Functional electrical stimulation for neuromuscular applications.

By P. Peckham, J. Knutson. Annual Review of Biomedical Engineering, 2005

802 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/ce89072d1af6b81fdd6b2b254d97c25d94d19824

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Philip S. Thomas
2. Michael S. Branicky
3. Kathleen M. Jagodnik
4. A. J. van den Bogert

In Cellular and Molecular Neuroscience

1. Philip S. Thomas
2. Michael S. Branicky
3. Kathleen M. Jagodnik
4. A. J. van den Bogert

In Cognitive Neuroscience

1. Philip S. Thomas
2. Michael S. Branicky
3. Kathleen M. Jagodnik
4. A. J. van den Bogert

Citations in the corpus

• Creating a Reinforcement Learning Controller for Functional Electrical Stimulation of a Human Arm. (2008, background): “For background information on FES refer to (Sujith, 2008; Ragnarsson, 2008; Sheffler and Chae, 2007; Peckham and Knutson, 2005).”
• Training an Actor-Critic Reinforcement Learning Controller for Arm Movement Using Human-Generated Rewards (2017, background): “FUNCTIONAL Electrical Stimulation (FES) involves the application of electrical current to nerves and muscles to restore voluntary movement to individuals paralyzed by spinal cord injury (SCI) [1], [2].”
• Application of the Actor-Critic Architecture to Functional Electrical Stimulation Control of a Human Arm (2009, background): “For background information on FES refer to (Sujith 2008; Ragnarsson 2008; Sheffler and Chae 2007; Peckham and Knutson 2005).”
• Autonomy in Rehabilitation Robotics: An Intersection (2018, neutral): “FES, along with wearable sensors and virtual reality, are all technologies developed for neurorehabilitation which however fall outside of this scope of this article, as they do not involve the use of a robot.”