Gait Cycle Segmentation via Cross-Frame Stability Detection
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Solution Overview
Problem
Current gait analysis methods are subjective, invasive, and limited in their ability to objectively assess gait parameters, especially in non-clinical settings, due to the need for wearable devices or marker-based systems that require precise positioning and are not robust against variations in viewing angles and body movements.
Innovation Solution
A computer-implemented method using a single non-calibrated camera to analyze gait cycles by detecting cross-frame stability of features, such as edge or silhouette pixels, to segment gait into cycles without requiring body part detection, allowing for objective evaluation of stride duration, cadence, and stride length, and enabling monitoring in daily activities without devices or markers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wearable sensors are used to capture gait signals, then objective measurement of gait parameters is improved, but device complexity and user comfort deteriorate due to the need to place devices on the subject's body
Solution Approach 1:
The patent replaces the mechanical wearable sensor system with an optical camera-based system. Instead of using accelerometers, gyroscopes, or other mechanical sensors attached to the body, the invention uses a camera to capture visual data and extract gait parameters through image processing and analysis of body position changes over time, thereby eliminating the need for physical device attachment while maintaining measurement capability
Solution Approach 2:
The patent creates a visual copy or representation of the gait motion through camera imaging. By capturing and analyzing the visual sequence of body positions, the system reconstructs gait parameters from the optical copy of the motion rather than direct mechanical measurement, allowing remote assessment without physical contact
2Measurement precision
If marker-based systems are used for gait analysis, then measurement precision is improved, but ease of operation deteriorates due to the need for precise marker positioning and compliance from the subject
Solution Approach 1:
The patent extracts and eliminates the markers from the gait analysis system. Instead of requiring physical markers to be placed on body joints and segments, the invention processes raw visual data directly from the camera to identify body positions and calculate gait parameters, removing the intermediate marker component entirely while preserving the ability to measure joint angles and segment positions
Solution Approach 2:
The patent enables the system to automatically identify and track body segments and joints without requiring subject cooperation for marker placement. The image processing algorithms autonomously detect body contours, identify key anatomical points, and calculate gait parameters from the visual data alone, making the system self-sufficient and eliminating the need for subject involvement in the setup process
3Ease of operation
If traditional semi-subjective clinical assessment scales are used, then ease of operation is improved, but measurement precision deteriorates due to subjective variability in specialist evaluation
Solution Approach 1:
The patent replaces the human specialist's subjective visual assessment with an automated computer-based image analysis system. The camera captures objective visual data and processing algorithms calculate precise gait parameters such as stride length, cadence, and joint angles, eliminating the variability inherent in human observation while maintaining operational simplicity through automatic processing
Solution Approach 2:
The patent implements an automated feedback system where the camera continuously captures gait data and the processing system provides real-time or near-real-time objective measurements of gait parameters. This automated feedback loop replaces the delayed and subjective feedback from clinical scales with continuous, quantifiable, and objective data that can be used for immediate assessment and monitoring
Data Source
AI summary
A computer-implemented system and method for gait analysis of a subject. The method includes obtaining visual data from an image capture device positioned in front of or behind the subject, the plurality of image frames capturing at least one gait cycle of the gait of the subject, detecting one or more prescribed features within the plurality of image frames, analyzing each of the plurality of image frames to detect cross-frame stability of the one or more prescribed features, and segmenting the gait of the subject into at least one gait cycle based at least in part on the detected cross-frame stability of the one or more prescribed features.