Application of the actor-critic architecture to functional electrical stimulation control of a human arm

Philip Thomas, Michael Branicky, Antonie Van Den Bogert, Kathleen Jagodnik

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

21 Scopus citations

Abstract

Clinical tests have shown that the dynamics of a human arm, controlled using Functional Electrical Stimulation (FES), can vary significantly between and during trials. In this paper, we study the application of the actor-critic architecture, with neural networks for the both the actor and the critic, as a controller that can adapt to these changing dynamics of a human arm. Development and tests were done in simulation using a planar arm model and Hill-based muscle dynamics. We begin by training it using a Proportional Derivative (PD) controller as a supervisor. We then make clinically relevant changes to the dynamics of the arm and test the actor-critic's ability to adapt without supervision in a reasonable number of episodes. Finally, we devise methods for achieving both rapid learning and long-term stability.

Original languageEnglish
Title of host publicationProceedings of the 21st Innovative Applications of Artificial Intelligence Conference, IAAI-09
Pages165-172
Number of pages8
StatePublished - 2009
Externally publishedYes
Event21st Innovative Applications of Artificial Intelligence Conference, IAAI-09 - Pasadena, CA, United States
Duration: 14 Jul 200916 Jul 2009

Publication series

NameProceedings of the 21st Innovative Applications of Artificial Intelligence Conference, IAAI-09

Conference

Conference21st Innovative Applications of Artificial Intelligence Conference, IAAI-09
Country/TerritoryUnited States
CityPasadena, CA
Period14/07/0916/07/09

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