ArticleBiomedical signal processing and control2010
Fatigue and non-fatigue mathematical muscle models during functional electrical stimulation of paralyzed muscle.
Article in Biomedical signal processing and control, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- A Pilot Study on EEG-Based Evaluation of Visually Induced Motion Sickness.The Journal of imaging science and technology · 2020Article
- Exhaustion of Skeletal Muscle Fibers Within Seconds: Incorporating Phosphate Kinetics Into a Hill-Type Model.Frontiers in physiology · 2020Article
- Design of the Cooperative Actuation in Hybrid Orthoses: A Theoretical Approach Based on Muscle Models.Frontiers in neurorobotics · 2019Article
- Evoked Electromyographically Controlled Electrical Stimulation.Frontiers in neuroscience · 2016Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Electrical muscle stimulation demonstrates potential for preventing muscle atrophy and for restoring functional movement after spinal cord injury (SCI). Control systems used to optimize delivery of electrical stimulation protocols depend upon the algorithms generated using computational models of paralyzed muscle force output. The Hill-Huxley-type model, while being highly accurate, is also very complex, making it difficult for real-time implementation. In this paper, we propose a Wiener-Hammerstein system to model the paralyzed skeletal muscle under electrical stimulus conditions. The proposed model has substantial advantages in identification algorithm analysis and implementation including computational complexity and convergence, which enable it to be used in real-time model implementation. Experimental data sets from the soleus muscles of fourteen subjects with SCI were collected and tested. The simulation results show that the proposed model outperforms the Hill-Huxley-type model not only in peak force prediction, but also in fitting performance for force output of each individual stimulation train.
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Registered trials
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