Real-time implementation of a non-invasive tongue-based human-robot interface

Mace, M., Mamun, K., Vaidyanathan, R., Wang, S. and Gupta, L. (2010) Real-time implementation of a non-invasive tongue-based human-robot interface. In 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE. p. 5486 . (doi:10.1109/IROS.2010.5648834).

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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