How it works · EEG · Prevention

Fatigue detection: 13 minutes before microsleep

The device measures the driver’s brain activity and recognises the drop in attention before it becomes dangerous. Unlike systems that react to symptoms, Oraigo catches fatigue at the source.

Patented EEG 100,000 minutes validated 800+ potential accidents avoided

Advance warning

On average 13 min* before

The margin to stop safely before microsleep.
*as reported in our white paper

What it measures

Brain signals

Not the symptoms on the face. The cause, in the brain.

Publication

Oraigo white paper

Internal study on microsleep detection.

The three steps

How detection works: continuous and silent

The driver drives and the system works, without requiring any action.

Step 1

Measures the brain

It records the brain’s electrical signals in real time: the most direct indicator of alertness.

Step 2

Recognises the drop

When the signals show that alertness is dropping, the system recognises it. It is not an estimate, it is the driver’s real state.

Step 3

Warns on average 13 min before

It flags the risk in advance: the margin that turns a late alarm into effective prevention.

The problem with traditional systems

Whoever measures symptoms always arrives late

Fatigue begins in the brain before it shows in the body. Measuring it at the source means catching it early.

Cameras react to symptoms

They measure eyelid closure or head position. They only work when drowsiness is already visible, and lose effectiveness at night or against backlight.

Behavioural sensors arrive later

Driving style, heart rate: indirect signals that arrive after fatigue has already begun to affect performance.

EEG vs. other systems

EEG or camera: which detects fatigue first?

EEG detects fatigue sooner. The difference is structural: EEG observes the cause, the camera observes the effect.

ORAIGO · EEG

Brain signal

Measures the cause, not the effect
Works at night and against backlight
On average 13 min of advance warning
No camera on the driver
TELECAMERA

Eyes and face

Detects only visible symptoms
Struggles at night and against backlight
Minimal or no advance warning
Films the face continuously
BEHAVIOURAL

Driving style

Indirect and delayed signal
Confuses fatigue and distraction
No early advance warning
Depends on road conditions
Why choose Oraigo

Distinctive technology, documented results

No laboratory promises, verifiable data and published research.

EEG™

Patented technology developed from research

100K+

Minutes of real driving analysed for validation

800+

Potential accidents avoided in field use

Oraigo White Paper

Internal study on microsleep detection

How to use it

Simple for the driver, powerful for the manager

For the driver it is simple: wear the device and the app warns them when needed. For the manager, the dashboard gathers the data and shows where to act.

AIGO

The EEG device

Wearable and light, it measures attention directly from brain signals, unobtrusively.

GO

The driver app

It receives alerts in real time and tells the driver when it is time to stop safely.

FLEETS

The manager dashboard

It gives the fleet manager a view of risk over time, to organise safer shifts.

No invasive installations on the vehicles: the data comes from what the driver already wears.

Try detection with a free pilot

The best way to understand how it works is to see it on your own fleet. A period agreed together, with no commitment.

Frequently asked questions

How does the device predict microsleep?

It measures the brain’s signals and recognises the drop in alertness before it becomes microsleep, giving on average 13 minutes of advance warning.

Yes. Detection is based on the brain’s signals and does not depend on light or on the position of the face, so it also works at night and against backlight.

No. It is a safety system for preventing microsleep at the wheel: it measures attention, but has no diagnostic or clinical purpose.

Wear the device and keep the app running. The system does the rest, without requiring interaction while driving.