Fatigue-o-meter helps you decide when people are functioning optimally, and can be trusted with difficult or stressful tasks


The test consists of a randomized series of simple object requiring  spatial judgments, which have to be made by the employee at speed. The test requires the subject to concentrate, decide and record their responses for a period of 2-5 minutes. The sophisticated statistical properties built into the system measures response time, accuracy of judgment and overall variability. 

The performance of the employee is compared to his/her own performance during previous and baseline trials. If the subject's performance is significantly below par, or is more variable than usual, this is identified as cause for concern. You may then decide what to do about this situation (e.g.. you may decide to suspend the person from duties, determine the possible causes for the temporary impairment by an interview and behavioral inspection, breathalyzer, etc.).

It is clear from our research to date, that individual perceptual alertness varies normally across the population, therefore you may at point of selection, decide to select the most alert individual by reviewing their fatigue scores, however thereafter, individual negative variance analysis provides the most meaningful way of monitoring whom to trust with your assets. You will appreciate the value of spotting the individual who is impaired every Monday, after payday, after traumatized incidents, etc.

Psychometric theory indicates that combining judgment and reaction time, provides a valid system for measuring psychomotor efficiency. By adding the measurement of variability, the Fatigue-o-meter assesses the psychomotor performance deterioration which takes place as a result of perceptual fatigue and loss of concentration.

Reliability of the instrument:

The instrument has been validated on 7200 subjects and produces a high reliability at (KR 20) 0.84 (p<0.05).

What to do if you want to use the system:


You will need:

A standard Windows 2000 (or better) computer. If you want to use the "Gate-Pass" feature, you will also need a linked and dedicated printer. If you wish to test more than one person simultaneously, you can connect multiple PC's on a Local Area Network (LAN). The system is supported from a website and is updated daily.

Upon registration:

You need to decide how many employees you wish to test on the system. Based on this figure, your start-up pack will be prepared and installed by our representative. Upon installation, your system will be activated from our web site. The start up pack will provide you with a 1- month testing window period for the identified and registered employees. Our representative will provide support and training to your staff.

Each employee must complete 5 baseline trials on the system, to record their normal reactions and provide a start-up norm base.

Hereafter you may have these employees tested any number of times, before, after or during their working shift.

You may access reports on these employees at any time, but we will generate regular monthly performance reports via our website as well.

What happens after the initial 30 days:

You will be billed monthly in advance for the registered number of employees on your system.

When staff leave your service, you simply remove them from the database.

As new staff join you, you register them on the system.

You will be provided with regular reports to review your staff profiles, comparing your employees with the general population norms, identifying staff who are consistently showing low scores, etc.

You may terminate your contract at any stage, by providing us with 7 days written notice. Your service will then be terminated at the end of the current period of credit.

It will cost you:

Our price depend on number of employees registered as well as number of site registered, please Contact us for formal quotation.

Is this really a problem? Consider the following:

Traffic related and occupational accidents have an enormous impact on a developing country such as the RSA in terms of human loss, lower productivity as well as loss of valuable resources and capital assets. Occupational accidents were calculated in 1996 as having cost the South African economy more than R17b alone. At a 6% annualized wage and medical expense increase, this figure was estimated to be R28b in 2005. The compensation Commissioner, according to Cosatu, pays out more than R993m to accident victims in industry every year (this figure obviously does not include loss of productive capacity or assets).

  According to a study published by the CSIR's Transportek division in 2004, the total cost of road accidents (including the cost of vehicle damage, as well as human casualty), amounted to R42.8b in 1998. Working on a conservative increase of 6% p/a, this figure is estimated to have been R77b in 2005.According to an article published by Drive Alive in 2006, a United Kingdom study indicates that 20% of road accidents in the UK are caused by driver fatigue. It is suggested by the authors that this figure may be considerably higher (as high as 60%) in respect of the South African motorist.

The following graphical analysis shows how perceptual alertness (measured in accuracy and response times) of a sample group of bakery van drivers varied when tested by the Fatigue-o-meter:

Figure 1: Driver perceptual alertness


As can be observed from the above graph, 60% ( )of the vehicle accidents recorded over the previous 6 months in the sample group, occurred with the drivers falling into the high error, slow response time group !!


The following case study illustrates the latest findings ex two current sites, which clearly illustrate the results which may be achieved from a well managed system:

Fatigue monitoring results and accident prevention on two sites


Monthly summary driver vigilance was recorded in respect of two sites in Gauteng . These two sites employ a total of 150 (80 and 70 respectively) drivers and operate bulk carriers making deliveries on a national basis. The objective of the research project was to determine whether:

1.      The operational success in applying and managing the Fatigue-o-meter system differed from site to site, and

2.      Whether a relationship exists between the effective management of the site Fatigue-o-meter system and a direct reduction in site vehicle accident costs.

The following statistics were collected on a monthly basis:

  • Ave Resp is the average response speed for the total group tested in the month.
  • Av Err is the average number of erroneous responses given by each group.
  • Resp Var is the degree of response variability caused by individual drivers being slower that their baseline response patterns.
  • Err Var is the degree of error variance caused by drivers making more errors than their baselines.

These results were graphically presented in order to determine whether consistent management monitoring and cautioning of drivers were having the effect of coaching the drivers to show faster response patterns, less error and less individual variance (erratic-ness) around their baselines.

The hypothesis contained in this analysis suggests that  effective management of drivers vigilance leads to a convergent and steadily improving response pattern and therefore should lead to more attentive drivers on the road and a consequent reduction in accident costs.

The first graph below illustrates the well management site results. As can be seen, the various graphs show a convergent pattern and all graphs indicate a downward movement (in the direction of improved response vigilance and a reduction in cautions):


The second graph below indicates the poorly managed site, where the initial graphical direction was similar as the above site, but in month 3 the management control was lost and instead of converging, the site results show a divergent trend line, with a generally worsening of driver vigilance. The only graph showing an improving line is average response speed (likely caused by the drivers realizing that no action would be taken on errors):




The writer obtained accident statistics from both sites and the well managed site was compared with the poorly managed one. The following table shows the results from each site:

Accident analysis over the last 4 months of monitoring

Well managed site

Poorly managed site

1. Drivers on record 80 70
2. Drivers with accidents 5 21
3. Cost of accidents (R) over the period 70 000 400 000
5. Cost of accidents per driver 14 000 19 000


As can be seen, the site which shows a well managed vigilance profile, achieved an accident improvement ratio as follows:

  • 4 times fewer accidents than the poorly managed site
  • 82.5% less cost of total accidents.
  • A reduction of 26% in average financial impact (seriousness) per accident.