Spasticity Assessment Using Characteristic Vector Analysis
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Solution Overview
Problem
Traditional methods for assessing spasticity in stroke patients are subjective and inconsistent, lacking objective and personalized approaches to rehabilitation.
Innovation Solution
A system combining electromyography (EMG) signal analysis with kinematic data from wrist movements, using a processing unit to calculate wrist joint torque and determine moment arms, which generates a characteristic vector to quantify spasticity and inform personalized rehabilitation strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional subjective evaluation methods (Modified Ashworth Scale, Tardieu Scale) are used to assess spasticity, then the assessment process is simple and quick, but the measurement precision and reliability are low due to clinician variability
Solution Approach 1:
The patent replaces the manual, mechanical assessment process with an automated system that uses sensors to detect muscle tone and reflex responses. The system objectively measures spasticity parameters through sensor data collection and processing, eliminating clinician subjectivity while maintaining assessment functionality.
Solution Approach 2:
The patent introduces a computational model and characteristic vector calculation system as an intermediary between the physical assessment and the final diagnosis. This intermediary processes sensor data through mathematical models to generate objective spasticity metrics, bridging the gap between raw measurements and clinical interpretation.
2Adaptability or versatility
If generic rehabilitation protocols are used for stroke patients, then the treatment process is simple to implement, but the adaptability to individual patient needs is poor
Solution Approach 1:
The patent applies local quality by creating personalized rehabilitation profiles for each patient based on their specific spasticity characteristics. The system tailors treatment parameters to individual patient needs rather than applying uniform protocols, with each patient receiving customized intervention based on their unique sensor data and characteristic vectors.
Solution Approach 2:
The patent implements dynamic adaptation of rehabilitation protocols by continuously monitoring patient progress through sensor measurements and adjusting treatment parameters accordingly. The system evolves the rehabilitation plan over time based on measured improvements or changes in spasticity, making the treatment adaptive rather than static.
3Reliability
If detailed sensor-based analysis with characteristic vector calculation is implemented, then the measurement precision and objectivity of spasticity assessment improve, but the device complexity and data processing requirements increase
Solution Approach 1:
The patent transforms complex sensor data into simplified characteristic vectors through parameter transformation. The system changes the representation of muscle tone and reflex data from raw sensor readings to standardized vector parameters that capture essential spasticity features, reducing data complexity while preserving diagnostic information.
Solution Approach 2:
The patent segments the complex assessment process into distinct functional modules: sensor data acquisition, signal processing, characteristic vector calculation, and clinical interpretation. This segmentation allows each module to handle specific tasks independently, reducing overall system complexity while maintaining comprehensive assessment capabilities.
Data Source
AI summary
The present invention relates to a system for assessing and rehabilitating spasticity in stroke patients, utilizing a novel approach that combines EMG signal analysis with kinematic data of wrist movements. The system comprises a set of electrodes for capturing EMG signals from key wrist muscles, a motion tracking module for monitoring wrist joint movements, and a processing unit for calculating and normalizing wrist joint torque. A distinctive feature is computation of a characteristic vector, indicative of the spasticity state, derived from the moment arms of the involved muscles. The system includes a motorized wrist system, designed to assist wrist movements in a direction countering the spasticity-induced pull, guided by the characteristic vector. This approach allows for personalized rehabilitation, adapting to the patient's specific muscular imbalances. The invention holds promise for enhanced assessment accuracy and tailored therapy in stroke rehabilitation, offering significant benefits for both clinical and home-based rehabilitation settings.