%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 }