Wearable Gait Analytics System Using Sensor Fusion
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Solution Overview
Problem
Traditional clinical gait labs are not portable, user-friendly, and suffer from environmental bias, as they require subjects to perform tests in a laboratory setting, which does not reflect natural behaviors and may not be accessible to all individuals.
Innovation Solution
A wireless portable gait system comprising a wearable device with sensors such as three-axis accelerometers, gyroscopes, and pressure sensors that communicate with a mobile computing device for real-time analysis using statistical or machine learning-based classification to assess gait, balance, or posture, and predict the risk of slip, trip, and fall events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional clinical gait lab testing is used, then measurement precision can be achieved, but device complexity and lack of portability prevent ubiquitous testing
Solution Approach 1:
The system divides the traditional clinical gait lab into distributed wearable sensor nodes that can be independently worn and moved. Each sensor node captures specific gait parameters, and the collective data from multiple nodes reconstructs comprehensive gait analysis functionality in a portable, distributed manner.
Solution Approach 2:
The patent replaces the mechanical, fixed laboratory equipment with wireless sensor networks and digital signal processing. The physical gait lab infrastructure is substituted by electronic sensors, wireless communication modules, and computational algorithms that run on mobile devices, enabling gait analysis without fixed mechanical equipment.
2Measurement precision
If clinical gait lab testing is conducted in a laboratory setting, then controlled measurement conditions are achieved, but environmental bias occurs and natural behavior is not reflected
Solution Approach 1:
The system transitions from static laboratory measurements to dynamic, real-time monitoring in natural environments. The wearable sensors continuously adapt to the user's movements and environmental conditions, capturing gait data during actual daily activities rather than controlled lab simulations, thereby eliminating environmental bias while maintaining measurement quality.
Solution Approach 2:
The wearable device automatically performs calibration and adaptation to the individual user's gait patterns without requiring laboratory supervision. The system self-adjusts to natural walking behaviors and environmental variations, eliminating the need for controlled lab conditions while maintaining measurement accuracy through automated baseline establishment.
3Measurement precision
If traditional gait lab equipment is used, then comprehensive gait analysis is achieved, but ease of operation and user-friendliness are reduced
Solution Approach 1:
The wearable device integrates multiple sensing capabilities (accelerometers, gyroscopes, pressure sensors) into a single universal platform that performs various gait analysis functions. The same device can assess different gait parameters, monitor balance, and evaluate posture simultaneously, eliminating the need for multiple specialized laboratory equipment and simplifying user interaction to a single wearable unit.
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 user-friendly, accurate, and ubiquitous testing of gait, balance, or posture in real-time, providing personalized healthcare and real-time risk identification for slip, trip, and fall events, enhancing safety and health by allowing testing in natural environments.
Implementation Method 1
The sensors include a three-axis accelerometer, a three-axis gyroscope and an array of pressure sensors embedded within the wearable device
Implementation Method 2
The sensors include a three-axis accelerometer, a three-axis gyroscope and an array of pressure sensors embedded within the wearable device
Implementation Method 3
The sensors include a three-axis accelerometer, a three-axis gyroscope and an array of pressure sensors embedded within the wearable device
Data Source
AI summary
This disclosure relates to systems and methods to analyze gait, balance or posture information extracted from data collected by one or more wearable and connected sensor devices with sensors embedded therewithin. The embedded sensors include a three-axis accelerometer, a three-axis gyroscope and an array of pressure sensors. Sensor data detected by the sensors can be received by a mobile computing device, which can analyze the sensor data to identify a pattern related to gait, balance or posture within the sensor data; and apply a statistical/machine learning-based classification to the pattern related to gait, balance or posture to assign a clinical parameter to the pattern characterizing a risk of a slip, trip and fall event.