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Human-Computer Interface & Assistive Technology Efforts at

Human-Computer Interface & Assistive Technology Efforts at. FLORIDA INTERNATIONAL UNIVERSITY. HCI/Assistive Technology for individuals with motor disabilities EMG-driven HCI (hands-off) EMG-EGT-driven HCI (hands-off). Center For Advanced Technology and Education (CATE)

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Human-Computer Interface & Assistive Technology Efforts at

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  1. Human-Computer Interface &Assistive Technology Efforts at FLORIDA INTERNATIONAL UNIVERSITY • HCI/Assistive Technology for individuals with motor disabilities • EMG-driven HCI (hands-off) • EMG-EGT-driven HCI (hands-off) Center For Advanced Technology and Education (CATE) Dr. Malek Adjouadi • HCI/Assistive Technology for individuals with visual impairments • On-screen deconvolution • Icons w/ Spatialized sound Digital Signal Processing Laboratory Dr. Armando Barreto • Assistive Technology for individuals with auditory impairments • Visual Feedback Tool for speech training • * Spectrogram * Articulation Index Human-Computer Interface Laboratory – Georgia Tech Dr. Julie Jacko

  2. HCI/AT for individuals with motor disabilities • Objective: Hands-off interaction with standard GUI • Electromyogram (EMG)-driven interface • 3 electrodes in a headband detect EMG. System translates voluntary contraction of facial muscles into cursor STEPS (up, down, left, right). • EMG & Eye-Gaze Tracking (EGT)-driven interface • EGT system moves the cursor to user’s point of gaze on screen, for quick, long displacements. EMG system used for fine-tuning cursor position, and clicking.

  3. HCI/AT for individuals with visual disabilities • Characterization of functional limitations for different eye pathologies • Impaired cursor positioning in low-vision users • Overshoot location of icons • Lack of visual feedback • Substitute with spatialized auditory feedback, using Head-Related Transfer Functions (HRTF) • Developments towards customization of HRTFs

  4. Ideal Speaker Real Channel Listener Noise Imperfect Speech Real Speaker Ideal Channel Listener Noise Imperfect Speech AT for individuals with auditory disabilities • Visual Speech Training Tool for deaf individuals • Provide VISUAL feedback to substitute the auditory feedback hearing individuals use during speech learning (trial & error) • Comparison of Spectrograms (Model vs. Trial) • Does not directly address intelligibility • Comparison of “Articulation Index” * (Model vs. Trial) * Originally, for estimation of speech intelligibility over a known communications channel

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