title: Unstable Morse code recognition with adaptive variable-ratio threshold prediction for physically disabled persons.
abstract: With one or two switches, Morse code could provide an effective alternative communication channel for individuals with physical limitations. However, most of the physically disabled persons have difficulties in maintaining a stable typing of Morse code, and hence the automated recognition of unstable Morse code is becoming more on demand. In this study, an adaptive variable-ratio threshold prediction (AVRTP) algorithm is proposed to analyze the Morse code time series with variable unit time period and ratio. Two least-mean-square (LMS) predictors are applied to track the dot interval and the dot-dash difference concurrently, and then a predicted threshold based on a variable-ratio decision rule is used to distinguish between dots and dashes. The same method is also applied to identify character-spaces. By the adaptive prediction of variable-ratio threshold, AVRTP has successfully overcome the difficulty of analyzing severely unstable Morse code time series and outperformed the previously proposed adaptive unstable-speed prediction (AUSP) algorithm and LMS and matching (I,MS&M) algorithm. This study concludes with a computer simulation and a preliminary clinical evaluation that demonstrate AVRTP as an efficient and reliable method for unstable Morse code recognition.
authors.affiliation: Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan, ROC.
authors.forename: M C
authors.initials: MC
authors.lastname: Hsieh
authors.forename: C H
authors.initials: CH
authors.lastname: Luo
authors.forename: C W
authors.initials: CW
authors.lastname: Mao
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D015982:Bias; D003143:Communication Devices for People with Disabilities; D003198:Computer Simulation; D003663:Decision Trees; D006233:Persons with Disabilities / Q000534:rehabilitation*; D005246:Feedback; D006801:Humans; D009716:Numerical Analysis, Computer-Assisted; D010363:Pattern Recognition, Automated; D011237:Predictive Value of Tests; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors; D014584:User-Computer Interface