Motor Function Assessment Using Motion Shape and Symmetry Indexing
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Solution Overview
Problem
Current motor function assessments for neuromuscular disorders like SMA and DMD are unable to quantitatively measure incremental changes in patient progress due to the use of ordinal, subjective rating scales and infrequent clinical visits, and are confounded by factors such as device positioning, limb length variations, and phase variability, making it difficult to monitor the effectiveness of emerging therapies.
Innovation Solution
A computerized system using wearable sensors and imaging devices to gather motion shape, symmetry, and kinetic energy data, combined with machine learning, calculates a composite index to quantify motor function by aligning and analyzing motion trajectories, accounting for shape, symmetry, and speed factors, and incorporating ultrasound and dynamometry for muscle scoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional ordinal rating scales are used for motor function assessment, then the assessment is simple to administer, but the ability to detect incremental changes in motor function is lost
Solution Approach 1:
The patent replaces traditional manual clinical assessment with automated wearable sensors and computer vision systems. The wearable sensors (accelerometers, gyroscopes) and imaging devices automatically capture motion data, which is then processed by machine learning algorithms to generate quantitative motor function scores. This substitution enables continuous, objective measurement of motor function changes without requiring manual administration of rating scales.
Solution Approach 2:
The patent transforms motor function assessment from ordinal categories to continuous quantitative parameters. By measuring multiple motion parameters (amplitude, velocity, acceleration, symmetry) and combining them through machine learning models, the system generates precise numerical scores that can detect even incremental changes in motor function, replacing the coarse granularity of traditional rating scales.
2Measurement precision
If frequent clinical visits are conducted to monitor patient progress, then the temporal dynamics of neuromuscular disorders can be tracked, but the cost and burden on patients increases
Solution Approach 1:
The patent enables continuous monitoring of motor function through wearable sensors that operate continuously in the patient's natural environment. The system collects motion data during daily activities without requiring patients to return to the clinic, providing uninterrupted temporal coverage of motor function progression and eliminating the need for periodic visit interruptions.
Solution Approach 2:
The system allows patients to self-monitor their motor function through wearable devices they wear during daily activities. The automated data collection and analysis eliminate the need for active participation in structured clinical assessments, reducing the time and effort required from patients while maintaining continuous monitoring capability.
3Productivity
If wearable sensors are used to capture motion data, then continuous monitoring is enabled, but the data is affected by confounding factors such as device positioning, limb length variations, and phase variability
Solution Approach 1:
The patent segments the motion data into distinct components (amplitude, velocity, acceleration, symmetry) and analyzes each separately. By breaking down the complex motion signal into manageable segments, the system can apply specific normalization and correction techniques to each component, reducing the impact of confounding factors like device positioning and limb length variations.
Solution Approach 2:
The patent applies multiple transformation techniques to the raw sensor data, including normalization by limb length, temporal alignment to account for phase variability, and conversion to invariant representations. These parameter transformations adjust the data to compensate for confounding factors while preserving the underlying motor function information.
4Measurement precision
If multiple sensors and imaging devices are integrated into the system, then comprehensive motor function assessment is achieved, but the device complexity increases
Solution Approach 1:
The patent employs a multi-functional wearable sensor suite where accelerometers, gyroscopes, and magnetometers simultaneously capture multiple motion parameters (position, orientation, velocity, acceleration). This universal sensor approach consolidates what would otherwise require multiple separate devices into a single integrated system, reducing overall complexity while maintaining comprehensive assessment capability.
Data Source
AI summary
A computerized system calculates a composite index for sets of functional movement scores that quantify motor function abilities for patients. Wearable sensors, kinetic energy sensors, ultrasound imagers, and force sensors are used to store the composite index from predictors of the functional movement scores, the predictors comprising a respective shape of motion factor, a respective motion symmetry factor, and a respective motion speed factor for each of the sets of functional movement scores. The software tabulates the respective composite index by calculating a probability that the respective shape of motion factor, the respective motion symmetry factor, and the respective motion speed factor correspond to one of the sets of functional movement scores.