EMG Frequency Power Spectra Analysis for Concussion Detection
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Solution Overview
Problem
Current diagnostic methods for mild traumatic brain injuries (mTBI) are inadequate, as they fail to detect mild cases, under-diagnose concussions, and lack objective and sensitive tests for assessing brain injury severity and recovery, leading to repetitive injuries and increased risks of neurodegenerative diseases.
Innovation Solution
A method and apparatus using electromyogram (EMG) signals to detect anomalies in frequency power spectra associated with brain injuries, involving EMG signal acquisition, transformation, feature extraction, and comparison against a database to diagnose mTBI and neurodegenerative diseases, utilizing EMG sensors and a portable device with signal processing algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If routine diagnostic brain imaging devices (CT, MRI, PET scan) are used, then focal brain damages can be detected, but mild traumatic brain injuries (mTBI) and diffuse axonal injuries cannot be detected
Solution Approach 1:
The patent replaces complex mechanical imaging systems (CT, MRI, PET scanners) with a simplified electromyography-based detection system. Instead of using large, expensive imaging equipment to detect brain injuries, the invention uses surface EMG sensors to record muscle electrical activity and analyzes frequency power spectra to identify mTBI and diffuse axonal injuries that imaging devices miss.
Solution Approach 2:
The patent introduces EMG signal analysis as an intermediary method between direct brain imaging and clinical diagnosis. Rather than imaging the brain directly or relying on subjective symptom assessment, the system uses muscle electrical activity as a mediator to indirectly detect brain injury effects, providing objective measurements of neurological function.
2Reliability
If brain imaging techniques are used to detect significant focal brain damages, then structural anomalies can be visualized, but the detection does not correlate with symptom severity and recovery outcomes
Solution Approach 1:
The patent changes the measurement parameter from structural imaging data to functional EMG frequency spectra. Instead of measuring anatomical structures that may appear normal in mTBI, the system measures electrical activity parameters (frequency power spectra) that reflect actual neurological function and correlate with symptoms and recovery.
Solution Approach 2:
The patent establishes a feedback loop where EMG measurements provide objective data about neurological function that directly correlates with symptom severity. This feedback mechanism allows clinicians to track recovery progress and adjust treatment based on measurable changes in muscle electrical activity patterns rather than relying on inconsistent imaging findings.
3Measurement precision
If EMG signals are transformed into frequency power spectra and analyzed, then objective and sensitive detection of mTBI is achieved, but the diagnostic process becomes more complex
Solution Approach 1:
The patent segments the EMG frequency spectrum into distinct bands (theta, alpha, beta, gamma) and analyzes power distribution across these segments. This segmentation simplifies the complex spectral analysis by breaking it into manageable frequency ranges, each with specific neurological significance, making the diagnostic process more systematic and interpretable.
Solution Approach 2:
The patent applies partial action by focusing analysis on specific frequency bands most relevant to mTBI detection rather than analyzing the entire spectrum in detail. This selective approach maintains high detection sensitivity while reducing computational complexity and processing requirements compared to a complete spectral analysis.
Data Source
AI summary
A method and a device for diagnosing brain injury (e.g. concussion) based on analysis of electromyogram (EMG) signals and presence of neurological modulation impairment of motor activity are described. The method consists of recording specific EMG signals under defined conditions, processing the acquired EMG signals, extracting the relevant information, and making diagnosis of brain injury and disorders that are associated with brain pathology. Specifically, the steps and device involved in the method include placing an EMG electrode set on the subject's body area, acquiring EMG signals from a subject's muscle(s) undergoing contraction, processing the acquired EMG signals using a signal processing algorithm that includes Fourier transformation. The resulting EMG data with a frequency domain (frequency power spectra) are then analyzed in comparison with databases stored in the device and used to determine anomaly of diagnostic value in the EMG power spectra from subjects. A diagnosis can be made based the altered EMG frequency power spectra that reflect the neurological modulation impairment of motor neurons. The diagnostic value, determination, management suggestions are displayed on the device.