Jean Verhardt

Jean Verhardt founded and leads WOMBATT Fatigue Management, a business with a mission to use the most advanced technology available to entirely eliminate fatigue and sleepiness as a cause of accidents and death in industry and on the roads and transport networks of the world. Jean, a former graduate business school associate professor in strategic management, founded the company while participating in the European Space Agency (ESA) business incubation program in the Netherlands during 2009, and the business found its first customers in the challenging mining industry of the Andes mountains in South America. There, where mining haul truck drivers work around the clock in extreme climatic conditions at altitudes from 12,000 to 16,000 feet and more, driver fatigue is a constant problem and the cause of many accidents. WOMBATTs patented fatigue detection system was tested and improved under these challenging conditions, and a full program of fatigue training, fatigue risk management and change management was developed to support the technology. During this same period ESA began planning a manned mission to Mars, and found that a key risk factor for the voyage was astronaut fatigue. None of the existing technologies were considered to be suitable for a long space voyage, but we all know when someone we are close to is tired or sleepy simply from the sound of their voice. How many times have we said to someone we know well “you sound tired.” Jean’s scientific partners in WOMBATT developed for ESA an artificial intelligence algorithm that could recognize growing fatigue or sleepiness over the next four to five hours from the voice of another person, and tested it with astronauts participating in the Mars 500 program. During these tests the voice algorithm was found to have an accuracy of up to 90% in predicting fatigue. That’s the science. The innovation came with Jean’s insight from his background in detecting fatigue in mining haul truck drivers in the Andes. The voice technology could be made available to the wider world by using the ubiquitous mobile phone, which by 2015 had developed to the point where the microphones and chips in phones, tablets and computers were of a high enough quality to detect the tiny variations in the voice which show growing fatigue due to lack of sleep in the speaker. Tiredness due to lack of sleep is expressed to the outside world via changes in the voice muscles and these changes in the voice are recorded using the mobile device microphone. The artificial intelligence algorithm at the heart of the system learns over a short time how each individual speaker’s voice should sound at any particular time of day and so becomes more and more accurate in predicting the increase in fatigue for that person over the next few hours, enabling early action to be taken to prevent the fatigue from ever actually occurring. Placing the most advanced artificial intelligence fatigue prediction technology into the hands of all drivers and workers via their own personal mobile devices has been described as a game changer in the management of fatigue, and is a huge step on the road to eliminating fatigue entirely as a cause of accidents.