Gait Steadiness Assessment via Polynomial Signal Modeling
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Solution Overview
Problem
Current methods for assessing fall risk in older adults, such as the Timed Up and Go (TUG) test, have limited validity in predicting falls, necessitating a more reliable method for determining gait safety to identify individuals at increased risk early.
Innovation Solution
A method involving a route defined between a starting and reversal point, with movement recorded and analyzed to derive a polynomial function model, allowing for the comparison of the signal course and determination of gait safety, independent of overall speed, using a device with sensors and a processing unit to generate a measure of gait stability, specifically using regression lines or normal distributions for accurate prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the Timed Up and Go (TUG) test is used to assess fall risk, then the test can be administered quickly and is easy to perform, but the predictive value for falls is limited
Solution Approach 1:
The TUG test is divided into multiple segments (rising phase, walking phase, turning phase, sitting phase) with specific focus on the walking phase between starting and turning points. By segmenting the test and analyzing specific phases separately, the system can identify gait stability characteristics that are more predictive of fall risk while maintaining the overall simplicity of the test structure.
Solution Approach 2:
The patent replaces manual observation and timing with automated sensor-based detection. Sensors (optical, acoustic, inertial measurement units) automatically detect and record movement parameters such as position, velocity, acceleration, and trajectory deviations, eliminating the need for manual measurement while providing more precise and reliable data for fall risk prediction.
2Adaptability or versatility
If gait stability is assessed using traditional TUG test, then the test covers basic functional mobility tasks, but it cannot reliably identify increased fall risk early
Solution Approach 1:
The patent introduces multiple dimensions of analysis beyond simple timing. It analyzes spatial trajectory deviations, velocity profiles, acceleration patterns, and positional deviations from ideal paths. By adding these dimensional parameters to the traditional TUG test, the system achieves more precise measurement of gait stability while maintaining coverage of functional mobility tasks.
Solution Approach 2:
The patent introduces sensor systems and signal processing algorithms as intermediaries between the physical movement and the assessment results. Sensors capture detailed movement data, and algorithms process this data to derive gait stability metrics, enabling more accurate and reliable assessment while maintaining the versatility of the TUG test protocol.
3Measurement precision
If the path is analyzed in shorter segments, then the measurement becomes more precise for path length determination, but the complexity of data processing increases
Solution Approach 1:
The movement path is segmented into distinct phases (rising, walking, turning, sitting) and further into sub-segments (first section from start to turning point, second section from turning point to endpoint). This segmentation enables precise path length determination in each segment while allowing the processing system to handle complexity through structured analysis of manageable portions of the overall movement.
Data Source
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AI summary
The invention relates to a method for determining a person's gait steadiness, in which - a route is defined, said route being defined as extending at least between a starting point and a turn-round point and/or said route being defined as extending at least between the turning point and an end point, - the movement of a person along the route is recorded, a timekeeping system is started when the person starts moving along the route at the starting point or at the turning point, and the timekeeping system is stopped when the person stops moving along the route at the turning point or at the end point, - the position of the person relative to the starting point and/or end point is measured, the measured values determined in this way are supplied to a processing unit, and the processing unit generates a signal from the measured values collected over the time, characterised in that - a polynomial function is derived as model from the curve of the signal over the route, and - the curve of the signal is compared with the model and based on this comparison a score for the gait steadiness is determined.