The role of shared-control in BCI-based telepresence

Tonin, Luca; Leeb, Robert; Tavella, Michele; Perdikis, Serafeim; Millán, José del R.

doi:10.1109/icsmc.2010.5642338

Cited by 100 publications

(92 citation statements)

References 13 publications

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“…This is achieved by a system known as shared control, which takes the environmental context into account when interpreting the user's commands. It decides exactly when and how far to turn, and whether to avoid or dock to the obstacles it encounters along the way [8], [16].…”

Section: A the Telepresence Platformmentioning

confidence: 99%

“…Nevertheless, complex robotic devices have been successfully and reliably controlled by such BCIs, by exploiting smart interaction designs, such as shared control [12], [13], [14], [15]. Millán's group has pioneered the use of shared control in neuroprosthetics, by taking the continuous estimation of the user's intentions and providing appropriate assistance to execute tasks safely and reliably [1], [2], [16]. Furthermore, thanks to the mutual learning approach, where the user and the BCI are coupled together and adapt to each other, end-users are able to learn to operate brain-actuated devices relatively quickly (typically in a matter of hours spread across few days [8], [3], [17], [18]).…”

Section: Introductionmentioning

confidence: 99%

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A hybrid BCI for enhanced control of a telepresence robot

Carlson¹,

Tonin²,

Perdikis³

et al. 2013

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Abstract-Motor-disabled end users have successfully driven a telepresence robot in a complex environment using a BrainComputer Interface (BCI). However, to facilitate the interaction aspect that underpins the notion of telepresence, users must be able to voluntarily and reliably stop the robot at any moment, not just drive from point to point. In this work, we propose to exploit the user's residual muscular activity to provide a fast and reliable control channel, which can start/stop the telepresence robot at any moment. Our preliminary results show that not only does this hybrid approach increase the accuracy, but it also helps to reduce the workload and was the preferred control paradigm of all the participants.

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Section: A the Telepresence Platformmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A hybrid BCI for enhanced control of a telepresence robot

Carlson¹,

Tonin²,

Perdikis³

et al. 2013

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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“…BCI robots are categorized into two main classes as mobile robots and brain-controlled manipulators [12]. Recently due to the development in brain computer interface mobile robots have gain the attention of most researchers due to their ability to transport disabled people [13] [14] but at the same time these mobile robots require higher safety as they are designed to provide transportation for disabled people. To implement these robots in real life much higher accuracy is required.…”

Section: Introductionmentioning

confidence: 99%

Eye Controlled Mobile Robot with Shared Control for Physically Impaired People

Wasim¹,

Khan²,

Saeed³

et al. 2017

ijacsa

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Abstract-Physically impaired and disabled people are an integral part of human society. Devices providing assistance to such individuals can help them contribute to the society in a more productive way. The situation is even worse for patients with locked-in syndrome who cannot move their body at all. These problems were the motivation to develop an eye controlled robot to facilitate such patients. Readily available commercial headset is used to record electroencephalogram (EEG) signals for classification and processing. Classification based control signals were then transmitted to robot for navigation. The robot mimics a brain controlled wheelchair with eye movements. The robot is based on shared control which is safe and robust. The analysis of robot navigation for patients showed promising results.

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“…Recently, Tavella et al [48] demonstrated that healthy subjects can mentally control a non-invasive BCI-controlled neuroprosthesis for the restoration of grasping while performing a handwriting task. Tonin et al [49] showed how users and Carlson et al [2] how patients can mentally control a telepresence robot via the BCI to perform a navigation task in daily environments. All experiments give a short glimpse of the idea that users can successfully perform BCI control, which can be superimposed on a secondary task.…”

Section: Introductionmentioning

confidence: 99%

Thinking Penguin: Multimodal Brain–Computer Interface Control of a VR Game

Leeb

Lancelle

Kaiser

et al. 2013

IEEE Trans. Comput. Intell. AI Games

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Abstract-We describe a multi-modal brain-computer interface (BCI) experiment, situated in a highly immersive CAVE. A subject sitting in the virtual environment controls the main character of a virtual reality game: a penguin that slides down a snowy mountain slope. While the subject can trigger a jump action via the BCI, additional steering with a game controller as a secondary task was tested. Our experiment profits from the game as an attractive task where the subject is motivated to get a higher score with a better BCI performance. A BCI based on the so-called brain-switch was applied, which allows discrete asynchronous actions. Fourteen subjects participated, of which 50 % achieved the required performance to test the penguin game. Comparing the BCI performance during the training and the game showed that a transfer of skills is possible, in spite of the changes in visual complexity and task demand. Finally and most importantly, our results showed that the use of a secondary motor task, in our case the joystick control, did not deteriorate the BCI performance during the game. Through these findings, we conclude that our chosen approach is a suitable multi-modal or hybrid BCI implementation, in which the user can even perform other tasks in parallel.

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The role of shared-control in BCI-based telepresence

Cited by 100 publications

References 13 publications

A hybrid BCI for enhanced control of a telepresence robot

A hybrid BCI for enhanced control of a telepresence robot

Eye Controlled Mobile Robot with Shared Control for Physically Impaired People

Thinking Penguin: Multimodal Brain–Computer Interface Control of a VR Game

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