Inertial Sensor Gait Analysis for Limb Symmetry and Repeatability
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Solution Overview
Problem
Individuals with lower limb amputation exhibit asymmetrical gait patterns, which increase the risk for secondary health conditions and impact mobility and quality of life, but traditional gait assessment methods require expensive equipment and expertise.
Innovation Solution
Utilizing inertial sensors to measure symmetry and repeatability in jointed limbs by acquiring gait data, segmenting stride signals, and calculating gait metrics such as symmetry and repeatability metrics through dynamic time warping, enabling objective assessment without the need for costly equipment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional gait assessment methods are used, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent replaces complex mechanical gait laboratory equipment with inertial sensors that use accelerometers and gyroscopes to measure motion. This substitution maintains measurement precision while dramatically reducing device complexity and cost, as the inertial sensors are compact, portable, and require no complex mechanical infrastructure.
Solution Approach 2:
The patent creates a simplified digital model of gait analysis by using inertial sensors to capture motion data and processing it through algorithms that replicate the functionality of complex gait laboratories. This allows accurate gait assessment without requiring the physical infrastructure of traditional methods.
2Measurement precision
If traditional gait assessment methods are used, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The system enables self-service gait assessment by allowing patients to wear the inertial sensors and perform gait analysis independently without requiring specialized technicians or operators. The automated data processing and metric calculation further reduce the need for expert intervention, making the assessment process accessible to a broader range of users.
Solution Approach 2:
By replacing manual, expert-dependent assessment methods with automated inertial sensor-based systems, the patent eliminates the need for specialized technical expertise. The system automatically processes raw sensor data into meaningful gait metrics, significantly improving ease of operation while maintaining measurement precision.
3Measurement precision
If traditional gait assessment methods are used, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The inertial sensors continuously capture gait data throughout the entire walking process without interruption, unlike traditional methods that require staged assessments. This continuous data collection, combined with automated real-time processing, eliminates idle time and significantly reduces the total assessment time while maintaining comprehensive measurement precision.
Solution Approach 2:
The automated digital processing system replaces time-consuming manual analysis procedures. The inertial sensor data is automatically processed through algorithms that rapidly calculate gait metrics, reducing assessment time from hours or days to minutes while preserving measurement accuracy.
Data Source
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AI summary
Quantification of symmetry and repeatability in limb motion for treating abnormal motion patterns. In the context of gait analysis, gait data may be acquired as signals from inertial sensors (e.g., gryoscopes). Each signal represents an angular velocity of a lower limb segment of a subject during ambulation. Each signal may be segmented into stride signals, and a gait metric may be calculated based on the stride signals. The gait metric may comprise a symmetry metric that represents a similarity of the stride signals across two signals acquired for at least one pair of contralateral limb segments. Additionally or alternatively, the gait metric may comprise a repeatability metric that represents a similarity of the stride signals within a signal. In other embodiments, other types of sensors may be used and/or motion data may be acquired and metrics calculated for other types of motions and/or for upper limb segments.