Method and system for measuring, predicting, and optimizing human cognitive performance
Inventors
Reifman, Jaques • Liu, Jianbo • Wesensten, Nancy • Balkin, Thomas • Ramakrishnan, Sridhar • Khitrov, Maxim Y.
Assignees
United States Department of the Army
Publication Number
US-11241194-B2
Publication Date
2022-02-08
Expiration Date
2036-06-08
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Abstract
A system, method and apparatus is disclosed, comprising a biomathetical model for optimizing cognitive performance in the face of sleep deprivation that integrates novel and nonobvious biomathematical models for quantifying performance impairment for both chronic sleep restriction and total sleep deprivation; the dose-dependent effects of caffeine on human vigilance; and the pheonotypical response of a particular user to caffeine dosing, chronic sleep restriction and total sleep deprivation in user-friendly software application which itself may be part of a networked system.
Core Innovation
The invention provides a system, method, and apparatus comprising a biomathematical model for optimizing human cognitive performance under conditions of sleep deprivation. This model integrates novel biomathematical quantification of cognitive impairment due to chronic sleep restriction and total sleep deprivation, the dose-dependent effects of caffeine on human vigilance, and the phenotypical response of a particular user to caffeine dosing and sleep loss. The model is implemented in user-friendly software, which can be part of a networked system using portable computing devices such as smartphones, allowing users to measure, predict, and optimize cognitive performance and alertness.
The system enables users to input their prior sleep history and caffeine consumption, either manually or via physiological-monitoring devices, and uses these inputs to make predictions of future cognitive performance. These predictions can represent an average individual's alertness or be customized through an artificial intelligence algorithm that learns the user's unique response to sleep loss and caffeine. The system further allows users to explore future sleep schedules and caffeine dosing to optimize cognitive performance at desired times.
Claims Coverage
The patent includes multiple independent claims covering a system worn by a user for cognitive level monitoring, a networked system involving a server and multiple computing devices, and a method for determining cognitive state.
System for cognitive performance monitoring with integrated sensor and user input
A wearable system with a user interface, an accelerometer to detect movement and convert it into sleep-wake data, memory for storing an alertness model and data, and a processor configured to monitor activity, store sleep and caffeine data, compute cognitive level using the alertness model, display cognitive level, perform regular response time tests to individualize the model parameters based on offsets, and provide actionable feedback to address fatigue.
Networked system with server for aggregation and planning
The system includes the wearable device transmitting individualized alertness model parameters to a server that stores these parameters in a user-associated database, provides a planning interface to forecast future or regress past cognitive levels based on different sleep and caffeine schedules, and supports communication between multiple devices and the server.
Model incorporating homeostatic, circadian, and caffeine components
An alertness model that includes a homeostatic component with varying sleep debt asymptotes reflecting sleep-wake data, a circadian component with adjustable amplitude, and a caffeine component providing a multiplicative effect based on caffeine consumption data with exponential decay, enabling accurate prediction and personalization of cognitive levels.
Method for determining cognitive state using wearable device data and user input
A method involving receiving accelerometer data to determine sleep-wake state, storing caffeine consumption data, determining cognitive level with an alertness model incorporating homeostatic, circadian, and caffeine components, displaying results, performing response time tests every four hours awake for individualization, and enabling user action on displayed cognitive level to mitigate fatigue or impairment.
The claims cover a comprehensive system and method for accurately monitoring, predicting, and optimizing human cognitive performance under sleep deprivation through individualized modeling integrating physiological monitoring, caffeine intake, and user response testing, implemented in wearable devices and supported by a networked server for forecasting and planning.
Stated Advantages
Allows users to determine current and future cognitive performance levels accurately by integrating sleep, caffeine consumption, and individual responses.
Enables customization of predictions by learning the user's unique response to sleep loss and caffeine through response time testing and recursive model individualization.
Facilitates optimization of future cognitive performance by allowing exploration of sleep schedules and caffeine dosing strategies.
Provides a practical, user-friendly software implementation that can operate on portable computing devices and communicate with networked servers for group and individual planning.
Documented Applications
Optimizing human cognitive performance and alertness for individuals in both civilian and military settings, particularly to mitigate risks associated with sleep deprivation.
Fatigue risk management in industries engaged in 24-hour operations requiring shift-work scheduling and performance optimization, such as aviation, mining, and nuclear power plants.
Use in wearable computing devices capable of measuring sleep-wake states and cognitive testing to enable individuals to monitor and adjust their alertness.
Workforce scheduling and planning by aggregating individual cognitive performance models on a server for optimal task assignment and shift planning.
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