FAID Quantum Software

FAID Quantum fatigue assessment software is a powerful analytical tool, which can help identify fatigue exposures and support the management of hours of work within an organisation’s fatigue management plan.

FAID Quantum utilises two discrete biomathematical models (BMMs) to provide a richer overall understanding of fatigue exposures.

FAID Quantum provides:

  • Output in two scales – predicted Karolinska Sleepiness Scale (KSS) and FAID Score
  • Highly accurate sleep-wake prediction
  • Peer reviewed, documented scientific models
  • Biomathematical modelling based on real-world data
  • A cost-effective management solution

FAID Quantum offers the following capabilities:

  • Sleep prediction
  • Ability to set fatigue tolerance levels and task risk
  • Optional time zone and circadian disruption calculations
  • Optional crew augmentation (for resting pilots on long flights)
  • Optional input of actual sleep-wake data
  • Optional input and review of external results
  • Easy to use for large data sets

Read more about what FAID Quantum can do for you

InterDynamics’ FAID software and biomathematical model (BMM) has been a global standard for fatigue exposure prediction and fatigue management since its introduction in the late 1990s. In 2016, InterDynamics set a new standard with FAID Quantum, which offers a whole new level of scientifically-verified alertness prediction with the addition of a new BMM.

FAID Quantum is available in versions to suit both businesses and individuals:

FAID Quantum biomathematical models

FAID Quantum continues to provide output in the original FAID Standard biomathematical model developed and validated by Dr Adam Fletcher and Professor Drew Dawson at the Centre for Sleep Research, University of South Australia. The FAID Standard BMM was first released by InterDynamics in 1999 and has been a reliable contributor to assessing and managing fatigue risk since then.

Since 2016, the FAID Quantum biomathematical model, developed by Dr David Darwent in conjunction with Professor Drew Dawson and Dr Greg Roach of the Appleton Institute, has been available as a second output. It uses the best sleep-wake predictor algorithms that have yet been published in international peer-reviewed literature and analyses the work-rest schedules of your personnel to produce a fatigue score in the Karolinska Sleepiness Scale (KSS).

The researchers at the Appleton Institute have used what may be the largest database of quality sleep-wake data in the world, incorporating nearly 15,000 days and nights of data collected from various industries, including long-haul aviation, to underpin predictions. With older biomathematical models of fatigue, predictions were based on average patterns of sleeping and waking but, with FAID Quantum, actual sleep and wake patterns are used to predict future alertness. With this superior real-world data, FAID Quantum can justifiably claim to be the most accurate predictor of alertness available on the market today.