UMIP-235 – Breath analysis methodology as a medical diagnostics device

Problem: Operationof vehicles and heavy machinery while sleep-deprived, drowsy, or in otherwiseadverse physiological condition is conventionally understood to lead to greaterrisk of accidents. Approximately 5,000 fatalities and costs upwards of $100billion in damages arise annually from fatigue-related motor vehicle crashes. Increased workplaceerrors and injuries carry an economic burden estimated at $650 billion annuallyfor Canada, Japan, Germany, USA, and UK alone. There arecurrently no regulations to prevent drowsy driving or working, like there are withalcohol intoxication, nor is there any validated alert to the driver/operator ofpotential drowsiness related risks. This is particularly bad for healthcare andtransportation workers who generally have long shifts. Currently, no commercially available device exists that is capableof simple and accurate diagnosis of operator fatigue, drowsiness, and illness ina real-time fashion providing an advanced warning system before potentialaccidents or mistakes may occur. There are technologies that use otherparameters like driver habits, vehicle tracking, driver gestures like headtracking or eye tracking, most of these observances only respond when thedriver is already affected, while physiological cues like those found in breathmay be active even before the physical effects take hold. Further, trackingsystems may be cumbersome and or require a person to be fixed in location tooperate accurately. Therefore, a system targeting breath for drowsinessdetection is a useful diagnostic tool for drowsiness monitoring. Technology: Researchersat the University of Miami have developed a novel, solid-state sensor array as asafety and alert feature for vehicular use, utilizing changes in the subject’sbreath to produce an early warning system. The sensor setup works by identifyingbiomarkers from volatile organic compounds in the operator’s breath specific todrowsiness using a sensor array. Physiological changes caused by the body changethe concentration of various biomarkers in breath. This change in biomarkerstype and or concentration are detected by the solid-state sensor array andidentified as a breath fingerprint for the drowsiness level of a subject. Thetechnology utilizes electronic sensors which allow for seamless integrationinto a vehicle. The vehicle integration has been demonstrated successfully withminimal effort and modifications to existing test vehicle. Modifications to theexisting sensor system will allow connection to the onboard vehicle computer usingstandard communication protocol (Controller Area Network) for easy integration.In addition to connecting to the vehicle directly the system also can use Bluetoothand or Wi-Fi to communicate with other devices or the vehicle if preferred.This allows for access to the internet for real time feedback, monitoring and informationprocessing of the program operator in addition to the subject. Peter Gutenberg pxg372@miami.edu 305-243-4604