Comparison of adaptive neuro-fuzzy inference system (ANFIS) and Gaussian processes for machine learning (GPML) algorithms for the prediction of skin temperature in lower limb prostheses-Reference-Cited by-同舟云学术

Comparison of adaptive neuro-fuzzy inference system (ANFIS) and Gaussian processes for machine learning (GPML) algorithms for the prediction of skin temperature in lower limb prostheses

Published:2016-10 Issue:10 Volume:38 Page:1083-1089
ISSN:1350-4533
Container-title:Medical Engineering & Physics
language:en
Short-container-title:Medical Engineering & Physics

Author:

Mathur Neha,Glesk Ivan^ORCID,Buis Arjan

Funder

Engineering and Physical Sciences Research Council

Publisher

Elsevier BV

Subject

Biomedical Engineering,Biophysics

Reference17 articles.

1. Measuring residual limb skin temperatures at the skin-prosthesis interface;Huff;J Prosthet Orthot,2008

2. Residual-limb skin temperature in transtibial sockets;Peery;J Rehabil Res Dev,2005

3. Skin temperature prediction in lower limb prostheses;Mathur;IEEE J Biomed Health Inform,2016

4. Modeling, design & simulation of an adaptive neurofuzzy inference system (ANFIS) for speed control of induction motor;Kusagur;Int J Comput Appl,2010

5. Gaussian processes for regression;Williams,1996

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