Proceedings of the IEEE · 2015 · 182 citations · 37 references
EngineeringRehabilitation MedicineRobotics EngineeringAssistive TechnologyNeurorehabilitationRoboticsAssistive RoboticsBrain-computer InterfacesRehabilitation RoboticsShared ControlTeleoperationTelepresence RoboticsIndependenceMatched Control GroupRemote Assistance TechnologiesRemote NavigationShared Control In Brain-computer InterfacesTelepresence RobotsTelerehabilitationWorkload
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.
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