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US 10,854,104 B2Granted
System for movement skill analysis and skill augmentation and cueing
AssigneeIcuemotion LLC
InventorBerenice Mettler May
Life of this patent
Estimating the term…
Abstract
A cue processor uses one or more sensors to obtain motion data for a user performing a physical task in an environment. A cueing law is based on a model determined from the motion data, for example a movement and skill model where the collected motion data are parsed into one or more movement units used to accomplish a range of outcomes. The cue processor generates a movement phase estimation to predict a movement phase and associated movement feature, and applies the cueing law to generate a cue signal. The cue signal is communicated to the user as a visual, audio or haptic stimulus, selected to target the feature for the user to achieve or improve a desired outcome.
Claims43
A motion analysis and cueing system comprising:
- one or more sensors configured to obtain motion data from a user performing a task in an environment;
- a processor in communication with the one or more sensors, the processor configured to:
- collect the motion data from the one or more sensors;
- parse the collected motion data into one or more movement units and a range of outcomes associated with the one or more movement units;
- delineate the parsed motion data into movement classes;
- model the one or more movement units, wherein a repertoire of prior movement units is formed by aggregating the movement classes;
- analyze one or more of the modeled movement units, wherein a cueing law is synthesized based on the model;
- generate a comparison of the one or more analyzed movement units to the model based on the repertoire of prior movement units used by the user to accomplish the range of outcomes, wherein the model describes reliability and/or efficiency of the one or more movement units in achieving the range of outcomes;
- and
- identify one or more specific aspects of the parsed motion data for change based on the comparison, wherein the processor computes one or more movement features that relate to variations in the range of outcomes and are predictive of a desired outcome in the range;
- and
- a cueing system comprising a cue transducer configured to provide feedback to the user based on the cueing law, the feedback selected from visual, audio or haptic stimuli to target one or more of the movement features identified as predictive for the user to achieve or improve the desired outcome in the range.
9 more elements
A cue processor comprising:
- an input for collecting motion data from one or more sensors, wherein the one or more sensors are configured to obtain the motion data for a user performing a task in an environment;
- and
- a cueing law based on a model of the motion data, wherein the collected motion data are parsed into one or more movement units and a range of outcomes associated with the one or more movement units, and compared to the model based on a repertoire of prior movement units used by the user to accomplish the range of outcomes;
- wherein the cue processor is configured to:
- generate a movement phase estimation which provides a prediction of a movement phase and an associated movement feature that relates to variation in the range of outcomes, extract the associated movement feature based on the model, and apply the cueing law to the associated movement feature, wherein the model identifies the associated movement feature as predictive of a desired outcome in the range;
- and
- generate a cue signal for a cue transducer based on the cueing law, wherein the model describes reliability and/or efficiency of the one or more movement units in achieving the range of outcomes, and wherein the cue transducer is configured to generate cue stimuli for the user in visual, audio or haptic form selected to target the associated movement feature identified as predictive for the user to achieve or improve the desired outcome in the range.
4 more elements
A motion training and cueing program comprising code stored on a non-transitory, computer-readable medium, the code executable on a computer system to perform a method of:
- receiving motion data from one or more sensor inputs configurable to collect the motion data responsive to a user performing a task in an environment;
- and
- executing the motion training and cueing program, wherein the computer system is configured to:
- parse the collected motion data into one or more movement units and a range of outcomes associated with the one or more movement units;
- model the one or more movement units, wherein a cueing law is synthesized based on the model;
- generate a comparison of one or more of the movement units to the model based on a repertoire of prior movement units used by the user to accomplish the range of outcomes, wherein the model describes reliability of the one or more movement units in achieving the range of outcomes;
- identify one or more specific aspects of the parsed motion data for change, based on the comparison, wherein the computer system computes one or more movement features that relate to variations in the range of outcomes and the model identifies which of the movement features are predictive of a desired outcome in the range;
- and
- present at least one of a training assessment and training instruction to the user, responsive to one or more of the repertoire of prior movement units or a movement synergy describing one or more of biomechanical and neuro-muscular relationships between the movement features and muscle activation and body segment motion of the user;
- operating a cueing system configured to provide feedback augmentation to the user in real time or near time based on the cueing law, the feedback augmentation selected from visual, audio or haptic stimuli targeting one or more of the movement features identified as predictive for the user to achieve or improve the desired outcome in the range.
7 more elements
The motion training and cueing program of 31, wherein the training schedule identifies one or more patterns in the repertoire of prior movement units to be practiced by the user.
A method of motion analysis and cueing based training comprising:
- collecting motion data from one or more sensors, the motion data responsive to a user performing a task in an environment;
- parsing the collected motion data into one or more movement units and a range of outcomes associated with the one or more movement units;
- modeling the one or more movement units;
- analyzing the one or more movement units;
- generating a comparison of the one or more analyzed movement units to the modeling based on a repertoire of prior movement units used by the user to accomplish the range of the outcomes, wherein the modeling describes reliability and/or efficiency of the one or more movement units in achieving the range of outcomes;
- identifying one or more specific aspects of the parsed motion data for change, based on the comparison, wherein one or more movement features that relate to variations in the range of outcomes are computed and the modeling identifies which of the one or more movement features are predictive of a desired outcome in the range;
- and
- providing feedback to the user during performance of the task, the feedback selected from visual, audio or haptic stimuli targeting one or more of the movement features identified as predictive for the user to achieve or improve the desired outcome in the range.
5 more elements
Dependencies are inferred from the claim text.