Towards independence: a BCI telepresence robot for people with severe motor disabilities
This paper presents an important step forward towards increasing the independence of people with severe motor disabilities, by using brain-computer interfaces to harness the power of the Internet of Things. We analyze the stability of brain signals as end-users with motor disabilities progress from...
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| Main Authors: | , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
May 18, 2015
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| In: |
Proceedings of the IEEE
Year: 2015, Volume: 103, Issue: 6, Pages: 969-982 |
| ISSN: | 1558-2256 |
| DOI: | 10.1109/JPROC.2015.2419736 |
| Online Access: | Resolving-System, lizenzpflichtig, Volltext: https://doi.org/10.1109/JPROC.2015.2419736 Verlag, lizenzpflichtig, Volltext: https://ieeexplore.ieee.org/document/7109829 
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| Author Notes: | Robert Leeb, Luca Tonin, Martin Rohm, Lorenzo Desideri, Tom Carlson, and José del R. Millán |
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| 520 | |a This paper presents an important step forward towards increasing the independence of people with severe motor disabilities, by using brain-computer interfaces to harness the power of the Internet of Things. We analyze the stability of brain signals as end-users with motor disabilities progress from performing simple standard on-screen training tasks to interacting with real devices in the real world. Furthermore, we demonstrate how the concept of shared control-which interprets the user's commands in context-empowers users to perform rather complex tasks without a high workload. We present the results of nine end-users with motor disabilities who were able to complete navigation tasks with a telepresence robot successfully in a remote environment (in some cases in a different country) that they had never previously visited. Moreover, these end-users achieved similar levels of performance to a control group of 10 healthy users who were already familiar with the environment. | ||
| 650 | 4 | |a Application control | |
| 650 | 4 | |a BCI telepresence robot | |
| 650 | 4 | |a brain signal stability analysis | |
| 650 | 4 | |a brain-computer interface (BCI) | |
| 650 | 4 | |a complex tasks | |
| 650 | 4 | |a Computer interfaces | |
| 650 | 4 | |a control group | |
| 650 | 4 | |a electroencephalogram (EEG) | |
| 650 | 4 | |a end-users with motor disabilities | |
| 650 | 4 | |a handicapped aids | |
| 650 | 4 | |a healthy users | |
| 650 | 4 | |a Internet of Things | |
| 650 | 4 | |a Medical robots | |
| 650 | 4 | |a Mobile robots | |
| 650 | 4 | |a motor disabilities | |
| 650 | 4 | |a motor imagery | |
| 650 | 4 | |a navigation tasks | |
| 650 | 4 | |a Performance evaluation | |
| 650 | 4 | |a performance levels | |
| 650 | 4 | |a real device interaction | |
| 650 | 4 | |a remote environment | |
| 650 | 4 | |a Robot sensing systems | |
| 650 | 4 | |a robotic device | |
| 650 | 4 | |a severe motor disabled people | |
| 650 | 4 | |a shared control | |
| 650 | 4 | |a standard on-screen training tasks | |
| 650 | 4 | |a telepresence | |
| 650 | 4 | |a telerobotics | |
| 650 | 4 | |a user commands | |
| 650 | 4 | |a user workload | |
| 650 | 4 | |a Wheelchairs | |
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