Motion Sensor Energy Analysis for Complex System Movement
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Solution Overview
Problem
Current methods for analyzing the motion of complex systems, such as the human body or machines, are cumbersome, expensive, and inefficient, as they rely on elaborate optoelectronic setups and offline frame-by-frame analysis, making it difficult to accurately measure and characterize nonlinear movements.
Innovation Solution
A system that uses a motion sensor, including a three-axis accelerometer, gyroscope, and magnetometer, to obtain movement data and compute energy expenditures, identifying energy peaks and their frequency distribution to generate motion-analysis results, allowing for real-time or offline analysis and providing insights into system stability through self-organized criticality behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional optoelectronic setups with multiple LEDs and reflective markers are used to measure movement features, then measurement precision can be improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent extracts only the essential measurement function from the complex optoelectronic system by using a single motion sensor that attaches near the center of gravity. This removes the need for multiple LEDs, reflective markers, and high-speed cameras, dramatically simplifying the device while maintaining the core capability of measuring movement features through energy expenditure analysis
Solution Approach 2:
The patent replaces the mechanical and optical measurement system (physical markers and cameras) with a computational approach using a single accelerometer-based motion sensor. The system substitutes complex physical measurement infrastructure with algorithmic analysis of energy expenditure patterns, achieving measurement precision through software rather than hardware complexity
2Measurement precision
If elaborate optoelectronic setups with high-speed cameras are used for frame-by-frame analysis, then measurement precision is improved, but productivity decreases due to offline processing requirements
Solution Approach 1:
The patent performs preliminary action by continuously collecting and processing motion data in real-time as the subject moves. The system pre-computes energy expenditure metrics and identifies movement features during the actual activity rather than requiring post-processing, enabling immediate analysis and feedback while maintaining measurement accuracy
Solution Approach 2:
The patent ensures continuity of useful action by implementing real-time data processing that continuously analyzes motion patterns as they occur. The system maintains an ongoing computation of energy expenditure and movement features without interruption, eliminating the stop-and-process nature of traditional offline analysis and significantly improving productivity
3Measurement precision
If multiple sensors and complex computational methods are deployed to characterize nonlinear movements, then measurement precision improves, but ease of operation deteriorates
Solution Approach 1:
The patent applies universality by designing a single motion sensor with multi-functionality that can characterize various types of nonlinear movements across different applications. The same accelerometer-based device can analyze human gait, animal locomotion, or mechanical system vibrations, eliminating the need for specialized equipment for each measurement scenario and greatly improving ease of operation
Solution Approach 2:
The patent uses parameter changes by transforming the raw acceleration data into energy expenditure parameters through computational analysis. Instead of directly measuring complex movement features, the system changes the parameter domain from spatial-temporal coordinates to energy metrics, simplifying the characterization of nonlinear movements while maintaining measurement precision
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
This approach enables efficient and accurate characterization of complex system motion, providing stability and health assessments, fitness level evaluation, and disease diagnosis by analyzing energy expenditure patterns, while being more cost-effective and efficient than traditional methods.
Implementation Method 1
The motion sensor can include at least one of: a three-axis accelerometer, a gyroscope, and a magnetometer
Implementation Method 2
The motion sensor can include at least one of: a three-axis accelerometer, a gyroscope, and a magnetometer
Implementation Method 3
The motion sensor can include at least one of: a three-axis accelerometer, a gyroscope, and a magnetometer
Data Source
AI summary
One embodiment provides a system for analyzing a motion of a complex system. During operation, the system obtains movement data associated with the motion over a time interval and computes, over the time interval, a distribution of energy associated with the motion based on the obtained movement data. The system further identifies energy peaks based on the distribution of the energy over the time interval, computes an energy-occurrence-frequency distribution based on the identified energy peaks over a predetermined energy range, and generates a motion-analysis result for the complex system based on the computed energy-occurrence-frequency distribution.