# US 12,002,564 B2 · System and method for predicting individual performance in a sporting activity

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 12,002,564 B2
- Document ID: US12002564B2
- Status: Granted
- Kind: B2
- Application number: 17/808,806
- Filed: 2022-06-24
- Published: 2023-12-28
- Granted: 2024-06-04
- Earliest claimed: 2022-06-24
- Assignees: Rijjin, Inc.
- Applicants: Rijjin, Inc.
- Inventors: Derin Walters
- Web page: https://patentgrep.com/patent/US12002564B2

## CPC

- G16H 20/30: relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
- A61B 5/02438: {with portable devices, e.g. worn by the patient}
- A61B 5/1118: {Determining activity level}
- A61B 5/681: {Wristwatch-type devices}
- A61B 5/7267: {involving training the classification device}
- A61B 5/1112: {Global tracking of patients, e.g. by using GPS}
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)

## Abstract

A computing system receives, from a user device, a request to generate an estimated activity profile for a user of the user device for a workout. The computing system identifies route information for the workout. The computing system generates, via a trained prediction system, an initial estimated heartrate for the user based on a personalized training process for the user. The computing system generates, via the trained prediction system, a duration of a portion of the workout based on the route information and environmental information associated with a time and day of the workout. The computing system generates, via the trained prediction system, a projected heartrate of the user during the workout based on the initial estimated heartrate of the user and the generated duration. The computing system outputs the estimated activity profile corresponding to the workout based on the projected heartrate of the user.

## Claims

### Claim 1

A method comprising:
receiving, by a computing system from a user device, a request to generate an estimated activity profile for a user of the user device for a workout;
identifying, by the computing system, route information for the workout, wherein the route information comprises at least one data point associated with the route information;
generating, by the computing system via a trained prediction system, an initial estimated heartrate for the user for the at least one data point in the route information based on a personalized training process for the user;
generating, by the computing system via the trained prediction system, a duration of a portion of the workout based on the at least one data point in the route information and environmental information associated with a time and day of the workout;
generating, by the computing system via the trained prediction system, a projected heartrate of the user during the workout based on the initial estimated heartrate of the user and the generated duration; and
outputting, by the computing system, the estimated activity profile corresponding to the workout based on the projected heartrate of the user, wherein the estimated activity profile comprises the projected heartrate of the user.

### Claim 2 (depends on 1)

The method of claim 1, further comprising:
determining, by the computing system, that the request comprises a target heartrate for the workout,
wherein generating the initial estimated heartrate for the user is further based on the target heartrate for the workout.

### Claim 3 (depends on 1)

The method of claim 1, further comprising:
determining, by the computing system, that the request does not comprise a target heartrate for the workout; and
based on the request, generating, by the computing system a typical heartrate, maximum heartrate, and minimum heartrate for the user based on time and/or terrain features associated with the workout.

### Claim 4 (depends on 1)

The method of claim 1, wherein the route information comprises at least a second data point associated with the route information.

### Claim 5 (depends on 4)

The method of claim 4, further comprising:
generating, by the computing system via the trained prediction system, a second duration of a second portion of the workout based on the at least second data point in the route information and second environmental information associated with a second time and the day of the workout; and
generating, by the computing system via the trained prediction system, a second projected heartrate of the user during the workout based on the initial estimated heartrate of the user, the generated duration, and the second generated duration.

### Claim 6 (depends on 5)

The method of claim 5, wherein outputting, by the computing system, the estimated activity profile corresponding to the workout based on the projected heartrate of the user comprises:
generating the estimated activity profile, wherein the estimated activity profile comprises the projected heartrate of the user at the at least one data point and the second projected heartrate of the user at the at least second data point.

### Claim 7 (depends on 1)

The method of claim 1, further comprising:
determining, by the computing system, that the workout is a multi-point workout; and
based on the determining, simplifying and compressing, by the computing system, the route information associated with the workout.

### Claim 8

A non-transitory computer readable medium comprising one or more sequences of instructions, which, when executed by a processor, causes a computing system to perform operations comprising:
receiving, by the computing system from a user device, a request to generate an estimated activity profile for a user of the user device for a workout;
identifying, by the computing system, route information for the workout, wherein the route information comprises at least one data point associated with the route information;
generating, by the computing system via a trained prediction system, an initial estimated heartrate for the user for the at least one data point in the route information based on a personalized training process for the user;
generating, by the computing system via the trained prediction system, a duration of a portion of the workout based on the at least one data point in the route information and environmental information associated with a time and day of the workout;
generating, by the computing system via the trained prediction system, a projected heartrate of the user during the workout based on the initial estimated heartrate of the user and the generated duration; and
outputting, by the computing system, the estimated activity profile corresponding to the workout based on the projected heartrate of the user, wherein the estimated activity profile comprises the projected heartrate of the user.

### Claim 9 (depends on 8)

The non-transitory computer readable medium of claim 8, further comprising:
determining, by the computing system, that the request comprises a target heartrate for the workout,
wherein generating the initial estimated heartrate for the user is further based on the target heartrate for the workout.

### Claim 10 (depends on 8)

The non-transitory computer readable medium of claim 8, further comprising:
determining, by the computing system, that the request does not comprise a target heartrate for the workout; and
based on the request, generating, by the computing system a typical heartrate, maximum heartrate, and minimum heartrate for the user based on time and/or environmental features associated with the workout.

### Claim 11 (depends on 8)

The non-transitory computer readable medium of claim 8, wherein the route information comprises at least a second data point associated with the route information.

### Claim 12 (depends on 11)

The non-transitory computer readable medium of claim 11, further comprising:
generating, by the computing system via the trained prediction system, a second duration of a second portion of the workout based on the at least second data point in the route information and second environmental information associated with a second time and the day of the workout; and
generating, by the computing system via the trained prediction system, a second projected heartrate of the user during the workout based on the initial estimated heartrate of the user, the generated duration, and the second generated duration.

### Claim 13 (depends on 12)

The non-transitory computer readable medium of claim 12, wherein outputting, by the computing system, the estimated activity profile corresponding to the workout based on the projected heartrate of the user comprises:
generating the estimated activity profile, wherein the estimated activity profile comprises the projected heartrate of the user at the at least one data point and the second projected heartrate of the user at the at least second data point.

### Claim 14 (depends on 8)

The non-transitory computer readable medium of claim 8, further comprising:
determining, by the computing system, that the workout is a multi-point workout; and
based on the determining, simplifying and compressing, by the computing system, the route information associated with the workout.

### Claim 15

A system comprising:
a processor; and
a memory having programming instructions stored thereon, which, when executed by the processor, causes the system to perform operations comprising:
receiving, from a user device, a request to generate an estimated activity profile for a user of the user device for a workout;
identifying route information for the workout, wherein the route information comprises at least one data point associated with the route information;
generating, via a trained prediction system, an initial estimated heartrate for the user for the at least one data point in the route information based on a personalized training process for the user;
generating, via the trained prediction system, a duration of a portion of the workout based on the at least one data point in the route information and environmental information associated with a time and day of the workout;
generating, via the trained prediction system, a projected heartrate of the user during the workout based on the initial estimated heartrate of the user and the generated duration; and
outputting the estimated activity profile corresponding to the workout based on the projected heartrate of the user, wherein the estimated activity profile comprises the projected heartrate of the user.

### Claim 16 (depends on 15)

The system of claim 15, wherein the operations further comprise:
determining that the request comprises a target heartrate for the workout,
wherein generating the initial estimated heartrate for the user is further based on the target heartrate for the workout.

### Claim 17 (depends on 15)

The system of claim 15, wherein the operations further comprise:
determining that the request does not comprise a target heartrate for the workout; and
based on the request, generating a typical heartrate, maximum heartrate, and minimum heartrate for the user based on time and/or environmental features associated with the workout.

### Claim 18 (depends on 15)

The system of claim 15, wherein the route information comprises at least a second data point associated with the route information.

### Claim 19 (depends on 18)

The system of claim 18, wherein the operations further comprise:
generating, via the trained prediction system, a second duration of a second portion of the workout based on the at least second data point in the route information and second environmental information associated with a second time and the day of the workout; and
generating, via the trained prediction system, a second projected heartrate of the user during the workout based on the initial estimated heartrate of the user, the generated duration, and the second generated duration.

### Claim 20 (depends on 19)

The system of claim 19, wherein outputting the estimated activity profile corresponding to the workout based on the projected heartrate of the user comprises:
generating the estimated activity profile, wherein the estimated activity profile comprises the projected heartrate of the user at the at least one data point and the second projected heartrate of the user at the at least second data point.