Motion Sensor Toy Linking Physical Activity to Game Rewards

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Solution Overview

Problem

Youth obesity is a growing issue due to a lack of exercise among children, who spend excessive time engaging in sedentary activities without adequate incentives for physical activity.

Innovation Solution

A system that includes a motion sensing device and computing platform to monitor and encourage physical activity by integrating it with video games, where game attributes and rewards are modified based on the user's exercise data, using a device such as a plush toy with embedded sensors to track activity and provide virtual avatars that improve with increased exercise.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If video games are used to attract children's interest, then children's engagement is improved, but excessive participation in sedentary behavior leads to reduced physical activity

Engineering Contradiction:
Improvechildren's engagementVSAvoidphysical activity level
Core Design Contradiction:
Ease of operationVSProductivity

Solution Approach 1:

The system dynamically adjusts game attributes and rewards based on real-time activity data from motion sensors. Game characteristics change in response to user physical activity levels, creating a dynamic feedback loop that encourages movement while maintaining engagement.

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The system implements feedback by monitoring physical activity through motion sensors and using this data to modify game rewards and attributes. This feedback mechanism links sedentary entertainment with physical activity encouragement, allowing the system to respond to user behavior and adjust incentives accordingly.

Inventive Principle:
Principle #23Feedback

2Measurement precision

If motion sensors and computing platforms are integrated to monitor activity, then physical activity tracking is improved, but device complexity increases

Engineering Contradiction:
Improveactivity tracking accuracyVSAvoidsystem complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The system uses a computing platform that serves multiple functions: processing motion sensor data, managing game logic, storing activity records, and providing user interface. This multi-functionality reduces the need for separate dedicated components for each function, thereby managing complexity while maintaining measurement precision.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent introduces a computing platform as an intermediary that bridges the motion sensors and the video game system. This intermediary processes and interprets sensor data, transforming raw motion information into meaningful activity metrics that can influence game attributes, thereby simplifying the overall system architecture.

Inventive Principle:
Principle #24Intermediary (Mediator)

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

Encourages children to engage in regular physical activity by linking their exercise to game progress and rewards, motivating them to play video games while promoting healthier habits.

Implementation Method 1

Physical activity of a user is monitored using at least one accelerometer to collect motion data

Methodology Applied
Scientific EffectAccelerometer: Accelerometer

Data Source

PatentUS9901815B2Devices, systems, and methods for monitoring, classifying, and encouraging activity
Publication Date: 2018.02.27 RGT UNIV OF CALIFORNIA
  • US9901815B2 patent drawing
  • US9901815B2 patent drawing
  • US9901815B2 patent drawing

AI summary

Devices, methods, and systems for monitoring, classifying and encouraging activity through the use of an accelerometer or other sensor in a toy or other accessory (such as a backpack or watch) that records activity are disclosed. The activity is classified, using various motion classification algorithms, to determine the specific types and amount of activities performed and the times and duration for which they were performed. The classified data is used in the rest of the system, which allows users to view activity history, recommendations for how to improve health, and play games in which the player's game performance is effected by their activity levels. In games and on the website, feedback is also given to users to encourage and reward exercise, while handicapping users that are not active.