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A Learning Scheme for EMG Based Interfaces: On Task Specificity in Motion Decoding Domain

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Neuro-Robotics

Part of the book series: Trends in Augmentation of Human Performance ((TAHP,volume 2))

Abstract

A complete learning scheme for EMG based interfaces is used to discriminate between different reach to grasp movements in 3D space. The proposed scheme is able to decode human kinematics, using the myoelectric activity captured from human upper arm and forearm muscles. Three different task features can be distinguished: subspace to move towards, object to be grasped and task to be executed (with the grasped object). The discrimination between the different reach to grasp movements is accomplished with a random forest classifier. The classification decision triggers task-specific motion decoding models that outperform “general” models, providing better estimation accuracy. The proposed learning scheme takes advantage of both a classifier and a regressor, that cooperate advantageously in order to split the space, confronting with task specificity, the nonlinear relationship between the EMG signals and the motion to be estimated. The proposed scheme can be used for a series of EMG-based interfaces, ranging from EMG based teleoperation of robot arm hand systems to muscle computer interfaces and EMG controlled neuroprosthetic devices.

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Author information

Authors and Affiliations

  1. National Technical University of Athens, Athina, Greece

    Minas Liarokapis & Kostas J. Kyriakopoulos

  2. School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ, 85287, USA

    Panagiotis Artemiadis

Authors
  1. Minas Liarokapis
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  2. Kostas J. Kyriakopoulos
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  3. Panagiotis Artemiadis
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Corresponding author

Correspondence to Minas Liarokapis .

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Editors and Affiliations

  1. School for Engineering of Matter, Transport and Energy, Arizona State University, Tempe, Arizona, USA

    Panagiotis Artemiadis

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Liarokapis, M., Kyriakopoulos, K.J., Artemiadis, P. (2014). A Learning Scheme for EMG Based Interfaces: On Task Specificity in Motion Decoding Domain. In: Artemiadis, P. (eds) Neuro-Robotics. Trends in Augmentation of Human Performance, vol 2. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-8932-5_1

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