AI Medical Compendium Topic

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

Communication Devices for People with Disabilities

Showing 11 to 20 of 35 articles

Clear Filters

On the localness modeling for the self-attention based end-to-end speech synthesis.

Neural networks : the official journal of the International Neural Network Society
Attention based end-to-end speech synthesis achieves better performance in both prosody and quality compared to the conventional "front-end"-"back-end" structure. But training such end-to-end framework is usually time-consuming because of the use of ...

Modeling engagement in long-term, in-home socially assistive robot interventions for children with autism spectrum disorders.

Science robotics
Socially assistive robotics (SAR) has great potential to provide accessible, affordable, and personalized therapeutic interventions for children with autism spectrum disorders (ASD). However, human-robot interaction (HRI) methods are still limited in...

Visual P300 Mind-Speller Brain-Computer Interfaces: A Walk Through the Recent Developments With Special Focus on Classification Algorithms.

Clinical EEG and neuroscience
Brain-computer interfaces are sophisticated signal processing systems, which directly operate on neuronal signals to identify specific human intents. These systems can be applied to overcome certain disabilities or to enhance the natural capabilities...

Improving Performance of Devanagari Script Input-Based P300 Speller Using Deep Learning.

IEEE transactions on bio-medical engineering
The performance of an existing Devanagari script (DS) input-based P300 speller with conventional machine learning techniques suffers from low information transfer rate (ITR). This occurs due to its required large size of display, i.e., 8 × 8 row-colu...

Speech synthesis from ECoG using densely connected 3D convolutional neural networks.

Journal of neural engineering
OBJECTIVE: Direct synthesis of speech from neural signals could provide a fast and natural way of communication to people with neurological diseases. Invasively-measured brain activity (electrocorticography; ECoG) supplies the necessary temporal and ...

On the Relative Contribution of Deep Convolutional Neural Networks for SSVEP-Based Bio-Signal Decoding in BCI Speller Applications.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Brain-computer interfaces (BCI) harnessing steady state visual evoked potentials (SSVEPs) manipulate the frequency and phase of visual stimuli to generate predictable oscillations in neural activity. For BCI spellers, oscillations are matched with al...

Speech Technology Progress Based on New Machine Learning Paradigm.

Computational intelligence and neuroscience
Speech technologies have been developed for decades as a typical signal processing area, while the last decade has brought a huge progress based on new machine learning paradigms. Owing not only to their intrinsic complexity but also to their relatio...

Evaluation of a companion robot based on field tests with single older adults in their homes.

Assistive technology : the official journal of RESNA
The growing number of older adults places insurmountable load on family members and professional caregivers. Assistive technology with the aid of robots can present a possible solution. The goal of this article was to test a companion robot supportin...

Ambient intelligence framework for real-time speech-to-sign translation.

Assistive technology : the official journal of RESNA
Sign language can be used to facilitate communication with and between deaf or hard of hearing (Deaf/HH). With the advent of video streaming applications in smart TVs and mobile devices, it is now possible to use sign language to communicate over wor...