AIMC Topic: Communication Devices for People with Disabilities
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IoT-driven smart assistive communication system for the hearing impaired with hybrid deep learning models for sign language recognition.
Scientific reports
Feb 20, 2025
Deaf and hard-of-hearing people utilize sign language recognition (SLR) to interconnect. Sign language (SL) is vital for hard-of-hearing and deaf individuals to communicate. SL uses varied hand gestures to speak words, sentences, or letters. It aids ...
Dialogue agents for artificial intelligence-based conversational systems for cognitively disabled: a systematic review.
Disability and rehabilitation. Assistive technology
Nov 22, 2022
PURPOSE: We present a systematic literature review of dialogue agents for Artificial Intelligence (AI) and agent-based conversational systems dealing with cognitive disability of aged and impaired people including dementia and Parkinson's disease. We...
AI enabled sign language recognition and VR space bidirectional communication using triboelectric smart glove.
Nature communications
Sep 10, 2021
Sign language recognition, especially the sentence recognition, is of great significance for lowering the communication barrier between the hearing/speech impaired and the non-signers. The general glove solutions, which are employed to detect motions...
Speech Technology for Healthcare: Opportunities, Challenges, and State of the Art.
IEEE reviews in biomedical engineering
Jan 22, 2021
Speech technology is not appropriately explored even though modern advances in speech technology-especially those driven by deep learning (DL) technology-offer unprecedented opportunities for transforming the healthcare industry. In this paper, we ha...
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
Feb 11, 2020
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 ...
Electroencephalogram based communication system for locked in state person using mentally spelled tasks with optimized network model.
Artificial intelligence in medicine
Nov 19, 2019
Due to growth in population, Individual persons with disabilities are increasing daily. To overcome the disability especially in Locked in State (LIS) due to Spinal Cord Injury (SCI), we planned to design four states moving robot from four imagery ta...
Brain-Computer Interfaces
Wavelet Analysis
Spinal Cord Injuries
Communication Devices for People with Disabilities
Locked-In Syndrome
Electrodes
Sex Characteristics
Healthy Volunteers
Middle Aged
Electroencephalography
Reproducibility of Results
Aged
Aged, 80 and over
Algorithms
Young Adult
Humans
Computer Simulation
Adult
Neural Networks, Computer
Female
Male
Speech Technology Progress Based on New Machine Learning Paradigm.
Computational intelligence and neuroscience
Jun 25, 2019
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...
Visual P300 Mind-Speller Brain-Computer Interfaces: A Walk Through the Recent Developments With Special Focus on Classification Algorithms.
Clinical EEG and neuroscience
Apr 18, 2019
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...
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
Mar 13, 2019
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 synthesis from ECoG using densely connected 3D convolutional neural networks.
Journal of neural engineering
Mar 4, 2019
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 ...
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