Dynamic Goal Setting for Movement Analytics
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Solution Overview
Problem
Existing movement-based analytics systems lack dynamic and personalized goal setting, failing to effectively integrate external data and user behavior to motivate users in achieving activity and sleep goals.
Innovation Solution
A system that utilizes accelerometers and additional sensors to track movement data, providing a visual timeline display that adjusts user goals based on external factors like weather, health, and past behavior, allowing users to set and adjust activity and sleep goals dynamically, and incorporates social competition features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static step count goals are used, then the system is simple to implement, but it fails to motivate users effectively and does not adapt to individual patterns
Solution Approach 1:
The patent implements dynamic goal setting by automatically adjusting step count goals based on user's historical data, activity patterns, and external factors. The system transitions from static fixed goals to dynamic adaptive goals that evolve with the user's behavior, thereby improving motivation without requiring complex manual configuration from users.
Solution Approach 2:
The system incorporates feedback mechanisms where user performance data is continuously analyzed and used to adjust future goals. The goal curve is revised based on actual step count achievement, creating a closed-loop system that learns from user behavior and automatically optimizes goal setting to improve engagement and motivation.
2Adaptability or versatility
If goals are adjusted based on external data and behavior, then user motivation improves, but data processing complexity increases
Solution Approach 1:
The system performs self-service by automatically collecting, analyzing, and processing user data without requiring manual intervention. The background process autonomously retrieves historical data, analyzes patterns, and adjusts goals based on predefined algorithms, reducing the burden on users while enabling personalized adaptation to individual behavior patterns.
Solution Approach 2:
The system performs preliminary data collection and analysis in the background before goal adjustment is needed. Historical data is pre-processed and stored, allowing the system to quickly generate updated goals without real-time computational overhead, thus reducing perceived processing complexity while maintaining high personalization capability.
3Measurement precision
If the system tracks multiple data types and external factors, then goal accuracy improves, but energy consumption increases
Solution Approach 1:
The system employs periodic data collection and analysis rather than continuous processing. Goal adjustments are performed at scheduled intervals when new historical data becomes available, rather than continuously monitoring and processing all data streams in real-time. This periodic approach maintains measurement precision for accurate goal setting while significantly reducing energy consumption compared to continuous operation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances user motivation by providing a personalized and dynamic goal-setting system that aligns with real-life patterns, improving activity and sleep tracking, and enabling effective competition among users.
Implementation Method 1
As accelerometers become more common, smaller, and low-power consumption, users increasingly have accelerometer-based data available to them.
Data Source
AI summary
A visual display of user data, based on a motion sensor is described. In one embodiment, the visual display comprises a first plurality of time units, indicating an activity level for each time unit during a day portion of a day, and a fitted smooth goal curve, indicating a goal activity level, the goal activity level indicating a goal activity for each of the first time units, the goal activity level based on an overall goal setting and a goal curve defining activity levels throughout the day.