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Ultradian Rhythms in Prolonged Human Performance
Abstract
The recent wave of interest in rhythms in human behavior is erroneously attributed to the recent developments in the study of biological rhythms. In a recent historical review of the field of behavioral rhythmic research lavie(1980) uncovered several independent roots of research unrelated to questions regarding the nature and functions of biological rhythms. One of those roots was the rather naive ambition of educational psychologists to schedule school hours according with the optimal times for cognitive functioning such as mathematics, reading, etc, on the one hand, and activities requiring psychomotor skills, on the other. This research which attracted quite a number of investigators around the turn of the century, died away around the mid 1920's. Recently it has been revived by the renewed interest in biological rhythms, sleep rhythms, and their interaction with behavior. The notion of an optimal schedule of human behavior is indeed an attractive one. In nature, optimal scheduling and synchronization of different behaviors with the geophysical environment is for many species a crucial survival issue. Displaying courting behavior at the wrong times of the year is dangerously maladaptive, while synchronization of courting and mating behavior with suitable environmental conditions ensures offspring survival.
Human performance modeling (HPM) is a method of quantifying human behavior, cognition, physical performance, and processes used for the development of systems designed for optimal user experience and interaction (Seibok and Wickens, 2013). Human Performance Models (HPMs) are an effective tool for Model Based Systems Engineering (MBSE) (Steinberg et al, 2017), with high economic benefit. Human Engineering practitioners use HPMs to define crew design requirements including the number of operators needed, the benefits of automation, and distribution of member task responsibilities required to operate a system. The application of HPMs throughout the development process helps to influence the system design by integrating with MBSE processes and informing many aspects of system definition and development including performance trades of algorithms, hardware, command and control functions, automation, and the need for situation awareness to monitor the system. In addition to these design benefits, HPMs save development costs and for a described case study reduced costs $4.3M demonstrating the economic benefits for systems engineering. This paper will outline the HPM process for a Command and Control (C2) system.
Human performance modeling (HPM) can be an effective tool to use for determining crew designs. Crew design includes determining the number of operators needed, the role of automation, and member task responsibilities required to operate a system. Without effective measures of performance and thresholds for assessing success, design decisions from HPM will be erroneous. Operator tasks can be assigned and allocated to crew members in a simulation to estimate the workload for each operator during a period of performance. The methods for determining when an operator exceeds workload thresholds create challenges for those using HPM for crew design. Some types of analysis have more clearly defined thresholds. For example, if a military operator has too many tasks to complete to effectively initiate countermeasures between the times they receive a warning until the time the threat arrives, they are overloaded and cannot complete their mission. However, many missions do not have such a severe penalty for not completing the tasks within a given time. For example, pharmacists, satellite managers, traffic managers, food service workers do not have such stringent task timing completion thresholds. For example, the penalty for a food service provider to be overloaded is typically extended wait times rather than risk of a loss of life. For these types of operational situations, determining overload is much more challenging. This paper describes a new workload thresholds for operator workflow models. It incorporates the vigilance effort, the maximum time a crew member will be fully loaded, and determining the maximum time worked without a break.
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