Study on the Preferred Application-Oriented Index for Mental Fatigue Detection.

Area of Science:

• Cognitive Psychology
• Occupational Health
• Neuroscience

Background:

• Current mental fatigue evaluation methods rely on complex, large instruments, hindering widespread, timely application.
• A need exists for sensitive, rapid mental fatigue detection to enable early intervention and prevent adverse effects in workers.
• No prior studies have systematically compared the sensitivity of common objective mental fatigue evaluation indexes.

Purpose of the Study:

• To compare the sensitivity of six common objective mental fatigue evaluation indexes.
• To identify a quick, sensitive, and practical index for detecting mental fatigue in occupational settings.

Main Methods:

• Recruited 56 human subjects for mental fatigue testing.
• Evaluated subjects using the Stanford Sleepiness Scale, digital span, digital decoding, short-term memory, critical flicker fusion frequency (CFF), and speed perception deviation.
• Calculated the relative fatigue index (RFI) to account for individual differences and compared index sensitivity across fatigue levels.

Main Results:

• Digital decoding and digital span demonstrated higher sensitivity in detecting mild to severe mental fatigue compared to short-term memory and CFF.
• The relative fatigue index (RFI) values indicated sequential decreases in sensitivity for digital decoding, digital span, short-term memory, and CFF.
• Speed perception deviation exhibited high variability, rendering it unsuitable as a reliable mental fatigue evaluation index.

Conclusions:

• Digital decoding and digital span tests are effective, sensitive, and practical tools for assessing mental fatigue.
• These cognitive tests offer faster, more convenient, and accurate results compared to traditional methods.
• The findings support the use of digital decoding for timely mental fatigue detection and intervention in occupational health.