Adaptive analytical behavioral and health assistant system and related method of use
Inventors
Assignees
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Publication Number
US-10152675-B2
Publication Date
2018-12-11
Expiration Date
Abstract
This present disclosure relates to systems and methods for providing an Adaptive Analytical Behavioral and Health Assistant. These systems and methods may include collecting one or more of patient behavior information, clinical information, or personal information; learning one or more patterns that cause an event based on the collected information and one or more pattern recognition algorithms; identifying one or more interventions to prevent the event from occurring or to facilitate the event based on the learned patterns; preparing a plan based on the collected information and the identified interventions; and/or presenting the plan to a user or executing the plan.
Core Innovation
The invention is directed to a computer-implemented method for managing health of a user in which the method collects information relating to the user and learns one or more patterns that cause an event based on the collected information and one or more algorithms. Based on the learned patterns, the method identifies one or more actions to prevent the event from occurring or to facilitate the event, and prepares a plan based on the collected information and the identified one or more actions. The plan is presented to the user or executed.
The method electronically requests feedback from the user relating the user's subjective assessment of the plan and electronically receives the feedback in response to the request. The method then automatically revises the plan based on the feedback, and identifies actions based on learned patterns and provides the one or more actions to the user.
The revision further determines that the user's subjective assessment is inaccurate and responds by reducing a weight assigned to the user's subjective assessment and increasing a weight assigned to the learned patterns. The method then identifies one or more actions based on the reduced weight assigned to the user's subjective assessment and the increased weight assigned to the learned patterns to prevent the event from occurring or to facilitate the event, with an Adaptive Pattern Service and a cause-effect modeling service supporting identifying interventions and revising patient plans based on feedback.
The document further describes determining device and network speed to present revised patient care plan content by selecting a type of electronic data based on processor speed and network connection speed, and providing feedback about a manner in which the plan was presented. The feedback includes indicating whether the user prefers text-based information or visual-based information and indicating a preferred frequency for content delivery relating to the plan.
Claims Coverage
The document contains three independent claims. Across these claims, the inventive features center on learning event-causing patterns, identifying preventive or facilitating actions, preparing and presenting or executing a plan, and revising the plan automatically using user feedback with reweighting of subjective assessment versus learned patterns, with additional features for device- and network-speed presentation and feedback about presentation preferences and delivery frequency.
Learning event-causing patterns and identifying preventive or facilitating actions
Collecting information relating to the user; learning one or more patterns that cause an event based on the collected information and one or more algorithms; and identifying, based on the learned patterns, one or more actions to prevent the event from occurring or to facilitate the event.
Preparing a plan and presenting or executing the plan
Preparing a plan based on the collected information and the identified one or more actions; and presenting the plan to the user or executing the plan.
Automatically revising the plan based on feedback with reweighting subjective assessment versus learned patterns
Electronically requesting feedback from the user relating the user's subjective assessment of the plan; electronically receiving the feedback; automatically revising the plan based on the feedback; determining that the user's subjective assessment is inaccurate; reducing a weight assigned to the user's subjective assessment when identifying the one or more actions; increasing a weight assigned to the learned patterns when identifying the one or more actions; and identifying one or more actions based on the reduced weight and the increased weight.
Presenting revised care plan based on device and network speed
Analyzing user specific data relating to a user care plan and learning one or more patterns that cause an event; determining one or more actions based on the learned patterns and the user's subjective assessment; automatically preparing and presenting a revised user care plan based on the user specific data and the identified one or more actions; determining a speed of an electronic device associated with the user; and presenting the revised patient care plan based on the speed of the electronic device by selecting a type of electronic data to present based on processor speed of the electronic device and speed of an electronic network to which the electronic device connects.
Feedback about manner of plan presentation with text or visual preference and content frequency
Electronically requesting feedback from the user relating the user's subjective assessment of a manner in which the plan was presented; electronically receiving the feedback where the user manually enters the feedback into a computing device and the feedback includes indicating whether the user prefers text-based information or visual-based information and indicating a preferred frequency for content delivery relating to the plan; and automatically revising the plan based on the feedback by identifying one or more actions based on the feedback and the learned patterns and repeating the reweighting of subjective assessment versus learned patterns.
Across the independent claims, the method learns patterns that cause an event, identifies actions to prevent or facilitate the event, prepares and presents or executes a plan, and automatically revises the plan based on electronic user feedback. The revisions include determining inaccuracy of subjective assessment and adjusting weights by reducing the subjective-assessment weight and increasing the learned-pattern weight to select revised actions. Additional independent-claim coverage includes presenting revised care plan content based on device and network speed and requesting feedback about presentation preferences and preferred content delivery frequency.
Stated Advantages
Automatically revises the plan based on user feedback.
Improves action selection by reducing reliance on an inaccurate user subjective assessment and increasing reliance on learned patterns.
Adapts presentation of the revised patient care plan based on processor speed and network connection speed.
Allows plan presentation to be tailored based on user preference for text-based or visual-based information and preferred frequency of content delivery.
Documented Applications
Example use case includes managing health related to diabetes and inadequate blood glucose control, where low blood sugar is the event (blood glucose level below a normal range).
Plan and actions can include contacting a doctor, ordering medication, changing diet, changing an exercise routine, and indicating rest.
Use of electronic content delivery for revised user care plans, including feedback influencing whether text-based information or visual-based information is preferred and the preferred frequency for content delivery.
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