Fall Risk Assessment Using Pressure Sensors and Inertial Data
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Solution Overview
Problem
Current methods for assessing postural stability and fall risk in older adults are costly and require specialized equipment and clinical settings, limiting their accessibility and effectiveness for longitudinal monitoring.
Innovation Solution
A system and method using a portable pressure sensor matrix and inertial sensors to collect data during standing tests, which calculates features to train a classifier model to estimate fall risk, allowing for unsupervised assessments in various environments, including homes, and facilitating timely intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If specialized equipment such as force plates or optical motion capture systems is used to measure postural stability and balance control, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces expensive, complex specialized equipment (force plates, optical motion capture systems) with inexpensive, portable pressure-sensitive mats and inertial sensors that can be easily deployed and removed. These simplified devices provide sufficient measurement capability for clinical and home settings without requiring complex infrastructure.
Solution Approach 2:
The patent substitutes complex mechanical measurement systems with electronic sensing technologies. Pressure-sensitive mats with sensor arrays and inertial measurement units (IMUs) replace mechanical force plates and optical capture systems, enabling digital data collection that is processed through algorithms to derive postural stability metrics.
2Measurement precision
If specialized equipment and clinical visits are required for balance assessment, then measurement precision is improved, but ease of operation and accessibility worsen
Solution Approach 1:
The patent enables patients to perform balance assessments independently at home using portable equipment. The system includes automated data collection and analysis capabilities that do not require trained personnel to operate, allowing patients to conduct their own assessments and facilitating longitudinal monitoring without repeated clinical visits.
Solution Approach 2:
The patent creates a multi-functional assessment system that can be used in multiple settings (clinical and home environments) and for multiple purposes (initial assessment and longitudinal monitoring). The portable equipment and automated algorithms make the system universally applicable across different user groups and settings.
3Measurement precision
If trained personnel and clinical settings are used for fall risk assessment, then measurement precision is improved, but loss of time and productivity worsen
Solution Approach 1:
The patent implements automated data processing algorithms that pre-compute fall risk metrics from sensor data during or immediately after the assessment period. This eliminates the need for time-consuming manual analysis by trained personnel and provides rapid results that can be used for immediate clinical decision-making.
Solution Approach 2:
The patent replaces manual assessment procedures requiring trained personnel with automated electronic sensing and computational analysis. The system automatically collects data from pressure-sensitive mats and inertial sensors, processes the data through algorithms, and generates fall risk assessments without human intervention, significantly reducing assessment time.
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 reduces the cost of fall assessments, enables unsupervised data collection, and provides a timely determination of fall risk, facilitating appropriate interventions to reduce future falls, with demonstrated accuracy in predicting fall risk through classifier models.
Implementation Method 1
a portable pressure sensor matrix that has a plurality of pressure sensors that measure a person's pressure distribution
Implementation Method 2
The inertial sensor data may be collected from an inertial sensor attached to the person
Data Source
AI summary
A system, method, and apparatus is provided for estimating a risk of falls from pressure sensor data and inertial sensor data. A classifier function may be generated to relate the inertial sensor and the pressure sensor data with the falls risk (e.g., falls risk or prospective falls data) of the person who generated the pressure sensor data and inertial sensor data. The classifier function may be used to predict a person's risk of falls based on inputs of pressure sensor data and inertial sensor data. Separate classifier functions may be generated for men and women, or separate classifier functions may be generated for patients who closed their eyes while data was being collected and for patients who opened their eyes while data was being collected.