Fall Detection Using Acceleration Vector Calibration
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Solution Overview
Problem
Conventional wireless sensor devices struggle to accurately detect falls from activities of daily living without specific attachment orientations and fail to discriminate between falls and other movements.
Innovation Solution
A method and system using a wireless sensor device that determines if acceleration magnitude thresholds are met and compares the acceleration vector to a calibration vector, allowing for fall detection regardless of device orientation, employing a tri-axial accelerometer and processing application to differentiate between falls and daily activities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional threshold-based fall detection is used, then fall detection capability is provided, but the system cannot discriminate between falls and activities of daily living
Solution Approach 1:
The patent changes the parameters used for fall detection from simple acceleration magnitude thresholds to a combination of acceleration magnitude, direction (vector), and duration. By analyzing multiple parameters simultaneously and comparing them against calibrated baseline values, the system can distinguish between falls and daily activities with greater accuracy.
Solution Approach 2:
The system performs preliminary calibration by establishing baseline acceleration vectors and thresholds during normal activities before actual fall detection begins. This preliminary action creates a reference framework that enables subsequent discrimination between falls and daily activities.
2Reliability
If conventional fall detection methods are used, then fall detection is possible, but the wireless sensor device must be attached to the user in specific orientations
Solution Approach 1:
The patent makes the fall detection system universal by designing it to work regardless of sensor orientation. The system achieves this by measuring acceleration vectors in three-dimensional space and comparing directional changes rather than relying on fixed orientation assumptions. This allows the sensor to be attached in any orientation while maintaining fall detection accuracy.
Solution Approach 2:
The system transitions from two-dimensional or one-dimensional acceleration measurement to three-dimensional vector analysis. By incorporating directional information from multiple axes and analyzing the orientation of acceleration vectors in 3D space, the system eliminates the need for specific attachment orientations.
3Device complexity
If simple acceleration threshold comparison is used, then the system is simple and cost-effective, but it fails to discriminate problematic falls from activities of daily living
Solution Approach 1:
The patent enhances the detection algorithm by analyzing multiple parameters (acceleration magnitude, direction, duration) rather than relying on a single threshold. This multi-parameter approach maintains computational efficiency while significantly improving the ability to discriminate between falls and daily activities.
Solution Approach 2:
The system replaces complex mechanical or computational mechanisms with a streamlined algorithm that processes acceleration vector data. By using mathematical comparisons of vector directions and magnitudes against calibrated baselines, the system achieves sophisticated discrimination without requiring complex hardware or computationally intensive processing.
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
Enables accurate and cost-effective fall detection that discriminates between problematic falls and activities of daily living, functioning regardless of sensor device orientation, supporting various types of falls and confirming user position.
Implementation Method 1
measuring acceleration data related to the fall
Data Source
AI summary
A method, system, and computer-readable medium for fall detection of a user are disclosed. In a first aspect, the method comprises determining whether first or second magnitude thresholds are satisfied. If the first or second magnitude thresholds are satisfied, the method includes determining whether an acceleration vector of the user is at a predetermined angle to a calibration vector. In a second aspect, the system comprises a processing system and an application that is executed by the processing system. The application determines whether first or second magnitude thresholds are satisfied. If the first or second magnitude thresholds are satisfied, the application determines whether an acceleration vector of the user is at a predetermined angle to a calibration vector.