Mobile Balance Testing With Sensor Fusion and Real-Time Feedback
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Solution Overview
Problem
There is a need for an accessible and engaging platform that can objectively measure and improve user balance, particularly for older adults and athletes, by providing real-time feedback and gamified exercises, as existing methods often only initiate balance training after significant impairment.
Innovation Solution
A mobile or wearable device with built-in sensors uses quaternion-based orientation filtering and Kalman filtering to accurately measure balance, calculates stability scores, and provides real-time feedback through gamified exercises, adjusting for intentional movements and penalizing risky behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional physical therapy and rehabilitation programs are used, then balance improvement is achieved, but they are only initiated after significant impairment has occurred
Solution Approach 1:
The system enables balance training to be initiated before significant impairment occurs by providing accessible balance exercises through mobile devices. The application allows users to perform balance exercises at home before falling events occur, preventing the need for formal physical therapy until severe impairment has already happened.
2Measurement precision
If sensor fusion algorithms with quaternion-based orientation filtering and Kalman filtering are used, then measurement precision of balance is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical balance measurement systems with mobile devices that have integrated sensors. The smartphone or wearable device contains accelerometers, gyroscopes, and other sensors that can measure balance parameters without requiring specialized laboratory equipment or complex mechanical apparatus.
Solution Approach 2:
The mobile device serves multiple functions: it acts as both the balance measurement system and the exercise guidance platform. The same device that measures balance through sensor fusion algorithms also provides visual feedback, exercise instructions, and gamified training content, eliminating the need for separate specialized equipment.
3Ease of operation
If real-time feedback and gamified exercises are provided, then user engagement and accessibility are improved, but measurement precision may be affected by intentional movements
Solution Approach 1:
The system provides real-time visual feedback through the mobile device display, showing users their balance performance as they complete exercises. This feedback mechanism encourages users to maintain proper form and reduces intentional movements that would compromise measurement accuracy, while still maintaining high user engagement through gamified elements.
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
The system effectively measures and improves balance by providing real-time feedback, tracking progress, and recommending safer exercises, thereby reducing the risk of falls and enhancing overall balance and mobility.
Implementation Method 1
The mobile device or wearable device includes an accelerometer, gyroscope, and other sensors
Implementation Method 2
The mobile device or wearable device includes an accelerometer, gyroscope, and other sensors
Implementation Method 3
Recent advances in sensor fusion algorithms, including quaternion-based orientation filtering and Kalman filtering, can be used to generate more robust and drift-resistant estimates of device orientation (pitch and roll) and movement
Implementation Method 4
Recent advances in sensor fusion algorithms, including quaternion-based orientation filtering and Kalman filtering, can be used to generate more robust and drift-resistant estimates of device orientation (pitch and roll) and movement
Data Source
AI summary
A method, system, and/or apparatus for measuring user balance with sensors of a mobile device such as a mobile phone or wearable while showing a video or animation coaching various balance exercises. A filter can be utilized to merge accelerometer and gyroscope data to reduce noise. A quaternion-based orientation pipeline can compute the device's pitch, roll, and overall orientation. The system can calculate stability scores by measuring factors such as variance or root-mean-square of pitch and roll fluctuations, acceleration magnitudes, and/or jerk/fall events. If the user experiences sudden/large movements, the system penalizes the user's score to discourage risky behavior. The user may be asked to stand in a baseline posture to measure typical involuntary arm tremor, truncal instability, or normal minimal device motion, which is used to normalize subsequent balance measurements. The system gamifies the experience by providing real-time feedback and awarding points, achievements, and an overall score.