Next Article in Journal
Variational Disentangle Zero-Shot Learning
Next Article in Special Issue
Persistent Homology Identifies Pathways Associated with Hepatocellular Carcinoma from Peripheral Blood Samples
Previous Article in Journal
Some Theoretical and Computational Aspects of the Truncated Multivariate Skew-Normal/Independent Distributions
Previous Article in Special Issue
Imputing Phylogenetic Trees Using Tropical Polytopes over the Space of Phylogenetic Trees
 
 
Article
Peer-Review Record

Fatigue Estimation Using Peak Features from PPG Signals

Mathematics 2023, 11(16), 3580; https://doi.org/10.3390/math11163580
by Yi-Xiang Chen 1, Chin-Kun Tseng 2,3, Jung-Tsung Kuo 2, Chien-Jen Wang 2,4, Shu-Hung Chao 2, Lih-Jen Kau 2, Yuh-Shyan Hwang 2 and Chun-Ling Lin 1,*
Reviewer 1: Anonymous
Mathematics 2023, 11(16), 3580; https://doi.org/10.3390/math11163580
Submission received: 31 July 2023 / Revised: 14 August 2023 / Accepted: 16 August 2023 / Published: 18 August 2023
(This article belongs to the Special Issue Advanced Computational Biology and Bioinformatics)

Round 1

Reviewer 1 Report

please see the attachment

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

1. how the table 1 and table 2 values are finalised?

2. what is the model used for prediciton of fatigue is not clear in paper. 

3. Overall workflow diagram is missing.

4. How do you evaluate the model? what metrics used?  which model used for prediction?

 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

 

All major comments were adequately addressed and the Authors have done an admirable job of improving the quality of the manuscript. Therefore, it can be accepted without any structural modification. 

Reviewer 2 Report

author made changes based on review comments

Back to TopTop