Real-time implementation of a non-invasive tongue-based human-robot interface
IROS(2010)
Abstract
Real-time implementation of an assistive human-machine interface system based around tongue-movement ear pressure (TMEP) signals is presented, alongside results from a series of simulated control tasks. The implementation of this system into an online setting involves short-term energy calculation, detection, segmentation and subsequent signal classification, all of which had to be reformulated based on previous off-line testing. This has included the formulation of a new classification and feature extraction method. This scheme utilises the discrete cosine transform to extract the frequency features from the time domain information, a univariate Gaussian maximum likelihood classifier and a two phase cross-validation procedure for feature selection and extraction. The performance of this classifier is presented alongside a real-time implementation of the decision fusion classification algorithm, with each achieving 96.28% and 93.12% respectively. The system testing takes into consideration potential segmentation of false positive signals. A simulation mapping commands to a planar wheelchair demonstrates the capacity of the system for assistive robotic control. These are the first real-time results published for a tongue-based human-machine interface that does not require a transducer to be placed within the vicinity of the oral cavity.
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Key words
real-time classification,robotic control,discrete cosine transform,human-robot interaction,gaussian maximum likelihood classifier,maximum likelihood estimation,human-machine interface,cross-validation procedure,pattern classification,assistive hmi,tongue-movement ear pressure signals,discrete cosine transforms,short term energy calculation,feature extraction,gaussian processes,signal classification,time domain information,frequency feature,classification,decision fusion classification,feature selection,handicapped aids,tongue movement ear pressure,false positive,human machine interface,robot control,real time systems,accuracy,time domain,cross validation,real time,human robot interface,human robot interaction
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