Myogenic noise refers to unwanted electrical signals generated by muscle activity that interfere with the measurement of fainter physiological processes. This interference is a common challenge in biomedical signal processing, where clinicians and researchers rely on electrical recordings to diagnose conditions. The noise is an artifact that contaminates diagnostic measurements like brain or heart activity, making it necessary to understand this source of interference for accurate interpretation.
How Muscle Activity Generates Interference
Muscle fibers are electrically excitable cells that activate through an action potential. This action potential is a rapid change in the electrical voltage across the muscle cell membrane, which travels along the fiber and triggers contraction. When a muscle contracts, even subtly, it generates a measurable burst of electrical energy known as an electromyogram (EMG) signal.
This electrical discharge is the origin of myogenic noise, which acts much like static interference. The frequency spectrum of this muscle activity is broad, typically ranging from a few Hertz up to 500 Hertz, with dominant energy concentrated between 50 and 150 Hertz. Because this muscle signal has a higher amplitude, in the millivolt range, it can easily overwhelm weaker signals originating from the brain or heart. Electrodes placed on the skin capture this muscle activity, corrupting the final recording.
Where Myogenic Noise Impacts Medical Signals
Myogenic noise poses a significant problem across several major non-invasive diagnostic tests, particularly those that measure minute electrical changes. The impact is most profound in Electroencephalography (EEG), where the goal is to record the brain’s extremely weak electrical impulses. Brain waves are measured in the microvolt range, meaning they are thousands of times smaller than the millivolt-level electrical activity produced by muscle contraction.
Contractions in the face, neck, and scalp muscles are highly disruptive to EEG signals. Because the muscle’s frequency range overlaps significantly with the brain’s electrical frequencies, the resulting contamination can completely obscure the faint brain waves needed for analysis. Movement or tension from jaw clenching, blinking, or slight head movements can render an EEG recording unusable for diagnosis.
The noise also affects Electrocardiography (ECG), which records the heart’s electrical rhythm. While heart signals are much stronger than brain signals, movement and muscle tension in the chest, arms, or back can still introduce high-frequency artifacts. This is particularly problematic during stress tests, where a patient is exercising, or in long-term monitoring, where movement is unavoidable. The muscle noise can obscure subtle patterns in the ECG that are important for analyzing heart rhythm abnormalities.
Managing and Reducing the Interference
Managing myogenic noise involves a combination of procedural precautions and advanced technical processing. Procedural mitigation begins with ensuring the patient is relaxed and still during the recording session. Careful placement of electrodes away from large muscle groups, such as the neck and shoulder muscles, is a standard practice to minimize contamination.
Technological mitigation relies on digital signal processing techniques to separate the noise from the desired signal after it has been recorded. Since muscle activity has a characteristic frequency signature, specialized software employs digital filtering to isolate and mathematically remove the unwanted range. Techniques like adaptive filtering and Blind Source Separation are used to estimate the noise component and subtract it from the overall recording. This filtering process allows clinicians to extract the underlying, clean physiological signal necessary for accurate analysis.