Wearable Camera Gait Analysis for Fall Risk Prediction
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Solution Overview
Problem
Current gait analysis methods are inefficient and costly, requiring trained therapists and expensive equipment, and fail to effectively predict fall risk in a timely manner, as they often rely on subjective measures and are not suitable for widespread implementation.
Innovation Solution
A smart gait analysis system using a camera and processing unit, such as a smartphone, to capture and analyze gait parameters like step length, step width, and stride time variability, providing real-time data and biofeedback to assess fall risk and facilitate gait retraining.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive gait analysis by physical therapist is used, then measurement precision of gait parameters is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses video recording to create a visual copy of the gait motion, which can then be analyzed frame-by-frame. This replaces complex physical measurement equipment with a simpler optical copying system that captures movement data through standard video technology.
Solution Approach 2:
The patent replaces mechanical gait analysis equipment and manual measurement tools with a video-based optical system. The mechanical complexity of traditional gait labs is substituted with electronic video recording and digital image processing, reducing physical device complexity while maintaining measurement capability.
2Measurement precision
If comprehensive gait analysis by physical therapist is used, then measurement precision of gait parameters is improved, but loss of time increases
Solution Approach 1:
The patent performs preliminary video recording of the gait motion before detailed analysis. By capturing the entire motion sequence in advance, the actual measurement and analysis can be conducted efficiently without requiring the patient to undergo time-consuming manual measurement procedures during the analysis phase.
Solution Approach 2:
The video recording creates a permanent copy of the gait motion that can be analyzed repeatedly without requiring the patient to repeat the performance. This allows thorough analysis of multiple parameters from a single recording, reducing total assessment time while maintaining precision.
3Reliability
If environment-based detection with pressure sensors and video cameras is used, then reliability of fall detection is improved, but device complexity and cost increase
Solution Approach 1:
The patent extracts the essential detection function from complex environment-based systems and implements it using a wearable video camera on the patient. This removes the need for complex embedded pressure sensors in floors and multiple environmental cameras, simplifying the system while maintaining fall detection capability through portable video monitoring.
4Adaptability or versatility
If wearable detectors with accelerometers and gyroscopes are used, then adaptability to different environments is improved, but measurement precision of gait parameters deteriorates
Solution Approach 1:
The patent uses video recording to create an optical copy of gait motion, which can then be measured with high precision through frame-by-frame analysis. This visual copying method provides more accurate gait parameter measurement compared to accelerometer/gyroscope data, while the wearable camera maintains environmental adaptability.
Solution Approach 2:
The patent replaces inertial measurement units (accelerometers and gyroscopes) with a video-based optical measurement system. This substitution improves measurement precision by using visual tracking and image processing to capture gait parameters, while the wearable camera design maintains adaptability to various environments.
Data Source
AI summary
A method for acquiring gait parameters of an individual is disclosed. The method includes capturing calibration images from foot marker placed on feet or shoes of an individual while an individual is standing still, the calibration images are obtained from a camera worn by the individual, capturing subsequent time-varying images from the foot markers while the individual is walking, and comparing the calibration images to the subsequent time-varying images by a processing unit that is coupled to the camera to determine changes between the initial relative image size of the foot markers and the time-varying images of the foot markers as a function of time to analyze gait of the individual.