Noninvasive Brain–Machine Interfaces for Robotic Devices

Author:

Tonin Luca1,Millán José del R.2

Affiliation:

1. Intelligent Autonomous Systems Laboratory, Department of Information Engineering, Università degli Studi di Padova, 35122 Padova, Italy;

2. Department of Electrical and Computer Engineering and Department of Neurology, The University of Texas at Austin, Austin, Texas 78712, USA;

Abstract

The last decade has seen a flowering of applications driven by brain–machine interfaces (BMIs), particularly brain-actuated robotic devices designed to restore the independence of people suffering from severe motor disabilities. This review provides an overview of the state of the art of noninvasive BMI-driven devices based on 86 studies published in the last 15 years, with an emphasis on the interactions among the user, the BMI system, and the robot. We found that BMIs are used mostly to drive devices for navigation (e.g., telepresence mobile robots), with BMI paradigms based mainly on exogenous stimulation, and the majority of brain-actuated robots adopt a discrete control strategy. Most critically, in only a few works have disabled people evaluated a brain-actuated robot. The review highlights the most urgent challenges in the field, from the integration between BMI and robotics to the need for a user-centered design to boost the translational impact of BMIs.

Publisher

Annual Reviews

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