Location and activity tracking for medical monitoring
First Claim
1. A method of determining medical conditions of users participating in a social networking service, the method executed by a computer system and comprising:
- automatically monitoring for a first user destinations and user activities performed at the destinations via a first electronic device of the first user;
automatically placing a location module of the first electronic device into a sleep mode between the destinations;
automatically awakening the location module upon receipt of a location transmission at each of the destinations;
receiving user information comprising a first user activity performed at at least one of the destinations upon a user arriving at the at least one 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 automatically comparing a further context of each of a plurality of further user arrivals to the at least one of the destinations to the user activity context, wherein the activity patterns comprise an eating pattern or an exercise pattern, at a location or with one or more community members;
automatically determining a decrease in occurrences of the first user activity over a predetermined time period;
automatically analyzing the decrease to identify a deviation significance, wherein the decrease or the deviation significance is automatically determined using an inference engine, and analyzing the decrease comprises correlating the decrease to user locations and conditions of the current locations during the predetermined time period;
automatically correlating the deviation significance to a possible medical condition; and
automatically alerting the first user via the first electronic device or a second user via a second electronic device of a possible medical condition correlated to the deviation, wherein the second user is a medical professional, close community member, or community member engaged in a similar user activity.
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Accused Products
Abstract
A method, system, and/or apparatus for automatically monitoring for possible mental or physical health concerns. 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 learns user activity patterns and detects significant deviations therefrom. The deviations are automatically analyzed for known correlations to mental or physical concerns, which can then be automatically communicated to a relevant friend, family member, and/or medical professional.
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Citations
19 Claims
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1. A method of determining medical conditions of users participating in a social networking service, the method executed by a computer system and comprising:
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automatically monitoring for a first user destinations and user activities performed at the destinations via a first electronic device of the first user; automatically placing a location module of the first electronic device into a sleep mode between the destinations; automatically awakening the location module upon receipt of a location transmission at each of the destinations; receiving user information comprising a first user activity performed at at least one of the destinations upon a user arriving at the at least one 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 automatically comparing a further context of each of a plurality of further user arrivals to the at least one of the destinations to the user activity context, wherein the activity patterns comprise an eating pattern or an exercise pattern, at a location or with one or more community members; automatically determining a decrease in occurrences of the first user activity over a predetermined time period; automatically analyzing the decrease to identify a deviation significance, wherein the decrease or the deviation significance is automatically determined using an inference engine, and analyzing the decrease comprises correlating the decrease to user locations and conditions of the current locations during the predetermined time period; automatically correlating the deviation significance to a possible medical condition; and automatically alerting the first user via the first electronic device or a second user via a second electronic device of a possible medical condition correlated to the deviation, wherein the second user is a medical professional, close community member, or community member engaged in a similar user activity. - View Dependent Claims (2, 3, 4, 5)
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6. A method of determining medical conditions of users participating in a social networking service, the method executed by a computer system and comprising:
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automatically monitoring for a first user destinations and user activities performed at the destinations via a first electronic device of the first user; automatically receiving location information through a location module of the first electronic device at each of the destinations as the first electronic device travels to the destinations; automatically placing the location module into a sleep mode between the destinations, wherein the location module goes into the sleep mode;
after automatically determining location information, and during extended travel upon an automatically determined rate of travel exceeding a predetermined threshold;automatically awakening the location module at each of the destinations upon receipt of a corresponding location transmission; automatically determining as user information a location type and user activity at each of the destinations; automatically learning activity patterns from the user information at the destinations for the first user; automatically determining a deviation in the learned activity patterns; automatically analyzing the deviation to identify a significance of the deviation; automatically correlating the significance of the deviation to a possible medical condition; and automatically alerting the first user via the first electronic device or a second user via a second electronic device of the possible medical condition. - View Dependent Claims (7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
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Specification