Force Measurement System with Neural Network Balance Prediction
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Solution Overview
Problem
Conventional balance assessment systems are cumbersome and lack flexibility, using antiquated technology that hinders accurate balance assessment and is not adaptable to different testing schemes, necessitating a force measurement system with virtual reality scenarios for improved balance assessment and feedback.
Innovation Solution
A force measurement system incorporating a force measurement assembly with force transducers and data processing devices using a trained neural network to predict balance parameters, coupled with a motion capture system and immersive visual display, enabling immersive virtual reality scenarios and feedback on balance strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional balance assessment systems are used, then the system structure is simple, but the system is cumbersome and lacks flexibility in adapting to different testing schemes
Solution Approach 1:
The force measurement assembly is designed to perform multiple balance assessment functions through software configuration rather than hardware changes. The system can adapt to different testing schemes (static balance, dynamic balance, sensory organization tests) by loading different assessment protocols, making a single device universally applicable to various balance testing requirements.
Solution Approach 2:
The system incorporates adjustable testing parameters and configurable test protocols that can be dynamically modified based on specific assessment needs. The virtual reality environment and feedback mechanisms can be adjusted in real-time to accommodate different testing conditions and subject requirements, providing flexibility without requiring multiple fixed systems.
2Measurement precision
If antiquated technology is used in balance systems, then the device complexity is reduced, but the ability to accurately assess balance is significantly affected
Solution Approach 1:
The system replaces traditional mechanical balance assessment methods with force transducers that measure ground reaction forces and moments. This substitution of mechanical measurement with sensor-based measurement significantly improves assessment accuracy by providing objective, quantitative data on balance performance, center of pressure, and postural control.
Solution Approach 2:
The force measurement assembly acts as an intermediary between the subject's balance performance and the assessment system. It translates complex balance movements into measurable force and moment data, which is then processed by the control system to provide accurate balance assessment metrics, bridging the gap between physical balance behavior and quantifiable results.
3Loss of information
If conventional force measurement systems are used, then the system is simpler, but real-time feedback on balance strategies is not provided
Solution Approach 1:
The system incorporates real-time feedback mechanisms that provide subjects with information about their balance performance during testing. The control system processes force measurement data and delivers feedback through visual, auditory, or haptic interfaces, enabling subjects to understand and adjust their balance strategies. This feedback loop transforms the system from simple measurement to active balance training and assessment.
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 provides accurate and flexible balance assessment, allowing for real-time feedback on balance parameters and strategies, enhancing the ability to quantify errors and adapt to different testing conditions.
Implementation Method 1
at least one force transducer configured to sense one or more measured quantities and output one or more signals that are representative of forces and/or moments being applied to the top surface of the force measurement assembly by the subject
Data Source
AI summary
A force measurement system is disclosed herein. The force measurement system includes a force measurement assembly configured to receive a subject thereon, and one or more data processing devices operatively coupled to the force measurement assembly. In one or more embodiments, the one or more data processing devices are operatively coupled to the force measurement assembly, the one or more data processing devices configured to receive one or more signals that are representative of forces and/or moments being applied to a top surface of the force measurement assembly by the subject, and to convert the one or more signals into output forces and/or moments, the one or more data processing devices further configured to predict one or more balance parameters of the subject using a trained neural network.