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US 2025/0147584 A1Published application
Methods, systems, and related aspects for determining a cognitive load of a sensorized device user
AssigneeThe Johns Hopkins University
InventorsMathias UNBERATH, Kinjal SHAH, Wenhao GU
Life of this patent
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Abstract
Provided herein are methods of determining a cognitive load of a sensorized device user in certain aspects. Provided herein are also methods of adjusting an interface between a user and a sensorized device in some aspects. Related devices, systems, and computer program products are also provided.
Claims20
A method of determining a cognitive load change of a sensorized device user at least partially using a computer, the method comprising:
- receiving, by the computer, at least a first substantially real-time pupillometric data value from the user from at least a first time point and at least a first substantially real-time unconstrained environmental data value from at least one location proximal to the user from the first time point;
- receiving, by the computer, at least a second substantially real-time pupillometric data value from the user from at least a second time point and at least a second substantially real-time unconstrained environmental data value from at least one location proximal to the user from the second time point, wherein the user is using a sensorized device at least proximal to the first time point and/or the second time point;
- and,
- isolating, by the computer, one or more cognitive load factors from one or more non-cognitive load factors influencing the user at the first and second time points based at least upon the first substantially real-time pupillometric data value, the first substantially real-time unconstrained environmental data value, the second substantially real-time pupillometric data value, and/or the second substantially real-time unconstrained environmental data value to determine the cognitive load change in the user between the first and second time points, wherein determining the cognitive load change in the user between the first and second time points comprises determining an inverse probability of the cognitive load change given the first substantially real-time pupillometric data value, the first substantially real-time unconstrained environmental data value, the second substantially real-time pupillometric data value, and/or the second substantially real-time unconstrained environmental data value, thereby determining the cognitive load change of the sensorized device user.
1 more element
A system, comprising at least one controller that comprises, or is capable of accessing, computer readable media comprising non-transitory computer executable instructions which, when executed by at least one electronic processor, perform at least:
- receiving at least a first substantially real-time pupillometric data value from the user from at least a first time point and at least a first substantially real-time unconstrained environmental data value from at least one location proximal to the user from the first time point;
- receiving at least a second substantially real-time pupillometric data value from the user from at least a second time point and at least a second substantially real-time unconstrained environmental data value from at least one location proximal to the user from the second time point, wherein the user is using a sensorized device at least proximal to the first time point and/or the second time point;
- and,
- isolating one or more cognitive load factors from one or more non-cognitive load factors influencing the user at the first and second time points based at least upon the first substantially real-time pupillometric data value, the first substantially real-time unconstrained environmental data value, the second substantially real-time pupillometric data value, and/or the second substantially real-time unconstrained environmental data value to determine the cognitive load change in the user between the first and second time points, wherein determining the cognitive load change in the user between the first and second time points comprises determining an inverse probability of the cognitive load change given the first substantially real-time pupillometric data value, the first substantially real-time unconstrained environmental data value, the second substantially real-time pupillometric data value, and/or the second substantially real-time unconstrained environmental data value.
1 more element
A computer readable medium comprising non-transitory computer executable instructions which, when executed by at least electronic processor, perform at least:
- receiving at least a first substantially real-time pupillometric data value from the user from at least a first time point and at least a first substantially real-time unconstrained environmental data value from at least one location proximal to the user from the first time point;
- receiving at least a second substantially real-time pupillometric data value from the user from at least a second time point and at least a second substantially real-time unconstrained environmental data value from at least one location proximal to the user from the second time point, wherein the user is using a sensorized device at least proximal to the first time point and/or the second time point;
- and,
- isolating one or more cognitive load factors from one or more non-cognitive load factors influencing the user at the first and second time points based at least upon the first substantially real-time pupillometric data value, the first substantially real-time unconstrained environmental data value, the second substantially real-time pupillometric data value, and/or the second substantially real-time unconstrained environmental data value to determine the cognitive load change in the user between the first and second time points, wherein determining the cognitive load change in the user between the first and second time points comprises determining an inverse probability of the cognitive load change given the first substantially real-time pupillometric data value, the first substantially real-time unconstrained environmental data value, the second substantially real-time pupillometric data value, and/or the second substantially real-time unconstrained environmental data value.
1 more element
Dependencies are inferred from the claim text.