ArticleScientific reports2023
Blink-To-Live eye-based communication system for users with speech impairments.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 32 citations in OpenAlex.
- Thrivaad: A Multilingual, Predictive Eye-Sign-Based AAC System Powered by Optimized Deep Learning.Sensors (Basel, Switzerland) · 2026Article
- Neural Vision Restoration in Ophthalmology.Annals of biomedical engineering · 2026Review
- Wearable intelligent throat enables natural speech in stroke patients with dysarthria.Nature communications · 2026Article
- Blink Detection Using 3D Convolutional Neural Architectures and Analysis of Accumulated Frame Predictions.Journal of imaging · 2025Article
- Update on How to Approach a Patient with Locked-In Syndrome and Their Communication Ability.Brain sciences · 2024Review
- Innovations In Physical Medicine and Rehabilitation: Advances in the Diagnosis, Treatment, and Care of Amyotrophic Lateral Sclerosis.Missouri medicineReview
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Eye-based communication languages such as Blink-To-Speak play a key role in expressing the needs and emotions of patients with motor neuron disorders. Most invented eye-based tracking systems are complex and not affordable in low-income countries. Blink-To-Live is an eye-tracking system based on a modified Blink-To-Speak language and computer vision for patients with speech impairments. A mobile phone camera tracks the patient's eyes by sending real-time video frames to computer vision modules for facial landmarks detection, eye identification and tracking. There are four defined key alphabets in the Blink-To-Live eye-based communication language: Left, Right, Up, and Blink. These eye gestures encode more than 60 daily life commands expressed by a sequence of three eye movement states. Once the eye gestures encoded sentences are generated, the translation module will display the phrases in the patient's native speech on the phone screen, and the synthesized voice can be heard. A prototype of the Blink-To-Live system is evaluated using normal cases with different demographic characteristics. Unlike the other sensor-based eye-tracking systems, Blink-To-Live is simple, flexible, and cost-efficient, with no dependency on specific software or hardware requirements. The software and its source are available from the GitHub repository ( https://github.com/ZW01f/Blink-To-Live ).
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.