AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Communication Devices for People with Disabilities

Showing 21 to 30 of 35 articles

Clear Filters

Joint Dictionary Learning-Based Non-Negative Matrix Factorization for Voice Conversion to Improve Speech Intelligibility After Oral Surgery.

IEEE transactions on bio-medical engineering
This paper focuses on machine learning based voice conversion (VC) techniques for improving the speech intelligibility of surgical patients who have had parts of their articulators removed. Because of the removal of parts of the articulator, a patie...

Regularized Speaker Adaptation of KL-HMM for Dysarthric Speech Recognition.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This paper addresses the problem of recognizing the speech uttered by patients with dysarthria, which is a motor speech disorder impeding the physical production of speech. Patients with dysarthria have articulatory limitation, and therefore, they of...

Representation Learning Based Speech Assistive System for Persons With Dysarthria.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
An assistive system for persons with vocal impairment due to dysarthria converts dysarthric speech to normal speech or text. Because of the articulatory deficits, dysarthric speech recognition needs a robust learning technique. Representation learnin...

Performing mathematics activities with non-standard units of measurement using robots controlled via speech-generating devices: three case studies.

Disability and rehabilitation. Assistive technology
Purpose To examine how using a Lego robot controlled via a speech-generating device (SGD) can contribute to how students with physical and communication impairments perform hands-on and communicative mathematics measurement activities. This study was...

Improving zero-training brain-computer interfaces by mixing model estimators.

Journal of neural engineering
OBJECTIVE: Brain-computer interfaces (BCI) based on event-related potentials (ERP) incorporate a decoder to classify recorded brain signals and subsequently select a control signal that drives a computer application. Standard supervised BCI decoders ...

Real-Time Control of an Articulatory-Based Speech Synthesizer for Brain Computer Interfaces.

PLoS computational biology
Restoring natural speech in paralyzed and aphasic people could be achieved using a Brain-Computer Interface (BCI) controlling a speech synthesizer in real-time. To reach this goal, a prerequisite is to develop a speech synthesizer producing intelligi...

Training and testing ERP-BCIs under different mental workload conditions.

Journal of neural engineering
OBJECTIVE: As one of the most popular and extensively studied paradigms of brain-computer interfaces (BCIs), event-related potential-based BCIs (ERP-BCIs) are usually built and tested in ideal laboratory settings in most existing studies, with subjec...

User Adaptive Text Predictor for Mentally Disabled Huntington's Patients.

Computational intelligence and neuroscience
This paper describes in detail the design of the specialized text predictor for patients with Huntington's disease. The main aim of the specialized text predictor is to improve the text input rate by limiting the phrases that the user can type in. We...

Using robots in "Hands-on" academic activities: a case study examining speech-generating device use and required skills.

Disability and rehabilitation. Assistive technology
PURPOSE: A 12-year-old girl, Emily, with complex communication needs and severe physical limitations, controlled a Lego robot from a speech-generating device (SGD) to do various "hands-on" academic activities. Emily's teacher and assistive technology...

An SSVEP-Based Brain-Computer Interface for Text Spelling With Adaptive Queries That Maximize Information Gain Rates.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This paper presents a brain-computer interface for text entry using steady-state visually evoked potentials (SSVEP). Like other SSVEP-based spellers, ours identifies the desired input character by posing questions (or queries) to users through a visu...