Charles Jorgensen

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Sub-auditory speech recognition using electromyogram (EMG) sensors is potentially useful for interfaces in noisy environments, for discreet or secure communications, and for users with speech related disabilities. Past research has shown that a scaled conjugate gradient neural network, using dual tree wavelets for feature transformation, can categorize EMG(More)
This paper describes a prototype system designed to improve first responder situational awareness at emergency scenes. A high degree of situational awareness, both for individual responders and for incident commanders, helps to increase responder safety and improve scene management. The prototype system makes use of a variety of tools and techniques from(More)
1. Extended Abstract Speech intelligibility can be severely degraded by high levels of acoustic noise. Researchers have developed a variety of techniques to minimize the impact of noise, ranging from adaptive noise cancellation to throat microphones. Increasingly, researchers are experimenting with the measurement and analysis of bioelectric signals(More)
This paper presents results of a recent experiment in fine grain Electromyographic (EMG) signal recognition. We demonstrate bioelectric flight control of 757 class simulation aircraft landing at San Francisco International Airport. The physical instrumentality of a pilot control stick is not used. A pilot closes a fist in empty air and performs control(More)
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