Literature DB >> 12173739

A predictive fatigue model--I: Predicting the effect of stimulation frequency and pattern on fatigue.

Jun Ding1, Anthony S Wexler, Stuart A Binder-Macleod.   

Abstract

Previously we developed a mathematical force- and fatigue-model system that could predict fatigue produced by a wide range of frequencies and pulse patterns. However, the models tended to overestimate the forces produced by higher frequency trains. This paper presents modifications to our previously developed force- and fatigue-model system to improve the accuracy in predicting forces during repetitive activation of human skeletal muscle. By comparing the predictions produced by the modified force and fatigue models to those by our previous models, the modification appears to be successful. The current force- and fatigue-model system accounts for about 93% variance in experimental data produced by fatigue protocols consisting of trains with a wide range of frequencies and pulse patterns. In addition, the present models successfully predict the effect of stimulation frequency and pulse pattern on muscle fatigue. The success of our current force- and fatigue-model system suggests its potential use in helping to identify the optimal activation pattern to use during the clinical application of functional electrical stimulation.

Entities:  

Mesh:

Year:  2002        PMID: 12173739     DOI: 10.1109/TNSRE.2002.1021586

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  8 in total

1.  Predicting human chronically paralyzed muscle force: a comparison of three mathematical models.

Authors:  Laura A Frey Law; Richard K Shields
Journal:  J Appl Physiol (1985)       Date:  2005-11-23

2.  Model-Based Dynamic Control Allocation in a Hybrid Neuroprosthesis.

Authors:  Nicholas A Kirsch; Xuefeng Bao; Naji A Alibeji; Brad E Dicianno; Nitin Sharma
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2017-09-22       Impact factor: 3.802

3.  Dynamic optimization of stimulation frequency to reduce isometric muscle fatigue using a modified Hill-Huxley model.

Authors:  Brian D Doll; Nicholas A Kirsch; Xuefeng Bao; Brad E Dicianno; Nitin Sharma
Journal:  Muscle Nerve       Date:  2017-09-18       Impact factor: 3.217

4.  Fatigue and non-fatigue mathematical muscle models during functional electrical stimulation of paralyzed muscle.

Authors:  Zhijun Cai; Er-Wei Bai; Richard K Shields
Journal:  Biomed Signal Process Control       Date:  2010-04       Impact factor: 3.880

5.  Mathematical models use varying parameter strategies to represent paralyzed muscle force properties: a sensitivity analysis.

Authors:  Laura A Frey Law; Richard K Shields
Journal:  J Neuroeng Rehabil       Date:  2005-05-31       Impact factor: 4.262

6.  Mechanomyographic parameter extraction methods: an appraisal for clinical applications.

Authors:  Morufu Olusola Ibitoye; Nur Azah Hamzaid; Jorge M Zuniga; Nazirah Hasnan; Ahmad Khairi Abdul Wahab
Journal:  Sensors (Basel)       Date:  2014-12-03       Impact factor: 3.576

7.  Predicting non-isometric fatigue induced by electrical stimulation pulse trains as a function of pulse duration.

Authors:  M Susan Marion; Anthony S Wexler; Maury L Hull
Journal:  J Neuroeng Rehabil       Date:  2013-02-02       Impact factor: 4.262

8.  A computational model of torque generation: neural, contractile, metabolic and musculoskeletal components.

Authors:  Damien M Callahan; Brian R Umberger; Jane A Kent-Braun
Journal:  PLoS One       Date:  2013-02-06       Impact factor: 3.240

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.