Fall Detection Using Acceleration Vector Angle Calibration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional wireless sensor devices struggle to accurately detect falls from daily activities without specific attachment orientations, leading to limited fall detection capabilities.
Innovation Solution
A method and system that uses a wireless sensor device with a processing system to determine if acceleration magnitude thresholds and angle conditions are met, allowing for fall detection regardless of device orientation, by comparing acceleration vectors to a calibration vector and assessing stooped postures and activity metrics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional approaches measure acceleration data and compare to thresholds, then fall detection can be performed, but the system cannot discriminate between problematic falls and activities of daily living
Solution Approach 1:
The patent transitions from scalar acceleration magnitude comparison to vector-based analysis by introducing angle calculation between acceleration vectors. This dimensional expansion from 1D magnitude to 2D/3D vector space enables discrimination between fall patterns and daily activities through angular relationships, resolving the contradiction between detection reliability and measurement precision
Solution Approach 2:
The system performs preliminary calibration to establish a calibration vector representing the user's normal orientation and activity patterns. This pre-established reference enables subsequent fall detection to compare against personalized baseline data, improving both reliability and precision by accounting for individual variations in movement and posture
2Device complexity
If conventional approaches use acceleration threshold comparison, then fall detection is simple, but the device must be attached to the user in specific orientations
Solution Approach 1:
The patent creates a universal fall detection algorithm that functions correctly regardless of device attachment orientation. By using vector angle calculations relative to a calibration vector rather than fixed threshold comparisons, the system becomes orientation-independent, allowing the device to be attached in any position while maintaining detection accuracy
Solution Approach 2:
The system changes the detection parameter from fixed acceleration magnitude thresholds to dynamic angle measurements relative to a calibration vector. This parameter transformation allows the detection criteria to adapt to any attachment orientation, eliminating the need for specific mounting positions while maintaining algorithmic simplicity
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 accurate and cost-effective fall detection that discriminates between injurious falls and daily activities, improving sensitivity and specificity without requiring specific attachment orientations.
Implementation Method 1
measuring acceleration data related to the fall
Data Source
AI summary
A method and system 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 or whether the user is at a stooped posture. If the acceleration vector of the user is at the predetermined angle to the calibration vector or if the user is at the stooped posture, the method includes determining whether an activity metric is satisfied.