Active Light Blocking Glasses: An optical system for protection against photosensitive seizures

Photosensitive epilepsy affects over 2.5 million people worldwide, causing seizures triggered by flashing lights. Flashing lights are everywhere, on roads, in schools, and in entertainment. Even brief exposure can trigger a seizure. For many people, especially the 15 million living with drug-resistant epilepsy, they live without a solution. The fact that over 80% of people with epilepsy live in low-income regions makes access to effective protection even more limited.

I was diagnosed with photosensitive epilepsy at age 13, and since then it has impacted every aspect of my daily life. This project was inspired by my own experiences and a simple question: Is it possible to make everyday environments more accessible without relying on medication? My goal was to design a low-cost, wearable solution that could detect and dynamically attenuate strobe lights in real-time to protect epileptics from harmful light patterns.

Previous Research: Last year I developed a proof-of-concept algorithm that detects hazardous flashing lights. From data collected through a time-domain analysis, the system differentiates continuous lighting from strobe lighting by measuring timing between peaks from photodiode readings. When a dangerous frequency range (typically 5–30 Hz) is detected, the system can respond by activating a lens to block or reduce the trigger.

This project aims to build upon this research, to make public spaces safer and more accessible for people with epilepsy. By creating an affordable, non-pharmaceutical solution, it has the potential to reduce risk, increase independence, and improve quality of life for millions worldwide.

I used a multi-step process to optimize individual components and to test the effectiveness of the integrated system.

Step 1: Lens evaluation

- Liquid crystal display (LCD) and polymer dispersed liquid crystal (PDLC) selected for evaluation based on cost and availability.

- Measured light attenuation with a lux meter in clear and opaque states

- Visually assessed attenuation and diffusion characteristics

Step 2: Optimize strobe detection performance

- Increase detection range

- Improve accuracy of detections

Step 3: Build a wearable device

- Arduino Nano + soldered breadboard circuit

- Powered by USB battery bank

- Enclosed in plastic case

- Connected to glasses via cable

- Dual LCD lenses and photodiode in glasses

- Foam blinders on glasses for light sealing

Step 4: Test glasses performance

- Generate simulated light readings in the hazardous 5Hz-30Hz range

- Identify and correct algorithm for missed strobe detections

- Physical testing of frequencies outside the hazardous range

- Test under LED, fluorescent, incandescent and natural day and night lighting conditions

- Identify and correct algorithm to prevent false strobe detections

Step 5: Test effectiveness at blocking received seizure causing signals

-  Use EEG to measure steady-state visual evoked potentials (SSVEP) under exposure to 15Hz strobe-light

-  Conduct 3 trials with 40 exposures each to test stimulus

No glasses to confirm presence of neural entrainment

Wearing glasses in On state to confirm blocking of neural entrainment

No glasses to confirm return of neural entrainment

- Evaluate difference in SSVEP response with and without glasses

Step 1: Lens evaluation results

- LCD showed optimal attenuation (> 99%)

- PDLC showed optimal diffusion

- Composite LCD+PDLC combined optimal characteristics of both

- Composite is ideal candidate lens but it requires custom manufacturing

- LCD is best commercially available solution

Step 2: Optimized circuit design

- Photodiode continually monitors light levels

- Integrated photodiode module to boost signal for improved detection distance

- Controllable LCD lenses block light when strobe signal pattern detected by photodiode

- Boost converter used to amplify control signal from 5V to 16V, significantly increasing light attenuation of LCD lenses

Step 3: Wearable device

- Built custom frames using components from 3D glasses and sunglasses

- Glasses weigh 42g

- Adapted ethernet cable to connect glasses to circuit and battery back

- Battery and circuit pack weigh 280g and is small enough to fit in a large pocket

Step 4: Test results

Issue #1: Temporal aliasing

- False positive detections identified near LED and fluorescent lighting

- Identified strobe frequency did not match recorded light readings

- Temporal aliasing caused very high frequency signals to appear as lower frequency signals

- Resolved issue by improving code performance to less than 1ms per sample, thus increasing sampling rate and by implementing a rolling average

- Rolling average causes data smoothing of rapidly repeated signals, removing noise from the signal processing

Issue #2: Low-light environments

- Threshold to trigger a strobe detection could never be met in low light environments

- Lowering the threshold resulted in false positive detections under regular lighting

- Steven’s Power Law states that perceived intensity of stimulus is proportional to its physical intensity raised to a power, meaning that the perceived change in light intensity is greater in low-light environments.

- Resolved this issue by implementing a switchable low-light mode which reduces the threshold from 15 ADC to 2 ADC.

Step 5: SSVEP test results

- Signal analysis using fast-fourier transform to combine EEG signals from test trials

- SSVEP response in participant brain activity showed entrainment with 15Hz strobe and harmonic and sub-harmonic frequencies without glasses as expected

- SSVEP response with glasses in on state showed no entrainment with 15Hz strobe frequency or harmonics or sub-harmonics

- SSVEP response returned to expected entrained state when glasses were removed

This demonstrates an effective block to seizure inducing signals while wearing the glasses.

This project has built upon previous research to produce a wearable device which was then used to conduct testing. Simulated and real-world light signal detection testing allowed for refinement of the detection algorithm to the point where 0 false negatives were present across the hazardous 5-30Hz range, and 0 false positives were present in all identified real-world lighting test scenarios. The less than 30ms response time means that the device can detect and respond to the presence of a strobe light with sufficient speed to block all hazardous frequencies. Finally, SSVEP test results showed changes in brain response, providing evidence that the device is effective at blocking seizure inducing signals from being received by the brain.

This system enables real-time detection and attenuation of hazardous visual stimuli, providing a scalable, non-pharmaceutical solution to a widespread neurological problem. This research and prototype could be used to develop a low-cost wearable solution with minimal maintenance and long lifespan, making everyday life more accessible for a large number of people.

My goal is to continue this research to enable production as a real-world medical device. The following additional research will be required to accomplish this:

Camera Based Light Detection

Experiment with AI camera based light detection

Potential for improved detection under some conditions

Compact Design

Convert circuitry into PCB and integrate battery for a more compact, fully integrated design

SSVEP Testing - Non Epileptics

Conduct additional trails of SSVEP experiment for statistical significance

Experiment across diverse groups (age, gender, ethnicity)

SSVEP Testing - Epileptics

Pursue ethically approved clinical trials with epileptic patients to assess safety and real-world effectiveness

Special thanks to Dr. Randy Newman for her guidance and mentorship during the SSVEP testing process! Learn more about her work with Acadia WISE: https://wise.acadiau.ca/home.html

Special thanks to Acadia University for generously providing access to their facilities for conducting the SSVEP experiment.

Special thanks to the Acadia Research Ethics Board for their support and approval, making this research possible

Special thanks to Epilepsy Canada for their ongoing support and financial assistance! Visit their website to learn more and raise awareness: https://www.epilepsy.ca/

Special thanks to my dad, Chad West, for supervising high-risk activities such as soldering and working with potentially hazardous light frequencies!

Images:

All images taken by Finalist, 2026

Graphs:

All graphs created by Finalist, Excel, 2025-2026

SSVEP analysis graphs created by Dr. Randy Newman, 2026

Schematic:

Schematic drawn by Finalist, Goodnotes, 2026

References:

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