Optalert

A drowsy driver can drift into a microsleep state with no memory of what happened!

It is commonly held that sleep always involves closed eyes. But many microsleeps occur with eyes wide open – a phenomenon known as the “death stare”.

The driver looks fine. Their hands are on the wheel. But their brain has checked out.

This is one of the most dangerous aspects of fatigue: by the time visible warning signs appear, multiple microsleep events may have already occurred.

Our latest article unpacks the science behind microsleeps, why self-assessment is unreliable, and why early, objective detection is the only effective strategy.

Read it here:

Why (and how) drivers have microsleeps - Optalert Microsleeps are invisible, undetectable by the person experiencing them, and often happen with eyes open. Here's what the science and our research says about preventing them.

Many drivers believe they can tell when they are too drowsy to continue.

The evidence suggests otherwise.

Humans are fundamentally poor at assessing their own drowsiness, particularly in safety-critical environments like mining and transport. As drowsiness develops, the very cognitive systems required for self-monitoring begin to degrade.

The result is a dangerous mismatch between perceived state and actual impairment.

This is not simply a behavioural issue. It is a neurological one.
In our latest Insights piece, we unpack:

• Why subjective awareness of drowsiness is unreliable
• How drowsiness affects the brain and impacts one’s ability to self-monitor drowsiness
• The operational factors in the mining and transport industries that make accurate self-assessment even more difficult

Most importantly, it explains why objective drowsiness monitoring is increasingly essential for managing risk and improving safety outcomes.

Read it here -

Why We Can’t Reliably Assess Our Own Drowsiness - Optalert Human perception is a poor indicator of drowsiness. In industries where worker safety is paramount, relying on self-assessment alone can introduce serious operational risks.