Wireless EMG Sensor Array for Objective Muscle Function Quantification
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Solution Overview
Problem
Current medical diagnostic apparatuses and methodologies lack the ability to objectively quantify orthopedic movement function and physical therapy dysfunction across various body regions, compare severity, and measure patient management progression from pre- to postoperative status.
Innovation Solution
A system comprising sensors with electromyographic and gyrosensors that measure muscle activity and transmit electrical signals for comparison with reference data from healthy individuals, generating a personalized rehabilitation training plan that adapts to individual joint progress and abilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional subjective assessment methods are used for muscle function evaluation, then the assessment process is simple and quick, but the measurement precision and objectivity are insufficient
Solution Approach 1:
The patent replaces traditional mechanical/manual assessment methods with an electronic sensor-based system. EMG sensors detect electrical signals from muscle fibers, while force sensors measure mechanical output objectively. This substitution transforms subjective visual assessment into quantifiable electrical and mechanical data, significantly improving measurement precision while the modular sensor design keeps device complexity manageable.
Solution Approach 2:
The patent introduces computational algorithms and processing systems as intermediaries between the raw sensor data and the final assessment results. The processor analyzes EMG signal amplitude and frequency, correlates electrical activity with mechanical force output, and generates comprehensive muscle function reports. This intermediary layer transforms complex sensor data into clinically actionable insights without requiring the physical assessment device itself to be overly complex.
2Measurement precision
If comprehensive sensor arrays are deployed to measure multiple muscle parameters, then the measurement precision improves, but the device complexity and ease of operation deteriorate
Solution Approach 1:
The patent combines multiple sensor types (EMG electrodes, force sensors, motion sensors) into an integrated sensor array that can be applied as a unified unit. The sensors are positioned according to standardized anatomical landmarks, allowing simultaneous measurement of electrical activity, force, and movement across multiple muscle groups. This merging approach maintains comprehensive measurement capability while simplifying the application process through standardized protocols and pre-positioned sensor configurations.
Solution Approach 2:
The patent segments the measurement system into modular sensor units that can be independently applied to different muscle groups. Each sensor module is self-contained with specific placement instructions for targeted muscle assessment. This segmentation allows clinicians to apply only the necessary sensors for each specific clinical question, reducing overall complexity while maintaining measurement precision for the assessed parameters.
3Measurement precision
If reference data from healthy cohorts is collected and compared, then the ability to quantify dysfunction severity improves, but the loss of time for data processing increases
Solution Approach 1:
The patent performs preliminary actions by pre-collecting and storing reference data from healthy cohorts in a standardized database before clinical use. Normal ranges, percentiles, and expected values for various muscle functions are established in advance. When a patient is assessed, the system automatically retrieves and compares patient data against this pre-prepared reference framework, enabling rapid dysfunction severity quantification without manual comparison processes.
Solution Approach 2:
The patent implements automated feedback mechanisms where the system continuously compares real-time sensor measurements against stored reference data and provides immediate diagnostic feedback. The processor analyzes deviations from normal ranges and generates real-time assessments of muscle function status. This automated feedback loop eliminates manual data comparison time while maintaining precise dysfunction severity quantification through continuous algorithmic evaluation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables objective quantification of muscle activity and orthopedic movement function, allowing for tailored rehabilitation plans that improve muscle strength and coordination, effectively guiding patient recovery and therapy progression.
Implementation Method 1
The plurality of sensors may include sleeves with inwoven electromyographic sensors. The plurality of sensors may measure electrical signals generated by muscle cell activation.
Data Source
AI summary
A method and system for determining rehabilitation treatment of a joint, the method comprising communicatively connecting to a plurality of sensors attached to an individual at muscles in a joint area, wherein the plurality of sensors transmit electrical signals generated by the muscle to the computing device. The method further comprising receiving the electrical signals from the plurality of sensors, generating initial measurement data by evaluating strength and activity level of the muscles based on the electrical signals, and comparing the initial measurement data with reference data, wherein the reference data includes measurements of healthy people with normal muscle function. The method further comprising generating a training plan based on the comparison.