Wearable computing systems installed in helmets have emerged as the new weapon in preventing carbon monoxide poisoning among construction workers, according to new research in the United States.

An award-winning paper written by a research team at Virginia Tech College describes carbon monoxide poisoning as a potentially lethal danger faced by construction workers around the world as exhaust from gasoline-powered hand tools can build up and overcome the tools’ users and co-workers in enclosed spaces.

By integrating a ‘pulse oximetry’ into a typical helmet, however, the researchers were able to determine workers’ gas saturation levels – an ability they claim could be used to alert the worker of potentially impending carbon monoxide poisoning with a probability of greater than 99 per cent.

In order to demonstrate their work without actually subjecting anyone to dangerous conditions, the researchers used a prototype for monitoring blood oxygen saturation – the theory being that if oxygen monitoring proved feasible, so too would carbon monoxide monitoring because the difference in monitoring for oxygen and carbon dioxide differs only in the wavelengths of light employed.

A helmet was chosen as the preferred clothing article because of the need for designs which can be worn all year round – unlike seasonal clothing such as overalls or coats – and strike a balance between considerations relating to comfort, usability, feasibility and social acceptance.

While the latest helmet targets poisoning, the researchers believe wearable computing could help stop other injuries.

“This helmet is only a first step toward our long-term vision of having a network of wearable and environmental sensors and intelligent personal protective gear on construction sites that will improve safety for workers,” the researches say.

“While this helmet targets carbon monoxide poisoning, we believe there are compelling opportunities for wearable computing in reducing injuries due to falls, electrocution and particulate inhalation as well as workers on foot being struck by vehicles.”

The researchers, who include computer engineering PHD student Jason B Forsyth, electrical and computer engineering professor Thomas Martin, civil engineering and environmental engineering assistant professor Deborah Young-Corbett and associate professor of industrial design Ed Dorsa, were presented with the Best Paper Award at the August 17-21 2013 Institute of Electrical and Electronic Engineers (IEEE) Conference on Automation Science and Engineering.