Motivational State Computing System for Adaptive Behavioral Coaching

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Solution Overview

Problem

Existing mobile and wearable devices primarily focus on tracking user activity and providing status indicators for fitness goals, but they often fail to guide users effectively in achieving these goals, lacking personalized and contextually relevant feedback.

Innovation Solution

A computing system that uses a motivational model to provide personalized and contextually relevant output, adapting to different motivational states of the user by outputting targeted information to induce behavioral changes, such as educational, inspirational, or celebratory messages, based on the user's current context and fitness information.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If the system provides frequent notifications to motivate users, then user engagement increases, but battery power consumption increases and user annoyance increases

Engineering Contradiction:
Improveuser engagementVSAvoidbattery power consumption
Core Design Contradiction:
ProductivityVSUse of energy by moving object

Solution Approach 1:

The system dynamically adjusts notification frequency and content based on user motivational state transitions. Instead of static frequent notifications, the system adapts its behavior based on real-time detection of user state changes, providing targeted interventions only when needed to drive behavioral change.

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The system changes the parameters of notification delivery based on user motivational state. Different motivational states trigger different notification strategies in terms of frequency, timing, and content, optimizing engagement while reducing unnecessary power consumption from overly frequent notifications.

Inventive Principle:
Principle #35Parameter changes

2Productivity

If the system provides frequent notifications to motivate users, then user engagement increases, but user annoyance increases

Engineering Contradiction:
Improveuser engagementVSAvoiduser annoyance
Core Design Contradiction:
ProductivityVSObject-affected harmful factors

Solution Approach 1:

The system continuously monitors user motivational state and uses this feedback to adjust notification delivery. By detecting when users are in specific motivational states, the system provides targeted feedback that is more likely to be received positively, reducing annoyance while maintaining engagement.

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The notification strategy dynamically adapts based on user state transitions. The system transitions between different notification patterns based on real-time detection of motivational state changes, providing targeted interventions only when needed to drive behavioral change.

Inventive Principle:
Principle #15Dynamics

3Device complexity

If the system provides generic tracking and status indicators, then device complexity is low, but adaptability to user needs is insufficient

Engineering Contradiction:
Improvesystem simplicityVSAvoidpersonalization capability
Core Design Contradiction:
Device complexityVSAdaptability or versatility

Solution Approach 1:

The system performs self-service by automatically detecting user motivational states and generating personalized notifications without requiring manual input or configuration from the user. This maintains relative simplicity while achieving high adaptability through automated state-based personalization.

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The system changes notification parameters dynamically based on detected motivational states. Instead of using fixed generic notifications, the system adapts content, timing, and delivery based on real-time user state detection, achieving personalization without requiring complex user input mechanisms.

Inventive Principle:
Principle #35Parameter changes

Data Source

PatentUS11544591B2Framework for a computing system that alters user behavior
Publication Date: 2023.01.03 GOOGLE LLC
  • US11544591B2 patent drawing
  • US11544591B2 patent drawing
  • US11544591B2 patent drawing

AI summary

An example method includes obtaining user consent to collect and make use of personal information for providing behavioral coaching; obtaining contextual and fitness related information of a user; determining, by inputting the contextual and fitness related information into a model that defines a motivational state, a current motivational state of the user; determining, based at least in part on the current motivational state of the user, a type of information to output as part of the behavioral coaching, wherein the type of information is selected from a group comprising education information, inspirational information, and achievement information; determining, based on the type of information to output, a channel for outputting the type of information as part of the behavioral coaching; and outputting, by the computing device, via the channel, a notification including content of the type of information.