Activity Meter Behavior Estimation via Gravity-Axis Coordinate Transformation
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Solution Overview
Problem
Existing activity estimation technologies using activity meters face challenges in accuracy due to variations in physical characteristics among workers and the presence of disturbance noise components in sensor signals, leading to reduced estimation accuracy and increased complexity in signal processing.
Innovation Solution
The solution involves transforming the coordinate system of measured acceleration using an angle between the arm and a dolly, extracted from the resolved gravity acceleration value, to improve behavior estimation accuracy without requiring correct waveform data for each worker, and reducing noise components through low-pass filtering and coordinate transformation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If correct waveform data is prepared for each worker to reduce estimation accuracy variations, then behavior estimation accuracy is improved, but labor and costs increase significantly
Solution Approach 1:
The patent applies universality by creating a single standard waveform data that can be used for all workers regardless of their individual physical characteristics. The coordinate transformation technique allows the same waveform data to accurately represent behaviors of workers with different heights, arm lengths, and other anatomical variations, eliminating the need for individualized waveform preparation while maintaining estimation accuracy.
Solution Approach 2:
The patent transforms the problem by changing the coordinate system parameters rather than changing the waveform data for each worker. By applying coordinate transformation based on gravitational acceleration components, the system adapts a universal waveform to different workers' physical characteristics through mathematical parameter transformation, avoiding the need to collect and store individual waveform data for each worker.
2Measurement precision
If individual optimization of signal detecting method is performed for each detection environment, then detection accuracy is improved, but system complexity increases significantly
Solution Approach 1:
The patent creates a universal signal processing method that works across different detection environments and worker types. The coordinate transformation approach provides a single, unified processing pipeline that handles various detection conditions without requiring environment-specific optimization, thereby maintaining accuracy while reducing complexity.
Solution Approach 2:
The patent extracts the essential behavioral pattern from the acceleration signal by separating it from worker-specific physical characteristics through coordinate transformation. This extraction process isolates the universal behavior signature that can be detected across different environments and individuals, simplifying the detection method while maintaining accuracy.
3Measurement precision
If low-pass filtering is applied to remove disturbance noise components, then signal quality is improved, but slow change detection capability may be compromised
Solution Approach 1:
The patent applies local quality by selectively filtering noise components in specific frequency ranges while preserving the slow-changing behavioral signals. The coordinate transformation method allows targeted noise removal in directions where noise predominates while maintaining signal integrity in directions where slow changes occur, achieving both noise reduction and slow change detection.
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 enhances behavior estimation accuracy by adapting to individual physical characteristics and reducing noise, allowing for reliable signal detection without labor-intensive waveform data preparation for each worker.
Implementation Method 1
extracted from the resolved gravity acceleration value
Data Source
AI summary
According to one embodiment, a behavior estimating method for estimating behavior of a person being measured equipped with an activity meter including an acceleration sensor, includes presetting a first angle between a gravitation direction and a direction of action of a standard person being measured, calculating different acceleration waveforms from the activity meter, extracting a second angle between the gravitation direction and the direction of action of the person from the acceleration waveforms, performing a coordinate transformation process among the acceleration waveforms based upon the present first angle and the extracted second angle, and performing behavior estimation of the person using a result of the coordinate transformation.