Infection risk and illness assessment method

Patent metadata

Field	Value
Publication number	US-2022257200-A1
Application number	US-202217730378-A
Country	US
Kind code	A1
Filing date	Apr 27, 2022
Priority date	Oct 10, 2013
Publication date	Aug 18, 2022
Grant date	—

Abstract

A method, system, and/or apparatus for automatically monitoring for possible infection or other physical health concerns, such as from Covid-19. The method or implementing software application uses or relies upon location information available on the mobile device from any source, such as cell phone usage and/or other device applications. The method and system automatically uses and/or learns user location and activity patterns and determines and infection risk or illness-based deviation that can be communicated as a warning to community members.

First claim

What is claimed is:

1 . A method of determining infection risks for individuals during an epidemic or pandemic, the method executed by a computer system and comprising:
automatically determining and monitoring positional destinations of a first user using a first mobile electronic device of the user; automatically determining context information about each of the positional destinations without input by the first user; automatically deducing as user information a location type and/or user activity of each of the positional destinations from the context information; automatically learning activity patterns for the user from the user information; assigning a user risk assessment to the first user according to locations and/or activities of the user during a predetermined timeframe; providing the user risk assessment to a community member via a community member electronic device; automatically determining a decrease deviation in the learned activity patterns during or after the predetermined timeframe from further monitoring of further user locations or further user activities; automatically analyzing the decrease deviation to identify a significance of the deviation, wherein analyzing the decrease deviation comprises: correlating the deviation to a current location of the first user to identify a temporary decrease in the learned activity patterns as a function of the current location not allowing for the learned activity patterns, and identifying words and/or ideas from sent or received messages via the first mobile electronic device to identify an explanation for the deviation; automatically correlating the significance of the decrease deviation to a possible infection condition; and automatically alerting the first user via the first mobile electronic device or a second user via a second electronic device of the possible infection condition.

2 . The method of claim 1 , further comprising providing the user risk assessment to a community member before an in-person meeting with the first user.

3 . The method of claim 2 , wherein the user risk assessment is automatically displayed to the community member upon an electronic meeting request and/or the meeting being entered into an electronic calendar.

4 . The method of claim 1 , wherein the predetermined timeframe is at least a predetermined incubation or latency period of a contagion or pathogen.

5 . The method of claim 4 , wherein the user risk assessment is a compilation of a plurality of risk metrics determined for the locations and/or activities during the predetermined time period.

6 . The method of claim 1 , further comprising:
determining a risk metric for each of the locations and/or activities for the first user, to provide a plurality of risk metrics during the predetermined timeframe; and computing the user risk assessment from the plurality of risk metrics.

7 . The method of claim 6 , wherein the risk metric is determined from a predetermined assessment score for each of the location and any activity performed at the location, as a function of time at the location and/or performing the activity.

8 . The method of claim 6 , further comprising:
determining a corresponding user participation time for the each of the locations and/or activities; and scaling the risk metric for the each of the locations and/or activities according to the corresponding user participation time.

9 . The method of claim 6 , wherein the determining the risk metric for the each of the locations and/or activities comprises comparing a location and/or an activity to a predetermined risk scale.

10 . The method of claim 6 , further comprising increasing a risk metric of the user risk assessment upon an in-person contact at the locations and/or activities with a person having a negative risk assessment.

11 . The method of claim 1 , further comprising:
determining any in-person contact of the user for the each of the locations and/or activities; obtaining a contact person risk assessment for the in-person contact; and adjusting the user risk assessment as a function of the contact person risk assessment.

12 . The method of claim 1 , further comprising:
automatically associating the first user with a second user at the positional destination, wherein a second user location and/or second user activity is determined; automatically inferring the location type and/or user activity from the second user location and/or activity; and adjusting the user risk assessment due to in-person contact with the second user.

13 . The method of claim 1 , further comprising for each of the locations, determining the assessment score by normalizing the number of infected people in an area around the location.

14 . The method of claim 1 , wherein the user risk assessment is a summation of a risk metric for each of a location, an activity, and a duration of the activity and/or at the location.

15 . The method of claim 1 , wherein the computer system comprises the first mobile electronic device in wireless communication with a server computer, and the computer system comprises more than one non-transitory recordable medium collectively including a series of preprogrammed instructions that, when executed by the first mobile electronic device and the server computer, cause the computer system to perform the method.

16 . The method of claim 1 , wherein the analyzing the decrease comprises correlating a geographic or weather condition with the current location, and identifying the temporary change in the learned activity patterns as based upon the geographic condition.

17 . The method of claim 1 , wherein the user risk assessment is a compilation of a plurality of risk metrics determined for the locations and/or activities during the predetermined time period, and each of the risk metrics is determined from a predetermined assessment score for each of the location and any activity performed at the location, as a function of time at the location and/or performing the activity, and further comprising:
determining a risk metric for each of the locations and/or activities for the user, to provide the plurality of risk metrics during the predetermined timeframe, wherein the determining the risk metric for the each of the locations and/or activities comprises comparing a location and/or an activity to a predetermined risk scale; determining a corresponding user participation time for the each of the locations and/or activities; scaling the risk metric for the each of the locations and/or activities according to the corresponding user participation time; increasing any risk metric of the user risk assessment upon an in-person contact at the each of the locations and/or activities with a person having a negative risk assessment; and computing the user risk assessment from the plurality of risk metrics.

18 . A method of determining infection risks for individuals during an epidemic or pandemic, the method executed by a computer system and comprising:
automatically monitoring destinations and user activities performed at the destinations of a first user via a first electronic device of the first user; receiving user information comprising a first user activity performed at each of the destinations upon a user arriving at the each of the destinations; automatically learning activity patterns for the first user activity by automatically associating the user information with the at least one of the destinations, automatically determining a user activity context for the first user activity, and automaticall

Assignees

• Aura Home Inc

Inventors

• Frieder Ophir
• Chowdhury Abdur
• Jensen Eric

Classifications

• H04W4/33

  for indoor environments, e.g. buildings · CPC title

• H04L51/52

  for supporting social networking services · CPC title

• A61B5/7465

  Arrangements for interactive communication between patient and care services, e.g. by using a telephone network (telemetry of measured physiological signal A61B5/0002) · CPC title

• H04W52/0254

  detecting a user operation or a tactile contact or a motion of the device · CPC title

• A61B5/7455

  characterised by tactile indication, e.g. vibration or electrical stimulation · CPC title