Impairment detection technology
Impairment detection technology (IDT) refers to tools and systems designed to assess whether an individual is functionally impaired at a given moment, regardless of the cause. Unlike drug and alcohol tests that detect substances or their metabolites in the body, IDTs evaluate real-time cognitive or physical performance to identify active impairment.[1][2] These systems are relevant where safety is critical, such as workplaces and law enforcement.[3][4]
IDTs do not identify the specific cause of impairment, such as drug use, fatigue, or illness, but instead detect behavioral or physiological markers like slowed reaction time, poor coordination, or eye movement abnormalities.[5]
Interest in IDT has increased as workplaces and law enforcement agencies address the limitations of traditional drug testing methods. The legalization of cannabis has underscored challenges associated with metabolite-based tests, which can yield positive results days after use, even when the individual is no longer impaired.[6] Studies indicate that tetrahydrocannabinol (THC) levels in blood or saliva do not reliably correlate with functional impairment, as frequent users may retain high THC concentrations without experiencing intoxication, and metabolites may remain detectable long after psychoactive effects have ended.[6]
Types
[edit]IDTs assess an individual’s functional state in real time by monitoring cognitive performance or physiological responses. These technologies fall into several categories:
Oculomotor
[edit]These systems analyze involuntary eye movements and pupil responses, such as nystagmus or delayed reactions to detect impairment. Devices like Gaize’s VR headset use eye-tracking sensors and machine learning to detect intoxication based on ocular behavior.[7]
Psychomotor
[edit]Digital tests measure reaction time, attention, and coordination to detect cognitive deficits due to fatigue or substances. The Psychomotor Vigilance Test (PVT), widely used in fatigue studies, has been shown to detect alertness lapses in professional drivers.[8]
Physiological
[edit]Wearables and in-vehicle systems detect drowsiness or impairment by monitoring eye blinks, head movement, or steering behavior. Some advanced devices use brain-scanning methods like functional near-infrared spectroscopy (fNIRS) to identify cannabis related changes in brain activity.[6] From 2024, the EU mandates drowsiness detection systems in all new vehicles to enhance road safety.[9]
See also
[edit]References
[edit]- ^ "Impairment Detection - National Safety Council". www.nsc.org. Retrieved 2025-05-13.
- ^ Spindle, Tory R.; Martin, Erin L.; Grabenauer, Megan; Woodward, Thomas; Milburn, Michael A.; Vandrey, Ryan (July 2021). "Assessment of cognitive and psychomotor impairment, subjective effects, and blood THC concentrations following acute administration of oral and vaporized cannabis". Journal of Psychopharmacology. 35 (7): 786–803. doi:10.1177/02698811211021583. ISSN 1461-7285. PMC 9361180. PMID 34049452.
- ^ "Impairment Detection Technology Makes Workplaces Safer - National Safety Council". www.nsc.org. Retrieved 2025-05-13.
- ^ "'Impairment Detection Technology and Workplace Safety': NSC releases report | 2022-08-18 | Safety+Health". www.safetyandhealthmagazine.com. Retrieved 2025-05-13.
- ^ "Artificial Vision Systems for Mobility Impairment Detection: Integrating Synthetic Data, Ethical Considerations, and Real-World Applications". MDPI.
- ^ a b c harvardgazette (2022-01-11). "Harvard-led research identifies potential test for cannabis impairment". Harvard Gazette. Retrieved 2025-05-22.
- ^ "What impairment measurement standards does Gaize use?". Gaize. Retrieved 2025-05-22.
- ^ Zhang, Chunbai; Varvarigou, Vasileia; Parks, Philip D.; Gautam, Shiva; Bueno, Antonio Vela; Malhotra, Atul; Kales, Stefanos N. (March 2012). "Psychomotor vigilance testing of professional drivers in the occupational health clinic: a potential objective screen for daytime sleepiness". Journal of Occupational and Environmental Medicine. 54 (3): 296–302. doi:10.1097/JOM.0b013e318223d3d6. ISSN 1536-5948. PMC 3742032. PMID 21826029.
- ^ "Mandatory drivers assistance systems expected to help save over 25,000 lives by 2038 - European Commission". single-market-economy.ec.europa.eu. Retrieved 2025-05-22.