US-20260128142-A1 - SYSTEM AND METHOD FOR ENGAGEMENT OPERATING SYSTEM AND INDEX

US20260128142A1US 20260128142 A1US20260128142 A1US 20260128142A1US-20260128142-A1

Abstract

An engagement operating system includes at least one processing device. The at least one processing device is configured to extract a plurality of data from a plurality of data sources and pre-process the plurality of data. The at least one processing device is also configured to determine an engagement index. The at least one processing device is also configured to identify, using one or more artificial intelligence models, patterns and trends using the engagement index. The at least one processing device is also configured to generate, using the identified patterns and trends, at least one of one or more engagement pathways, or one or more user experience recommendations. The at least one processing device is also configured to continuously monitor the engagement index using a monitoring and updating model to adjust at least one of the one or more engagement pathways or the one or more user experience recommendations.

Inventors

Ravi Seshadri

Assignees

Healthy Engage LLC

Dates

Publication Date: 20260507
Application Date: 20241107

Claims (20)

1 . An engagement operating system comprising: at least one processing device configured to: extract a plurality of data from a plurality of data sources and pre-process the plurality of data via transforming, filtering, modifying, and/or standardizing the plurality of data; determine an engagement index; identify, using one or more artificial intelligence models, patterns and trends using the engagement index; generate, using the identified patterns and trends, at least one of: one or more engagement pathways; or one or more user experience recommendations; and continuously monitor the engagement index using a monitoring and updating model to adjust at least one of the one or more engagement pathways or the one or more user experience recommendations.
2 . The engagement operating system of claim 1 , wherein the at least one processing device is further configured to: generate an N-gram dataset using the pre-processed plurality of data; and store the N-gram dataset in an N-gram repository.
3 . The engagement operating system of claim 2 , wherein, to generate the N-gram dataset, the at least one processing device is further configured to: slide a fixed-size window over the pre-processed plurality of data to capture data combinations within the fixed-size window; and create sequences of features representing a fixed-length combination of consecutive elements in the pre-processed plurality of data.
4 . The engagement operating system of claim 2 , wherein the at least one processing device is further configured to: determine the engagement index using N-grams in the N-gram repository; and identify, using the one or more artificial intelligence models, patterns and trends in the N-gram dataset.
5 . The engagement operating system of claim 4 , wherein the engagement index representing a numerical value reflecting a composite effect of various factors on fitness and engagement related to a user.
6 . The engagement operating system of claim 4 , wherein the at least one processing device is further configured to transmit data on the one or more engagement pathways to an electronic device.
7 . The engagement operating system of claim 2 , wherein the at least one processing device is further configured to store on a blockchain network at least a portion of one or more of: the pre-processed plurality of data; the N-gram dataset; the engagement index; the one or more engagement pathways; or the one or more user experience recommendations.
8 . The engagement operating system of claim 1 , wherein the at least one processing device is further configured to: generate an engagement dataset using the pre-processed plurality of data; and create the engagement index using the engagement dataset.
9 . The engagement operating system of claim 1 , wherein the at least one processing device is further configured to apply the one or more user experience recommendations in one or more contexts of a plurality of contexts.
10 . The engagement operating system of claim 1 , wherein the at least one processing device is further configured to generate, using the identified patterns and trends, both the one or more engagement pathways and the one or more user experience recommendations.
11 . A method of an engagement operating system, the method comprising: extracting a plurality of data from a plurality of data sources and pre-processing the plurality of data via transforming, filtering, modifying, and/or standardizing the plurality of data; determining an engagement index; identifying, using one or more artificial intelligence models, patterns and trends using the engagement index; generating, using the identified patterns and trends, at least one of: one or more engagement pathways; or one or more user experience recommendations; and continuously monitoring the engagement index using a monitoring and updating model to adjust at least one of the one or more engagement pathways or the one or more user experience recommendations.
12 . The method of claim 11 , further comprising: generating an N-gram dataset using the pre-processed plurality of data; and storing the N-gram dataset in an N-gram repository.
13 . The method of claim 12 , wherein generating the N-gram dataset comprises: sliding a fixed-size window over the pre-processed plurality of data to capture data combinations within the fixed-size window; and creating sequences of features representing a fixed-length combination of consecutive elements in the pre-processed plurality of data.
14 . The method of claim 12 , further comprising: determining the engagement index using N-grams in the N-gram repository; and identifying, using the one or more artificial intelligence models, patterns and trends in the N-gram dataset.
15 . The method of claim 14 , wherein the engagement index representing a numerical value reflecting a composite effect of various factors on fitness and engagement related to a user.
16 . The method of claim 14 , further comprising transmitting data on the one or more engagement pathways to an electronic device.
17 . The method of claim 12 , further comprising storing on a blockchain network at least a portion of one or more of: the pre-processed plurality of data; the N-gram dataset; the engagement index; the one or more engagement pathways; or the one or more user experience recommendations.
18 . The method of claim 11 , further comprising: generating an engagement dataset using the pre-processed plurality of data; and creating the engagement index using the engagement dataset.
19 . The method of claim 11 , further comprising applying the one or more user experience recommendations in one or more contexts of a plurality of contexts.
20 . The method of claim 11 , further comprising generating, using the identified patterns and trends, both the one or more engagement pathways and the one or more user experience recommendations.

Description

TECHNICAL FIELD This disclosure relates generally to blockchain and machine learning systems. More specifically, this disclosure relates to a system and method for an engagement operating system and index. BACKGROUND The healthcare industry is rapidly evolving and so are the options available to support it. However, current technological systems for monitoring patients and aspects of their healthcare are antiquated and rely on incomplete data and poor decision-making solutions. SUMMARY This disclosure relates to a system and method for an engagement operating system and index. In one example, an engagement operating system includes at least one processing device. The at least one processing device is configured to extract a plurality of data from a plurality of data sources and pre-process the plurality of data via transforming, filtering, modifying, and/or standardizing the plurality of data. The at least one processing device is also configured to determine an engagement index. The at least one processing device is also configured to identify, using one or more artificial intelligence models, patterns and trends using the engagement index. The at least one processing device is also configured to generate, using the identified patterns and trends, at least one of one or more engagement pathways, or one or more user experience recommendations. The at least one processing device is also configured to continuously monitor the engagement index using a monitoring and updating model to adjust at least one of the one or more engagement pathways or the one or more user experience recommendations. In one or more of the above examples, the at least one processing device is further configured to generate an N-gram dataset using the pre-processed plurality of data and store the N-gram dataset in an N-gram repository. In one or more of the above examples,, to generate the N-gram dataset, the at least one processing device is further configured to slide a fixed-size window over the pre-processed plurality of data to capture data combinations within the fixed-size window and create sequences of features representing a fixed-length combination of consecutive elements in the pre-processed plurality of data. In one or more of the above examples, the at least one processing device is further configured to determine the engagement index using N-grams in the N-gram repository and identify, using the one or more artificial intelligence models, patterns and trends in the N-gram dataset. In one or more of the above examples, the engagement index representing a numerical value reflecting a composite effect of various factors on fitness and engagement related to a user. In one or more of the above examples, the at least one processing device is further configured to transmit data on the one or more engagement pathways to an electronic device. In one or more of the above examples, the at least one processing device is further configured to store on a blockchain network at least a portion of one or more of the pre-processed plurality of data, the N-gram dataset, the engagement index, the one or more engagement pathways, or the one or more user experience recommendations. In one or more of the above examples, the at least one processing device is further configured to generate an engagement dataset using the pre-processed plurality of data and create the engagement index using the engagement dataset. In one or more of the above examples, the at least one processing device is further configured to apply the one or more user experience recommendations in one or more contexts of a plurality of contexts. In one or more of the above examples, the at least one processing device is further configured to generate, using the identified patterns and trends, both the one or more engagement pathways and the one or more user experience recommendations. In another example, a method of an engagement operating system includes extracting a plurality of data from a plurality of data sources and pre-processing the plurality of data via transforming, filtering, modifying, and/or standardizing the plurality of data. The method also includes determining an engagement index. The method also includes identifying, using one or more artificial intelligence models, patterns and trends using the engagement index. The method also includes generating, using the identified patterns and trends, at least one of one or more engagement pathways or one or more user experience recommendations. The method also includes continuously monitoring the engagement index using a monitoring and updating model to adjust at least one of the one or more engagement pathways or the one or more user experience recommendations. In one or more of the above examples, the method further includes generating an N-gram dataset using the pre-processed plurality of data and storing the N-gram dataset in an N-gram repository. In one or more of the above examples, generating the N-gram dataset inc