Scholarlink

<p>For those with disabilities, eye blink detection is a natural besides accessible way to communicate besides control devices. Users restricted motor abilities can engage assistive technology like virtual keyboards, speech synthesisers, or smart home devices by identifying deliberate blinks using schemes on electroencephalogram (EEG) or computer vision. Without the need physical exertion, this system improves autonomy, privacy, and accessibility. In people visual impairments communicate more effectively, this study suggests a new-fangled framework that combines You Only Look Once (YOLOv5) with Transformer-based text production. Problems encountered by physically disabled people who use eye movements means of communication are the intended target of proposed paradigm. After quickly besides accurately detecting eye blinks YOLOv5, the framework extracts feature like blink duration besides intermissions. In generate text responses in real-time, these attributes are subsequently input into Transformer model. Apt for use in real-time scenarios, the representation's architecture guarantees low latency without sacrificing accuracy. The system achieves a 95% accuracy rate in blink detection and delivers meaningful text responses in an average of 0.2&#xa0;s each sentence, according to our experimental data. The system also works in different lighting situations, so it used in a variety of settings. This study represents a major step forward in field of assistive technology since it allows people with physical limitations to communicate in real-time with both visual besides audible output. The technology might improve in the future to recognise more complicated motions, as head movements or eyebrow lifts, in addition to eye blinks, besides to make models more personalised for specific users.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Integrating YOLOv5 for eye blink detection with transformer models for real-time text generation in assistive technologies

  • 期刊论文

  • 发表日期：

    2026年3月18日

查看全文
  • H. C. Nalini,
  • S. V. Shashikala

摘要

For those with disabilities, eye blink detection is a natural besides accessible way to communicate besides control devices. Users restricted motor abilities can engage assistive technology like virtual keyboards, speech synthesisers, or smart home devices by identifying deliberate blinks using schemes on electroencephalogram (EEG) or computer vision. Without the need physical exertion, this system improves autonomy, privacy, and accessibility. In people visual impairments communicate more effectively, this study suggests a new-fangled framework that combines You Only Look Once (YOLOv5) with Transformer-based text production. Problems encountered by physically disabled people who use eye movements means of communication are the intended target of proposed paradigm. After quickly besides accurately detecting eye blinks YOLOv5, the framework extracts feature like blink duration besides intermissions. In generate text responses in real-time, these attributes are subsequently input into Transformer model. Apt for use in real-time scenarios, the representation's architecture guarantees low latency without sacrificing accuracy. The system achieves a 95% accuracy rate in blink detection and delivers meaningful text responses in an average of 0.2 s each sentence, according to our experimental data. The system also works in different lighting situations, so it used in a variety of settings. This study represents a major step forward in field of assistive technology since it allows people with physical limitations to communicate in real-time with both visual besides audible output. The technology might improve in the future to recognise more complicated motions, as head movements or eyebrow lifts, in addition to eye blinks, besides to make models more personalised for specific users.