Decoding Onset and Direction of Movements Using Electrocorticographic (ECoG) Signals in Humans

Abstract

Communication of intent usually requires motor function. This requirement can be limiting when a person is engaged in a task, or prohibitive for some people suffering from neuromuscular disorders. Determining a person's intent, e.g., where and when to move, from brain signals rather than from muscles would have important applications in clinical or other domains. For example, detection of the onset and direction of intended movements may provide the basis for restoration of simple grasping function in people with chronic stroke, or could be used to optimize a user's interaction with the surrounding environment. Detecting the onset and direction of actual movements are a first step in this direction. In this study, we demonstrate that we can detect the onset of intended movements and their direction using electrocorticographic (ECoG) signals recorded from the surface of the cortex in humans. We also demonstrate in a simulation that the information encoded in ECoG about these movements may improve performance in a targeting task. In summary, the results in this paper suggest that detection of intended movement is possible, and may serve useful functions.

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Document Details

Document Type
Technical Report
Publication Date
Aug 08, 2012
Accession Number
ADA574168

Entities

People

  • Anthony L. Ritaccio
  • Aysegul Gunduz
  • Gerwin Schalk
  • Peter Brunner
  • Qiang Ji
  • Zuoguan Wang

Organizations

  • Albany Medical College

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Bayesian Networks
  • Brain
  • Computational Science
  • Computers
  • Decoding
  • Detection
  • Diseases And Disorders
  • Frequency
  • Health Services
  • Human-Machine Interaction
  • Information Processing
  • Information Science
  • Machine Learning
  • Neural Networks
  • Prosthetics
  • Supervised Machine Learning

Readers

  • Image Processing and Computer Vision.
  • Instructional Design and Training Evaluation.
  • Neuroscience