title: Use of EEG workload indices for diagnostic monitoring of vigilance decrement.
abstract: OBJECTIVE
  A study was run to test which of five electroencephalographic (EEG) indices was most diagnostic of loss of vigilance at two levels of workload.
  
  
  BACKGROUND
  EEG indices of alertness include conventional spectral power measures as well as indices combining measures from multiple frequency bands, such as the Task Load Index (TLI) and the Engagement Index (El). However, it is unclear which indices are optimal for early detection of loss of vigilance.
  
  
  METHODS
  Ninety-two participants were assigned to one of two experimental conditions, cued (lower workload) and uncued (higher workload), and then performed a 40-min visual vigilance task. Performance on this task is believed to be limited by attentional resource availability. EEG was recorded continuously. Performance, subjective state, and workload were also assessed.
  
  
  RESULTS
  The task showed a vigilance decrement in performance; cuing improved performance and reduced subjective workload. Lower-frequency alpha (8 to 10.9 Hz) and TLI were most sensitive to the task parameters. The magnitude of temporal change was larger for lower-frequency alpha. Surprisingly, higher TLI was associated with superior performance. Frontal theta and El were influenced by task workload only in the final period of work. Correlational data also suggested that the indices are distinct from one another.
  
  
  CONCLUSIONS
  Lower-frequency alpha appears to be the optimal index for monitoring vigilance on the task used here, but further work is needed to test how diagnosticity of EEG indices varies with task demands.
  
  
  CONCLUSIONS
  Lower-frequency alpha may be used to diagnose loss of operator alertness on tasks requiring vigilance.
authors.forename: Altyngul T
authors.initials: AT
authors.lastname: Kamzanova
authors.forename: Almira M
authors.initials: AM
authors.lastname: Kustubayeva
authors.forename: Gerald
authors.initials: G
authors.lastname: Matthews
mesh_terms: D000293:Adolescent; D000328:Adult; D001288:Attention / Q000502:physiology*; D001359:Aviation; D003198:Computer Simulation; D003463:Cues; D004569:Electroencephalography; D005260:Female; D006801:Humans; D008297:Male; D008606:Mental Processes / Q000502:physiology*; D015203:Reproducibility of Results; D013647:Task Performance and Analysis; D016526:Workload / Q000523:psychology*; D055815:Young Adult