Morse code is now being harnessed for use in rehabilitation applications of augmentative-alternative communication and assistive technology, including mobility, environmental control and adapted worksite access. In this paper, Morse code is selected as a communication adaptive device for disabled persons who suffer from muscle atrophy, cerebral palsy or other severe handicaps. A stable typing rate is strictly required for Morse code to be effective as a communication tool. This restriction is a major hindrance. Therefore, a switch adaptive automatic recognition method with a high recognition rate is needed. The proposed system combines counter-propagation networks with a variable degree variable step size LMS algorithm. It is divided into five stages: space recognition, tone recognition, learning process, adaptive processing, and character recognition. Statistical analyses demonstrated that the proposed method elicited a better recognition rate in comparison to alternative methods in the literature.
%0 Journal Article
%1 Yang2004
%A Yang, Cheng-Huei
%A Luo, Ching-Hsing
%A Yang, Cheng-Hong
%A Chuang, Li-Yeh
%D 2004
%J Biomed Mater Eng
%K Adult; Algorithms; Artificial Intelligence; Cerebral Palsy; Communication Aids for Disabled; Female; Humans; Male; Neural Networks (Computer); Pattern Recognition, Automated; Signal Processing, Computer-Assisted; User-Computer Interface; Word Processing
%N 1
%P 23--32
%T Counter-propagation network with variable degree variable step size LMS for single switch typing recognition.
%V 14
%X Morse code is now being harnessed for use in rehabilitation applications of augmentative-alternative communication and assistive technology, including mobility, environmental control and adapted worksite access. In this paper, Morse code is selected as a communication adaptive device for disabled persons who suffer from muscle atrophy, cerebral palsy or other severe handicaps. A stable typing rate is strictly required for Morse code to be effective as a communication tool. This restriction is a major hindrance. Therefore, a switch adaptive automatic recognition method with a high recognition rate is needed. The proposed system combines counter-propagation networks with a variable degree variable step size LMS algorithm. It is divided into five stages: space recognition, tone recognition, learning process, adaptive processing, and character recognition. Statistical analyses demonstrated that the proposed method elicited a better recognition rate in comparison to alternative methods in the literature.
@article{Yang2004,
abstract = {Morse code is now being harnessed for use in rehabilitation applications of augmentative-alternative communication and assistive technology, including mobility, environmental control and adapted worksite access. In this paper, Morse code is selected as a communication adaptive device for disabled persons who suffer from muscle atrophy, cerebral palsy or other severe handicaps. A stable typing rate is strictly required for Morse code to be effective as a communication tool. This restriction is a major hindrance. Therefore, a switch adaptive automatic recognition method with a high recognition rate is needed. The proposed system combines counter-propagation networks with a variable degree variable step size LMS algorithm. It is divided into five stages: space recognition, tone recognition, learning process, adaptive processing, and character recognition. Statistical analyses demonstrated that the proposed method elicited a better recognition rate in comparison to alternative methods in the literature.},
added-at = {2014-07-20T09:29:52.000+0200},
author = {Yang, Cheng-Huei and Luo, Ching-Hsing and Yang, Cheng-Hong and Chuang, Li-Yeh},
biburl = {https://www.bibsonomy.org/bibtex/27a0091343381e5d1136a611e4279364a/ar0berts},
groups = {public},
interhash = {0857ec11cdc8081db1307aac1905026f},
intrahash = {7a0091343381e5d1136a611e4279364a},
journal = {Biomed Mater Eng},
keywords = {Adult; Algorithms; Artificial Intelligence; Cerebral Palsy; Communication Aids for Disabled; Female; Humans; Male; Neural Networks (Computer); Pattern Recognition, Automated; Signal Processing, Computer-Assisted; User-Computer Interface; Word Processing},
number = 1,
pages = {23--32},
pmid = {14757950},
timestamp = {2014-07-20T09:29:52.000+0200},
title = {Counter-propagation network with variable degree variable step size LMS for single switch typing recognition.},
username = {ar0berts},
volume = 14,
year = 2004
}