Employee wellness tracking and recommendations using wearable devices and human resource (HR) data

• US 9,842,313 B2
• Filed: 03/06/2014
• Issued: 12/12/2017
• Est. Priority Date: 02/06/2014
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: B'Far, Reza, Lingg, Elizabeth, Spaulding, Kent, Chakrabarti, Malini, Leone, Christopher
• Primary Examiner(s): Suhol, Dmitry
• Assistant Examiner(s): Larsen, Carl V
• Application Number:
  US14/199,143
• Publication Number:
  US 20150220883A1
• Time in Patent Office: 1,377 Days
• CPC Class Codes: G06Q 10/105 Human resources

Abstract

Embodiments of the invention provide systems and methods for wellness tracking and recommendations. More specifically, embodiments of the present invention provide wellness applications that integrate wearable devices with Human Resource (HR) and other enterprise application data. According to one embodiment, providing integrated wellness information can comprise retrieving enterprise application data from one or more data sources, retrieving data from one or more wearable devices of one or more employees, and applying analytics to the retrieved enterprise application data and the data retrieved from the wearable devices. The integrated wellness information can be generated based on the applied analytics and can be provided to the one or more employees through a user interface.

Claims

1. A method comprising:

retrieving, by a computer system, enterprise application data from one or more data sources of an enterprise, the one or more data sources storing data for a set of employees of the enterprise;

retrieving, by the computer system, data from one or more wearable devices of the set of employees;

applying, by the computer system, analytics to the retrieved enterprise application data and the data retrieved from the one or more wearable devices to generate wellness information, wherein the wellness information includes;

a sedentary metric for a first employee from the set of employees, the sedentary metric indicative of a percentage of time of a period of time that the first employee was determined to be sedentary;

a sedentary score for the first employee for the period of time; and

information identifying a reason associated with the sedentary score and a related recommendation customized for the first employee;

outputting, by the computer system, the wellness information through a user interface;

calculating one or more scores for a sleep quality of the first employee using the data retrieved from the one or more wearable devices; and

analyzing the sedentary score of the first employee and determining a correlation between the one or more sleep quality scores of the first employee and the sedentary score of the first employee.

2. The method of claim 1, wherein the wellness information further includes information comparing activity level information for the first employee with activity level information for other employees in the set of employees.

3. The method of claim 1, wherein the wellness information further includes sleep quality information for the first employee.

4. The method of claim 1, wherein the wellness information further includes information correlating the one or more sleep quality scores for the first employee to one or more factors related to the first employee that impact the sleep quality score.

5. The method of claim 1, wherein the wellness information further includes information correlating a set of sleep scores and a set of performance scores for the first employee.

6. The method of claim 1, wherein the wellness information further includes a set of sleep quality metrics for the set of employees categorized by project types or occupations.

7. The method of claim 1, wherein the wellness information further includes a set of sleep metrics categorized by location for the first employee.

8. The method of claim 1, wherein the wellness information further includes one or more work-life balance and wellness metrics relative to a set of user defined goals for the first employee and one or more recommendations to achieve the user defined goals for the first employee.

9. The method of claim 1, wherein the wellness information further includes one or more wellness metrics for the first employee relative to a set of organization defined wellness goals of a wellness program and one or more recommendations for the first employee to achieve the organization defined wellness goals.

18. The method of claim 1, further comprising:

identifying one or more days in the period of time that the first employee was determined to be sedentary; and

determining, using the identified one or more days, a reason that the first employee was determined to be sedentary, wherein the related recommendation customized for the first employee included in the wellness information is based on the determined reason.

19. The method of claim 1, wherein the retrieved enterprise application data includes, for each employee of the set of employees, at least one of an age, a gender, a geographic location, working hours, a salary range, a job title, an occupation, one or more project types, or an organization.

10. A system comprising:

a processor; and

a memory coupled with and readable by the processor and storing therein a set of instructions which, when executed by the processor, causes the processor to;

retrieve enterprise application data from one or more data sources of an enterprise, the one or more data sources storing data for a set of employees of the enterprise;

retrieve data from one or more wearable devices of the set of employees;

apply analytics to the retrieved enterprise application data and the data retrieved from the one or more wearable devices to generate wellness information, wherein the wellness information includes;

a sedentary metric for a first employee from the set of employees, the sedentary metric indicative of a percentage of time of a period of time that the first employee was determined to be sedentary;

a sedentary score for the first employee for the period of time; and

information identifying a reason associated with the sedentary score and a related recommendation customized for the first employee;

output the wellness information through a user interface;

calculate one or more scores for a sleep quality of the first employee using the data retrieved from the one or more wearable devices; and

analyze the sedentary score of the first employee and determining a correlation between the one or more sleep quality scores of the first employee and the sedentary score of the first employee.

11. The system of claim 10, wherein the wellness information further includes information comparing activity level information for the first employee with activity level information for other employees in the set of employees.

12. The system of claim 10, wherein the wellness information further includes one or more of:

sleep quality information for the first employee;

information correlating the one or more sleep quality scores for the first employee to one or more factors related to the first employee that impact the one or more sleep quality scores;

information correlating a set of sleep scores and a set of performance scores for the first employee;

a set of sleep quality metrics for the set of employees categorized by project types or occupations; and

a set of sleep metrics categorized by location for the first employee.

13. The system of claim 10, wherein wellness information further includes one or more of:

one or more work-life balance and wellness metrics relative to a set of user defined goals for the first employee;

one or more recommendations to achieve the user defined goals for the first employee;

one or more wellness metrics for the first employee relative to a set of organization defined wellness goals of a wellness program; and

one or more recommendations for the first employee to achieve the organization defined wellness goals.

14. A computer-readable memory comprising a set of instructions stored therein which, when executed by a processor, causes the processor to:

retrieve enterprise application data from one or more data sources of an enterprise, the one or more data sources storing data for a set of employees of the enterprise;

retrieve data from one or more wearable devices of the set of employees;

apply analytics to the retrieved enterprise application data and the data retrieved from the one or more wearable devices to generate wellness information, wherein the wellness information includes;

a sedentary metric for a first employee from the set of employees, the sedentary metric indicative of a percentage of time of a period of time that the first employee was determined to be sedentary;

a sedentary score for the first employee for the period of time; and

information identifying a reason associated with the sedentary score and a related recommendation customized for the first employee;

output the wellness information through a user interface;

calculate one or more scores for a sleep quality of the first employee using the data retrieved from the one or more wearable devices; and

analyze the sedentary score of the first employee and determining a correlation between the one or more sleep quality scores of the first employee and the sedentary score of the first employee.

15. The computer-readable memory of claim 14, wherein the wellness information further includes information comparing activity level information for the first employee with activity level information for other employees in the set of employees.

16. The computer-readable memory of claim 14, wherein the wellness information further includes one or more of:

sleep quality information for the first employee;

information correlating the one or more sleep quality scores for the first employee to one or more factors related to the first employee that impact the one or more sleep quality scores;

information correlating a set of sleep scores and a set of performance scores for the first employee; and

a set of sleep quality metrics for the set of employees categorized by project types or occupations; and

a set of sleep metrics categorized by location for the first employee.

17. The computer-readable memory of claim 14, wherein the wellness information further includes one or more of:

one or more work-life balance and wellness metrics for the first employee relative to a set of user defined goals for the first employee;

one or more recommendations for the first employee to achieve the user defined goals for the first employee;

one or more wellness metrics for the first employee relative to a set of organization defined wellness goals of a wellness program; and

one or more recommendations for the first employee to achieve the organization defined wellness goals.