Systems and Methods for Detecting Impairment Based Upon Movement Data
AssigneeBI Incorporated
InventorRic Miller
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Abstract
Various embodiments provide systems and methods for identifying impairment using measurement devices and trained models, and/or for indicating interference with impairment testing. Embodiments discussed herein provide systems, methods, and/or devices that enable remote impairment testing that does not require a human monitor to be present or physically near the individual being monitored. Such an ability is an improvement.
Claims20
A system for detecting impairment based upon movement, the system comprising:
- a movement sensor configured to receive movement information about a user detached monitor device;
- one or more processors;
- a non-transient computer readable medium coupled to the one or more processors, and having stored therein instructions which when executed by the one or more processors, causes the one or more processors to:
- receive the movement information from the movement sensor;
- apply a movement impairment model to the movement information to yield a probability that the individual is impaired;
- indicate a likelihood of impairment based at least in part on a determination that the probability exceeds a first threshold;
- and
- indicate no impairment when the probability is less than a second threshold.
A method for detecting impairment based upon movement information, the method comprising:
- receiving, by a processor, movement information from a movement sensor included in a user detached monitor device;
- applying, by the processor, a movement impairment model to the movement information to yield a probability that the individual is impaired;
- indicating, by the processor, a likelihood of impairment based at least in part on a determination that the probability exceeds a first threshold;
- and
- indicating, by the processor, no impairment when the probability is less than a second threshold.
A non-transient computer readable medium having stored therein instructions, which when executed by a hardware processing system cause the hardware processing system to:
- receive movement information from a movement sensor;
- apply a movement impairment model to the movement information to yield a probability that the individual is impaired, wherein the movement impairment model is a machine learning model trained using at least one hundred instances of movement information data, and wherein the at least one hundred instances of movement information correspond to at least ten different individuals undergoing a movement based impairment test;
- indicate a likelihood of impairment based at least in part on a determination that the probability exceeds a first threshold;
- and
- indicate no impairment when the probability is less than a second threshold.
Dependencies are inferred from the claim text.