title: 2B-AlertWeb: An Open-Access Tool for Predicting the Effects of Sleep/Wake Schedules and Caffeine Consumption on Neurobehavioral Performance.
abstract: Computational tools that predict the effects of daily sleep/wake amounts on neurobehavioral performance are critical components of fatigue management systems, allowing for the identification of periods during which individuals are at increased risk for performance errors. However, none of the existing computational tools is publicly available, and the commercially available tools do not account for the beneficial effects of caffeine on performance, limiting their practical utility. Here, we introduce2B-AlertWeb, an open-access tool for predicting neurobehavioral performance, which accounts for the effects of sleep/wake schedules, time of day, and caffeine consumption, while incorporating the latest scientific findings in sleep restriction, sleep extension, and recovery sleep.
  
  
  
  We combined our validated Unified Model of Performance and our validated caffeine model to form a single, integrated modeling framework instantiated as a Web-enabled tool.2B-AlertWeb allows users to input daily sleep/wake schedules and caffeine consumption (dosage and time) to obtain group-average predictions of neurobehavioral performance based on psychomotor vigilance tasks.2B-AlertWeb is accessible at: https://2b-alert-web.bhsai.org.
  
  
  
  The2B-AlertWeb tool allows users to obtain predictions for mean response time, mean reciprocal response time, and number of lapses. The graphing tool allows for simultaneous display of up to seven different sleep/wake and caffeine schedules. The schedules and corresponding predicted outputs can be saved as a Microsoft Excel file; the corresponding plots can be saved as an image file. The schedules and predictions are erased when the user logs off, thereby maintaining privacy and confidentiality.
  
  
  
  The publicly accessible2B-AlertWeb tool is available for operators, schedulers, and neurobehavioral scientists as well as the general public to determine the impact of any given sleep/wake schedule, caffeine consumption, and time of day on performance of a group of individuals. This evidence-based tool can be used as a decision aid to design effective work schedules, guide the design of future sleep restriction and caffeine studies, and increase public awareness of the effects of sleep amounts, time of day, and caffeine on alertness.
authors.affiliation: Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, MD.
authors.forename: Jaques
authors.initials: J
authors.lastname: Reifman
authors.affiliation: Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, MD.
authors.forename: Kamal
authors.initials: K
authors.lastname: Kumar
authors.affiliation: Air Traffic Organization, Federal Aviation Administration, Washington, DC.
authors.forename: Nancy J
authors.initials: NJ
authors.lastname: Wesensten
authors.affiliation: Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, MD.
authors.forename: Nikolaos A
authors.initials: NA
authors.lastname: Tountas
authors.affiliation: Behavioral Biology Branch, Walter Reed Army Institute of Research, Silver Spring, MD.
authors.forename: Thomas J
authors.initials: TJ
authors.lastname: Balkin
authors.affiliation: Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, MD.
authors.forename: Sridhar
authors.initials: S
authors.lastname: Ramakrishnan
mesh_terms: D001288:Attention / Q000187:drug effects / Q000502:physiology; D001364:Awareness / Q000187:drug effects / Q000502:physiology; D002110:Caffeine / Q000008:administration & dosage* / Q000494:pharmacology; D005221:Fatigue / Q000503:physiopathology / Q000523:psychology; D006801:Humans; D009483:Neuropsychological Tests; D066230:Patient-Specific Modeling; D011597:Psychomotor Performance / Q000187:drug effects / Q000502:physiology; D011930:Reaction Time / Q000187:drug effects / Q000502:physiology; D012892:Sleep Deprivation / Q000175:diagnosis / Q000503:physiopathology / Q000523:psychology; D020178:Sleep Disorders, Circadian Rhythm / Q000175:diagnosis* / Q000503:physiopathology / Q000523:psychology*; D012984:Software; D014584:User-Computer Interface
chemical_list: D002110:Caffeine
keywords: PVT; biomathematical model; caffeine model; prediction tool; sleep schedule