Gait Analysis Device Using Tri-Axial Acceleration for Rapid Fall Risk Estimation
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Solution Overview
Problem
Existing gait analysis devices struggle to accurately estimate walking conditions and fall risk in a short time, particularly since subjects are required to perform balance-related actions, which can be stressful and difficult to assess.
Innovation Solution
A gait analysis device with a measuring unit, determining unit, feature quantity calculator, and estimating unit that uses tri-axial acceleration sensors to detect and analyze motion, determine the walking start point, calculate feature quantities, and estimate walking conditions based on acceleration data, classifying them into 'safe', 'careful', and 'high-risk' categories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If measurement and estimation are performed under the assumption that the subject keeps walking, then the measurement process can be simplified, but it becomes difficult to estimate walking condition and fall risk in a short time
Solution Approach 1:
The system performs preliminary detection of walking start points and calculates feature quantities during the transient phase before steady-state walking is achieved. This allows the system to prepare estimation data in advance, enabling rapid assessment without requiring the subject to walk for an extended period while maintaining measurement accuracy through targeted feature extraction during the critical transition phase.
2Reliability
If the subject is required to do balance-related actions, then fall risk assessment can be performed, but the subject feels pressured and the assessment becomes difficult
Solution Approach 1:
The system utilizes the subject's natural walking motion and inherent balance control mechanisms without requiring specific balance-related tasks. The acceleration sensor detects subtle variations in gait patterns during normal walking that reflect balance ability and fall risk, allowing the assessment to be performed passively while the subject simply walks naturally, thereby maintaining both reliability and ease of operation.
3Loss of time
If feature quantity calculation is performed during the transient phase from walking start, then rapid assessment is enabled, but the motion data is less stabilized
Solution Approach 1:
The system changes the approach from requiring stable motion data to extracting meaningful feature quantities from the dynamic transient phase itself. By identifying walking start points through acceleration patterns and calculating features during this transition period, the system transforms the unstable transient data into reliable assessment parameters, achieving rapid evaluation without compromising on the stability of the measurement approach.
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 rapid estimation of walking conditions and fall risk without requiring complex balance actions, reducing subject stress and improving assessment efficiency.
Implementation Method 1
uses tri-axial acceleration sensors to detect and analyze motion
Data Source
AI summary
According to an embodiment, a gait analysis device includes a measuring unit configured to measure a subject's motion; a determining unit configured to determine a walking start point in time at which the subject starts walking based on the subject's motion; a feature quantity calculator configured to, when the walking start point in time is determined, calculate a feature quantity of the subject's motion measured during a predetermined time period starting from the walking start point in time as a time period in which the subject's motion is not stabilized; and an estimating unit configured to estimate a subject's walking condition based on the feature quantity.