Literature DB >> 15742371

Mathematical model that predicts isometric muscle forces for individuals with spinal cord injuries.

Jun Ding1, Samuel C K Lee, Therese E Johnston, Anthony S Wexler, Wayne B Scott, Stuart A Binder-Macleod.   

Abstract

The ideal functional electrical stimulation (FES) system requires a mathematical model to provide feedforward control of the stimulation parameters such that they are optimal for different individuals across a range of physiological conditions, muscles, and tasks. Recently we tested and validated such a model using able-bodied subjects. The purpose of this study was to determine whether this model applied to persons with spinal cord injuries (SCI). To this end, the isometric force responses of the paralyzed quadriceps femoris muscles of 14 adolescents and young adults were tested. For each subject, the force responses to two six-pulse stimulation trains were used to identify the parameter values of the model and then the model was used to predict the force responses to three train patterns across a range of frequencies in both a nonfatigued and fatigued condition. The intraclass correlation coefficients (ICCs) between the experimental and predicted force-time integrals and peak forces were above 0.90 for 12 of the 13 stimulation trains tested in the nonfatigued condition and all 13 trains tested in the fatigued condition. The success of our model with SCI subjects leads us to believe that our model may be useful for designing optimal stimulation parameters for standing and ambulation in patients who use FES.

Entities:  

Mesh:

Year:  2005        PMID: 15742371     DOI: 10.1002/mus.20303

Source DB:  PubMed          Journal:  Muscle Nerve        ISSN: 0148-639X            Impact factor:   3.217


  9 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.  Mathematical model that predicts the force-intensity and force-frequency relationships after spinal cord injuries.

Authors:  Jun Ding; Li-Wei Chou; Trisha M Kesar; Samuel C K Lee; Therese E Johnston; Anthony S Wexler; Stuart A Binder-Macleod
Journal:  Muscle Nerve       Date:  2007-08       Impact factor: 3.217

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.  A predictive mathematical model of muscle forces for children with cerebral palsy.

Authors:  Samuel C K Lee; Jun Ding; Laura A Prosser; Anthony S Wexler; Stuart A Binder-Macleod
Journal:  Dev Med Child Neurol       Date:  2009-08-24       Impact factor: 5.449

5.  In vivo demonstration of a self-sustaining, implantable, stimulated-muscle-powered piezoelectric generator prototype.

Authors:  B E Lewandowski; K L Kilgore; K J Gustafson
Journal:  Ann Biomed Eng       Date:  2009-08-06       Impact factor: 3.934

Review 6.  The effectiveness of FES-evoked EMG potentials to assess muscle force and fatigue in individuals with spinal cord injury.

Authors:  Morufu Olusola Ibitoye; Eduardo H Estigoni; Nur Azah Hamzaid; Ahmad Khairi Abdul Wahab; Glen M Davis
Journal:  Sensors (Basel)       Date:  2014-07-14       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.  Predicting muscle forces of individuals with hemiparesis following stroke.

Authors:  Trisha M Kesar; Jun Ding; Anthony S Wexler; Ramu Perumal; Ryan Maladen; Stuart A Binder-Macleod
Journal:  J Neuroeng Rehabil       Date:  2008-02-27       Impact factor: 4.262

9.  Electrically Elicited Force Response Characteristics of Forearm Extensor Muscles for Electrical Muscle Stimulation-Based Haptic Rendering.

Authors:  Jungeun Lee; Yeongjin Kim; Hoeryong Jung
Journal:  Sensors (Basel)       Date:  2020-10-04       Impact factor: 3.576

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.