Smart Insoles for Objective Gait Evaluation
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Solution Overview
Problem
Current methods for monitoring and evaluating gait in patients with multiple sclerosis (MS) are burdensome, subjective, and lack objective data, particularly in assessing kinematic, kinetic, and spatiotemporal metrics, due to the need for expensive equipment and laboratory settings, which limits accessibility and accuracy in tracking disease progression and fall risk.
Innovation Solution
A computer-implemented method using smart insoles with sensors (accelerometers, gyroscopes, pressure sensors) that segment and process gait data to calculate a composite gait quality score, integrating machine learning algorithms like SVM to classify walking patterns and provide a user-friendly interface for clinicians and patients, enabling remote monitoring and actionable feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion cameras and complex equipment are used in laboratory settings, then measurement precision of gait metrics is improved, but device complexity and accessibility worsen
Solution Approach 1:
The patent replaces complex mechanical motion capture systems with inertial measurement units (IMUs) containing accelerometers, gyroscopes, and magnetometers. These electronic sensors capture gait data through motion-induced electrical signals, eliminating the need for complex optical cameras and mechanical equipment while maintaining measurement precision for spatiotemporal gait parameters.
Solution Approach 2:
The patent uses wearable sensor copies that replicate the functionality of laboratory-grade motion capture equipment. The IMUs embedded in shoes or worn on the body create portable copies of complex lab systems, enabling gait analysis outside traditional laboratory settings while preserving the ability to measure key gait metrics.
2Measurement precision
If clinical walking tests are conducted in-person at clinician offices, then measurement precision of ambulation parameters is improved, but ease of operation and patient burden worsen
Solution Approach 1:
The patent enables patients to conduct their own gait assessments by wearing the sensor-equipped shoes or devices during daily activities. The system automatically captures and processes gait data without requiring clinician presence or supervision, allowing patients to perform assessments at home and reducing travel burden while maintaining measurement quality through automated algorithms.
3Measurement precision
If comprehensive gait analysis equipment is made accessible, then measurement precision of kinematic and kinetic metrics is improved, but device complexity and cost worsen
Solution Approach 1:
The patent divides the gait analysis system into modular segments: wearable IMU sensors in shoes or on the body, wireless communication modules, and processing algorithms. This segmentation allows the complex measurement function to be distributed across simple, low-cost components that can be manufactured and deployed widely, rather than requiring a single complex centralized system.
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 allows for objective, accessible, and continuous gait evaluation, providing a composite score that helps track disease progression, fall risk, and intervention effectiveness, improving patient care and reducing the burden on clinical resources.
Implementation Method 1
pressure sensor data can be leveraged to detect gait events, be used as a substitute for ground reaction forces, measure balance variables
Implementation Method 2
An accelerometer may allow for the calculation of spatial variables (e.g., step length, step width, step height, distance travelled)
Implementation Method 3
Gyroscope data can be used to calculate turning variables (e.g., mean, max, min turning angle/velocity) at the level of the foot
Implementation Method 4
inertial measurement unit (IMU; accelerometer, gyroscope, magnetometer (not always present))
Data Source
AI summary
Disclosed herein are systems and methods for monitoring and evaluating a user's gait, comprising receiving, by a computing device having a memory and a processor, from a pair of smart insoles communicatively coupled to the computing device and worn by the user, data measured by one or more types of sensors. The processor segmenting the data into gait-related segmented data comprising one or more of: gait cycle segmentation or activity type, and processing the gait-related segmented data to determine one or more of: gait patterns associated with the segmented data; gait parameters associated with the segmented data; gait phenotypes associated with the segmented data. The device determining, via one or more algorithms a composite movement quality score, based on a combination and interaction of at least two of: the segmented data, the gait patterns, the gait parameters, and the gait phenotypes.