr.v2i1.2849
 
Source International Journal of Advances in Scientific Research; Vol 2, No 1 (2016): Jan; 16-22
2395-3616
 
Language eng
 
Relation http://ssjournals.com/index.php/ijasr/article/view/2849/2122
 
Rights Copyright (c) 2016 International Journal of Advances in Scientific Research
http://creativecommons.org/licenses/by/4.0
 

Contact Us

The PKP Index is an initiative of the Public Knowledge Project.

For PKP Publishing Services please use the PKP|PS contact form.

For support with PKP software we encourage users to consult our wiki for documentation and search our support forums.

For any other correspondence feel free to contact us using the PKP contact form.

Find Us

Twitter

Copyright © 2015-2018 Simon Fraser University Library