Wellness Coaching Interface with Automatic Sensor-Based Activity Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing techniques for personalizing wellness coaching on electronic devices are cumbersome and inefficient, often requiring complex user interfaces and self-identification of relevant activities, leading to wasted user time and device energy.
Innovation Solution
The method involves displaying a first wellness-related action to a user, detecting if the action is not completed, and replacing it with a new action that meets different action-selection criteria, thereby optimizing user interaction and device efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing techniques are used for personalizing wellness coaching, then users can receive personalized recommendations, but the user interface becomes complex and time-consuming requiring multiple key presses
Solution Approach 1:
The system automatically monitors user activity through sensors and self-identifies relevant activities without requiring users to manually input or select them. The processor analyzes sensor data to determine which activities are personally relevant to each user, eliminating the need for complex user interfaces and manual configuration.
Solution Approach 2:
The patent replaces manual mechanical input (key presses, user selections) with automatic sensor-based detection. Sensors continuously monitor user activities and the processor automatically processes this data to generate personalized wellness recommendations, substituting the mechanical user interface interaction with automated electronic sensing and processing.
2Adaptability or versatility
If users are required to self-identify relevant activities, then personalization can be achieved, but user time and device energy are wasted
Solution Approach 1:
The system performs preliminary action by continuously monitoring and storing user activity data in advance through sensors. This pre-collected data is then automatically processed to identify relevant activities and generate personalized recommendations, eliminating the need for users to spend time manually identifying their activities at the moment of interaction.
Solution Approach 2:
The system performs self-service by automatically monitoring, analyzing, and processing user activity data without requiring user intervention. The processor autonomously identifies relevant activities from sensor data and generates personalized wellness coaching recommendations, saving both user time and device energy.
3Adaptability or versatility
If existing techniques are used for personalizing wellness coaching, then wellness recommendations can be provided, but device energy is consumed reducing battery life
Solution Approach 1:
The system implements self-service by automatically processing sensor data through the processor to identify relevant activities and generate recommendations without requiring repeated user inputs. This automated approach reduces the frequency of processor activation and display updates, thereby conserving device energy and extending battery life while maintaining personalization functionality.
Data Source
AI summary
The present disclosure generally relates to methods and user interfaces for providing personalized wellness coaching.