Tongue-Supported Human-Computer Interaction Systems: A Review
Access Status
Authors
Date
2014Type
Metadata
Show full item recordCitation
Source Title
Source Conference
ISBN
School
Remarks
Copyright © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Collection
Abstract
The tongue can substitute human sensory systems and has been used as a medium of input to help impaired patients communicate with the world. Innovative techniques have been employed to realize tongue movement, sense its position and exploit tongue dexterity, in order to achieve Tongue Supported Human Computer Interaction (TSHCI). This paper examines various approaches of using tongue dexterousness in TSHCI systems and introduces two infrared signal supported minimally-invasive TSHCI systems developed at Curtin University. Methods of sensing tongue movement andposition are especially discussed and depending on the employed methods, TSHCI systems are categorized as either invasive or minimally-invasive. A set of system usability criteria is proposed to help build more effective TSHCI systems in future.
Related items
Showing items related by title, author, creator and subject.
-
Khan, Masood ; Smart, Sharon; Bogaardt, Hans; Junaid, Zubairi; Svetlana, Yanushkevich (2024)A Tongue-Machine Interaction System (TMIS) can serve as a valuable tool for tongue strengthening training which could contribute to rehabilitation of patients with dysphagia and eventually help in mending the oropharyngeal ...
-
Khan, Masood Mehmood; Quain, R. (2014)Tongue supported human-computer interaction (TSHCI) systems can help critically ill patients interact with both computers and people. These systems can be particularly useful for patients suffering injuries above C7 on ...
-
Siddiqui, Aniqa Azeem (2021)This thesis reports a novel approach to translate tongue voluntary motion data into user-specific parametric tongue position models which are then used to train a classifier. The classifier is then tested to localise ...