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Introduction: Universally established comprehensive clinical bulbar scales objectively assessing disease progression in amyotrophic lateral sclerosis (ALS) are currently lacking. The goal of this working group project is to design a best practice set of provisional bulbar ALS guidelines, available for immediate implementation within all ALS clinics. Methods: ALS specialists across multiple related...
Amytrophic lateral sclerosis (ALS) is an incurable neurodegenerative disease. Difficulty articulating speech, dysarthria, is a common early symptom of ALS. Detecting dysarthria currently requires manual analysis of several different speech tasks by pathology experts. This is time consuming and can lead to misdiagnosis. Many existing automatic classification approaches require manually preprocessing...
Recent research has demonstrated the potential of using an articulation-based silent speech interface for command-and-control systems. Such an interface converts articulation to words that can then drive a text-to-speech synthesizer. In this paper, we have proposed a novel near-time algorithm to recognize whole-sentences from continuous tongue and lip movements. Our goal is to assist persons who are...
A novel approach was developed to recognize vowels from continuous tongue and lip movements. Vowels were classified based on movement patterns (rather than on derived articulatory features, e.g., lip opening) using a machine learning approach. Recognition accuracy on a single-speaker dataset was 94.02% with a very short latency. Recognition accuracy was better for high vowels than for low vowels....
This longitudinal investigation examines developmental changes in orofacial movements occurring during the early stages of communication development. The goals were to identify developmental trends in early speech motor performance and to determine how these trends differ across orofacial behaviors thought to vary in cognitive and linguistic demands (i.e., silent spontaneous movements, babble, and...
In this paper we describe a computer vision-based 3D hand tracking system for a multimodal augmented reality (AR) interface. We have developed a 3D vision-based natural hand interaction method. This consists of four steps: (1) skin colour segmentation, (2) feature point finding, (3) hand direction calculation, and (4) simple collision detection based on a short finger ray for interaction between the...
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