Patent ID: 11890508
Assignee: MORPHIX, INC.
Field: Medical technology (Instruments)
Classification: CPC A  G | IPC A  G

Claim 0:
1. A method for determining a user's readiness for an operational task, the method comprising:
at one or more processors of a wearable edge computing device co-located with the user:
during a training phase, for each of a plurality of user training sessions associated with a training task performed by a user, wherein the training task comprises foot travel during the user training session:
receiving location sensor data from a location sensor communicatively coupled to the one or more processors of the wearable edge computing device, wherein the location sensor comprises one or more of an accelerometer or a global positioning system (GPS) sensor;
using the location sensor data to determine distance of travel and a time elapsed for performance of the training task by the user during the user training session;
receiving a terrain type and a weather condition in which the training task is performed during the user training session, the terrain type being selected from a plurality of predefined terrain types;

receiving biometric data for the user from a biometric sensor, the biometric data comprising a biometric parameter, wherein the biometric sensor comprises one or more of a heart rate monitor, a galvanic skin response (GSR) sensor, a pulse oximeter, or a breath gas analyzer;
generating a training data pair for the user training session, the training data pair including,
as input, the distance of travel, the weather condition, the terrain type, and the biometric parameter, and
as ground truth output, the time elapsed determined using the location sensor data;

training an artificial intelligence (AI) performance model that models user performance of the foot travel during the user training session based on the training data pairs for the plurality of the user training sessions; and

during a run-time phase:
receiving operational input data associated with an operational task performed by the user, the operational task comprising foot travel, the operational input data including a target distance of travel, a target weather condition, a target terrain type in which the operational task is performed, and a value for the biometric parameter for the user during the run-time phase;
based on the operational input data, using the AI performance model to infer a predicted time elapsed for performance of the operational task;
outputting the predicted time elapsed for performance of the operational task;
receiving feedback for the predicted time elapsed for performance of the operational task;
pairing the feedback with the operational input data as a feedback training data pair; and
using the feedback training pair to conduct feedback training on the AI performance model.