In-shoe Sensor Arrays for Gait Asymmetry Detection
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Solution Overview
Problem
Current assessment tools for balance and gait disorders are inadequate for quantitative analysis over prolonged periods, particularly during daily activities, failing to effectively identify asymmetries and imbalances that can lead to injuries and chronic musculoskeletal pain.
Innovation Solution
A system utilizing pressure sensors and shear stress sensors in shoes to collect and analyze gait data, categorizing pressure uniformity and generating graphical outputs to evaluate gait phases, allowing for the comparison to baseline conditions and providing insights into pressure distribution and torque values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pressure sensors and shear stress sensors are placed in shoes to collect gait data, then measurement precision and duration of action are improved, but device complexity increases
Solution Approach 1:
The insole is divided into multiple discrete sensor locations arranged in arrays, with each sensor measuring pressure or shear stress at a specific location. This segmentation allows comprehensive gait analysis while keeping individual sensors simple and manageable.
Solution Approach 2:
The patent introduces a computer as an intermediary device that receives data from multiple sensors, processes the information, and generates graphical outputs. This intermediary handles the complexity of data integration and analysis, allowing the sensor system itself to remain relatively simple.
2Duration of action of moving object
If data are collected over prolonged periods during daily activities, then duration of action is improved, but loss of information increases due to data management challenges
Solution Approach 1:
The system provides visual feedback through graphical outputs that display gait phase information, pressure distribution, and shear stress patterns. This feedback mechanism helps verify data quality and completeness during prolonged monitoring, reducing information loss.
Solution Approach 2:
The patent replaces manual data analysis with automated computer processing that parses sensor data, identifies gait phases, and generates graphical representations. This substitution ensures consistent data processing over prolonged periods without manual intervention errors.
3Measurement precision
If pressure sensors are categorized into pressure uniformity categories, then measurement precision is improved, but device complexity and difficulty of detecting and measuring increase
Solution Approach 1:
The system changes the parameter being measured from raw pressure values to pressure uniformity categories. By categorizing sensors based on the uniformity of pressure distribution during different gait phases, the system simplifies the interpretation of complex pressure data while maintaining measurement precision.
Solution Approach 2:
The patent uses computer algorithms to automatically categorize sensors into pressure uniformity categories based on parsed gait data. This automated classification replaces manual analysis and reduces the difficulty of detecting and measuring pressure uniformity patterns.
Data Source
AI summary
Systems and methods for analyzing the gait of an individual are disclosed. The disclosed systems and methods can be configured to acquire data from a first array and a second array of sensors that are configured to be placed in a left and/or right shoe, respectively. The acquired data can be collected or separated into at least two separate gait phases for each array, compared to a baseline condition for each gait phase and categorized into one of at least two uniformity categories for each gait phase. Examples of collected and/or calculated data include pressure values, shear stress values and torque values. The analysis can be focused on both feet of a person, or focused on one foot. A graphical output showing at least one entire gait cycle based on the uniformity categories can then be generated.