Literature DB >> 17503498

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

Jun Ding1, Li-Wei Chou, Trisha M Kesar, Samuel C K Lee, Therese E Johnston, Anthony S Wexler, Stuart A Binder-Macleod.   

Abstract

We have previously developed and tested a muscle model that predicts the effect of stimulation frequency on muscle force responses. The aim of this study was to enhance our isometric mathematical model to predict muscle forces in response to stimulation trains with a wide range of frequencies and intensities for the quadriceps femoris muscles of individuals with spinal cord injuries. Isometric forces were obtained experimentally from 10 individuals with spinal cord injuries (time after injury, 1.5-8 years) and then compared to forces predicted by the model. Our model predicted accurately the force-time integrals (FTI) and peak forces (PF) for stimulation trains of a wide range of frequencies (12.5-80 HZ) and intensities (150-600-mus pulse duration), and two different stimulation patterns (constant-frequency trains and doublet-frequency trains). The accurate predictions of our model indicate that our model, which now incorporates the effects of stimulation frequency, intensity, and pattern on muscle forces, can be used to design optimal customized stimulation strategies for spinal cord-injured patients.

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Year:  2007        PMID: 17503498      PMCID: PMC2633444          DOI: 10.1002/mus.20806

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


  34 in total

1.  A novel stimulation pattern improves performance during repetitive dynamic contractions.

Authors:  M B Kebaetse; S C Lee; S A Binder-Macleod
Journal:  Muscle Nerve       Date:  2001-06       Impact factor: 3.217

2.  Mathematical models for fatigue minimization during functional electrical stimulation.

Authors:  Jun Ding; Anthony S Wexler; Stuart A Binder-Macleod
Journal:  J Electromyogr Kinesiol       Date:  2003-12       Impact factor: 2.368

Review 3.  Catchlike property of skeletal muscle: recent findings and clinical implications.

Authors:  Stuart Binder-Macleod; Trisha Kesar
Journal:  Muscle Nerve       Date:  2005-06       Impact factor: 3.217

4.  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

5.  Mathematical model that predicts lower leg motion in response to electrical stimulation.

Authors:  Ramu Perumal; Anthony S Wexler; Stuart A Binder-Macleod
Journal:  J Biomech       Date:  2005-11-22       Impact factor: 2.712

6.  Biomechanical model of the human knee evaluated by neuromuscular stimulation.

Authors:  R Riener; J Quintern; G Schmidt
Journal:  J Biomech       Date:  1996-09       Impact factor: 2.712

7.  The number of active motor units and their firing rates in voluntary contraction of human brachialis muscle.

Authors:  K Kanosue; M Yoshida; K Akazawa; K Fujii
Journal:  Jpn J Physiol       Date:  1979

8.  Model-based development of neuroprosthesis for paraplegic patients.

Authors:  R Riener
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  1999-05-29       Impact factor: 6.237

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

Authors:  Jun Ding; Samuel C K Lee; Therese E Johnston; Anthony S Wexler; Wayne B Scott; Stuart A Binder-Macleod
Journal:  Muscle Nerve       Date:  2005-06       Impact factor: 3.217

10.  Reducing muscle fatigue in FES applications by stimulating with N-let pulse trains.

Authors:  Z Z Karu; W K Durfee; A M Barzilai
Journal:  IEEE Trans Biomed Eng       Date:  1995-08       Impact factor: 4.538

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  5 in total

1.  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

2.  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

3.  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

4.  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

5.  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

  5 in total

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