Wearable EMG Mapping for Muscle-Specific Signal Separation
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Solution Overview
Problem
Existing technologies face challenges in accurately determining the contribution of individual muscles or muscle groups to electromyography (EMG) data, particularly in the presence of anatomical variability and signal cross-talk, which hinders effective neuromuscular rehabilitation and virtual/augmented reality applications.
Innovation Solution
A wearable EMG measurement system with adjustable electrodes and electronic processing to derive spatial muscle activity, employing methods like average movement mapping, system of movement equations, and blind source separation to disentangle muscle contributions from EMG data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional EMG measurement methods are used, then EMG data can be collected, but the contribution of individual muscles cannot be accurately determined due to signal cross-talk and anatomical variability
Solution Approach 1:
The patent segments the EMG signal processing into multiple independent muscle group analyses. By dividing the complex EMG data into separate muscle-specific components through processing pipelines that analyze different muscle groups independently, the system resolves signal cross-talk and accurately attributes activity to specific muscles or muscle groups.
Solution Approach 2:
The patent introduces an intermediary processing layer between raw EMG data and muscle activity interpretation. This intermediary system uses machine learning models and processing pipelines that act as mediators to disentangle mixed EMG signals and identify the specific muscle contributions, transforming ambiguous raw data into precise muscle-level insights.
2Adaptability or versatility
If fixed electrode arrangements are used, then device simplicity is maintained, but adaptability to different anatomies is reduced
Solution Approach 1:
The patent implements dynamic electrode arrangements that can be adjusted based on individual anatomy. The system allows flexible positioning of electrodes and dynamically adapts the processing pipeline to account for variations in muscle location and signal characteristics across different users, enabling the same device to accurately measure diverse anatomical configurations.
Solution Approach 2:
The patent changes processing parameters based on anatomical variability. The system adjusts measurement parameters, electrode placement guidelines, and analysis algorithms according to individual anatomical characteristics, allowing the device to maintain high measurement accuracy across different body types without requiring complex hardware modifications.
3Loss of information
If comprehensive EMG data collection is performed, then complete muscle activity information is obtained, but processing complexity and time increase
Solution Approach 1:
The patent performs preliminary processing and filtering of EMG data during data collection. By pre-processing signals to remove noise and preliminary identify active muscle groups before full analysis, the system reduces the computational burden of subsequent processing while maintaining complete muscle activity information, thereby reducing overall processing time.
Solution Approach 2:
The patent implements a tiered processing approach where essential muscle activity information is extracted through streamlined processing for time-sensitive applications, while more comprehensive analysis is available when time permits. This partial action approach provides sufficient information for most applications without requiring full exhaustive processing.
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 precise identification of muscle activity for volitional intent decoding, neuromuscular debilitation assessment, and accurate garment placement, enhancing neuromuscular rehabilitation and virtual/augmented reality systems.
Implementation Method 1
a plurality of electrodes arranged on the garment to contact skin of the anatomical region when the garment is worn on the anatomical region of the associated wearer, electronics operatively connected with the plurality of electrodes and configured to measure EMG data emanating from the anatomical region
Data Source
AI summary
An electromyography (EMG) measurement device includes a garment configured to be worn on an anatomical region of an associated wearer, a plurality of electrodes arranged on the garment to contact skin of the anatomical region when the garment is worn on the anatomical region of the associated wearer, electronics operatively connected with the plurality of electrodes and configured to measure EMG data emanating from the anatomical region, and an electronic processor programmed to derive a contribution of spatial muscle activity of a target muscle or muscle group to the measured EMG data.