Shared Control Brain Computer Interfaces
Author: Ian C. Langtree - Writer/Editor for Disabled World (DW)
Published: 2011/02/17 - Updated: 2026/01/15
Publication Type: Informative
Category Topic: Electronics - Software - Related Publications
Page Content: Synopsis - Introduction - Main - Insights, Updates
Synopsis: This information examines how brain-computer interface technology is becoming more practical for people with limited mobility through shared control systems that reduce mental fatigue. Developed by researchers at Switzerland's Ecole Polytechnique Federale de Lausanne, these systems use probability theory and statistical analysis to decode EEG signals more efficiently, letting users mentally relax and perform secondary tasks simultaneously - something impossible with earlier BCI designs that demanded constant concentration. The research shows real-world applicability, as demonstrated at the 2011 AAAS meeting, making the work particularly relevant to individuals with paralysis or severe mobility impairments who need assistive devices they can operate throughout the day without exhaustion - Disabled World (DW).
- Definition: Shared Control Brain Computer Interface
A Shared Control Brain Computer Interface is a system that splits decision-making responsibilities between the user's brain signals and automated assistive controls, rather than demanding that the user maintain conscious control over every movement. Instead of requiring someone to mentally command every action - say, steering a wheelchair left, right, or straight - the interface uses sensors and image processing to handle obstacle detection and basic navigation automatically, while the user focuses only on high-level intentions like "move toward that door." This hybrid approach works by having the system learn to interpret EEG readings from the scalp and distinguish between intentional commands and background brain activity, which means users can take mental breaks and even multitask without losing control. The practical benefit is massive: someone using a brain-powered wheelchair can actually make it through an airport without burning out after an hour, because the technology does the heavy cognitive lifting on routine tasks while the user reserves mental energy for strategic decisions.
Introduction
Brain-machine interfaces make gains by learning about their users, letting them rest, and allowing for multitasking. You may have heard of virtual keyboards controlled by thought, brain-powered wheelchairs, and neuro-prosthetic limbs. But powering these machines can be downright tiring, a fact that prevents the technology from being of much use to people with disabilities, among others. Professor Jose del R. Millan and his team at the Ecole Polytechnique Federale de Lausanne (EPFL) in Switzerland have a solution: engineer the system so that it learns about its user, allows for periods of rest, and even multitasking.
Main Content
In a typical brain-computer interface (BCI) set-up, users can send one of three commands - left, right, or no-command. No-command is the static state between left and right and is necessary for a brain-powered wheelchair to continue going straight, for example, or to stay put in front of a specific target. But it turns out that no-command is very taxing to maintain and requires extreme concentration. After about an hour, most users are spent. Not much help if you need to maneuver that wheelchair through an airport.
In an ongoing study demonstrated by Millan and doctoral student Michele Tavella at the AAAS 2011 Annual Meeting in Washington, D.C., the scientists hook volunteers up to BCI and ask them to read, speak, or read aloud while delivering as many left and right commands as possible or delivering a no-command. By using statistical analysis programmed by the scientists, Millan's BCI can distinguish between left and right commands and learn when each subject is sending one of these vs. a no-command. In other words, the machine learns to read the subject's mental intention. The result is that users can mentally relax and also execute secondary tasks while controlling the BCI.
The so-called Shared Control approach to facilitating human-robot interactions employs image sensors and image-processing to avoid obstacles. According to Millan, however, Shared Control isn't enough to let an operator rest or concentrate on more than one command at once, limiting long-term use.
Millan's new work complements research on Shared Control and makes multitasking a reality while at the same time allows users to catch a break. His trick is in decoding the signals coming from EEG readings on the scalp, readings that represent the activity of millions of neurons and have notoriously low resolution. By incorporating statistical analysis, or probability theory, his BCI allows for both targeted control maneuvering around an obstacle and more precise tasks, such as staying on a target. It also makes it easier to give simple commands like "go straight" that need to be executed over longer periods of time (think back to that airport) without having to focus on giving the same command over and over again.
It will be awhile before this cutting-edge technology makes the move from lab to production line, but Millan's prototypes are the first working models of their kind to use probability theory to make BCIs easier to use over time.
His next step is to combine this new level of sophistication with Shared Control in an ongoing effort to take BCI to the next level, necessary for widespread use.
Further advancements, such as finer grained interpretation of cognitive information, are being developed together with the European project for Tools for Brain Computer. The multinational project is headed by Professor Millan and has moved into the clinical testing phase for several BCIs.
Insights, Analysis, and Developments
Editorial Note: While brain-computer interfaces have moved considerably forward since 2011, the core insight from Millan's research remains crucial: technology designed for people with disabilities must account for human fatigue and cognitive load, not just raw functionality. The shift toward systems that work with our natural mental limitations rather than against them represents a maturity in assistive technology philosophy that should inform how all accessibility tools are engineered. As BCIs continue advancing toward clinical use, this principle of sustainable human-computer interaction may prove as important as the technical breakthroughs themselves - Disabled World (DW).
Author Credentials: Ian is the founder and Editor-in-Chief of Disabled World, a leading resource for news and information on disability issues. With a global perspective shaped by years of travel and lived experience, Ian is a committed proponent of the Social Model of Disability-a transformative framework developed by disabled activists in the 1970s that emphasizes dismantling societal barriers rather than focusing solely on individual impairments. His work reflects a deep commitment to disability rights, accessibility, and social inclusion. To learn more about Ian's background, expertise, and accomplishments, visit his full biography.