Abstract:
Individuals with severe motor disabilities (such as advanced ALS or high-levelspinal injury) often have no limb control and only eye movements remainvoluntary[1]. To restore communication, we propose a novel assistive interfacethat converts intentional eye blinks into text or speech. Our design draws onexisting eye-based methods (for example, Stephen Hawking’s ACAT system[2]and smartphone camera-based tracking apps[3]) but uses only low-cost, readilyavailable hardware. A non-invasive sensor (electrodes or a webcam) captureseyelid closures, which a microcontroller digitizes into input signals. Forexample, one can map blink sequences to Morse-like codes - an approach usedby the Synaspeak EEG project, which achieved full text entry with roughly $100of hardware[4]. In our system, the microcontroller runs a blink-detectionalgorithm: it samples the electrooculography (EOG) waveform and applies athreshold to identify blinks, yielding response times on the order of tens ofmilliseconds[5]. Each detected blink then triggers a software action, such asadvancing the highlighted letter or option on screen. Unlike static scanningkeyboards, our interface presents choices in a simple interactive narrative orgame format to keep users engaged. For instance, the user might navigate abranching story or predictive text grid: each blink selects the highlighted choice,gradually building a sentence. Because we rely on eye-electrode signals ratherthan expensive infrared or camera trackers, the hardware is minimal andaffordable. Prior experiments show that even inexpensive EOG setups can attainblink-detection accuracies around 95%[6]. By combining proven blink-detectionhardware (such as Arduino-based EOG circuits[7]) with a user-friendlyinterface, our system enables motor- impaired users to “speak” via eye blinks.This low-cost, flexible design could empower locked-in patients to communicatetheir thoughts in real time.
Page(s):
116-116
DOI:
DOI not available
Published:
Journal: 4th International Conference of Sciences “Revamped Scientific Outlook of 21st Century, 2025” , November 12,2025, Volume: 1, Issue: 1, Year: 2025
Keywords:
machine learning
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Quality Assurance
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food safety
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Artificial Intelligence
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Image classification
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food authentication
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