Electromyography Course

Lesson 1 • Physiology of Muscle Electrical Activity

Explains action potential generation, propagation, and summation in skeletal muscle. Links cellular electrophysiology to measurable surface and needle signals.

Lesson 2 • History and Clinical Applications of EMG

Traces EMG development from early galvanometer studies to modern diagnostics. Contextualizes clinical, research, and occupational uses of the technique.

Lesson 3 • Principles of Bioelectrical Signal Generation

Describes volume conduction, dipole theory, and how tissue properties shape recorded EMG waveforms. Grounds students in the physics underlying electrode detection.

Lesson 1 • Noise Sources and Artifact Control

Identifies electrical, motion, and biological noise sources affecting EMG quality. Teaches shielding, grounding, and cable management strategies.

Lesson 2 • Analog-to-Digital Conversion

Covers sampling rate, bit depth, and aliasing prevention in EMG digitization. Ensures students configure acquisition parameters to preserve signal integrity.

Lesson 3 • Amplifiers and Signal Conditioning

Explains differential amplification, common-mode rejection, and gain settings. Connects amplifier specifications to signal fidelity and noise reduction.

Lesson 4 • Equipment Calibration and Maintenance

Establishes calibration protocols and routine maintenance schedules for EMG systems. Ensures measurement consistency and equipment longevity across sessions.

Lesson 1 • Crosstalk Detection and Minimization

Explains signal contamination from adjacent muscles and methods to verify selectivity. Protects data validity in multi-muscle and fine-motor recording scenarios.

Lesson 2 • Surface Electrode Placement Standards

Applies standardized anatomical landmarks for electrode positioning on major muscles. Ensures inter-session and inter-operator reproducibility of surface EMG data.

Lesson 3 • Skin Preparation Techniques

Details abrasion, cleaning, and impedance verification steps before electrode application. Directly reduces contact resistance and motion artifact in recordings.

Lesson 4 • Needle Electrode Insertion Techniques

Teaches safe insertion angles, depth estimation, and patient positioning for needle EMG. Minimizes patient discomfort and risk of vascular or nerve injury.

Lesson 1 • Rectification and Smoothing

Demonstrates full-wave rectification and envelope detection for amplitude estimation. Connects smoothed envelopes to muscle activation timing and magnitude analysis.

Lesson 2 • Filtering Techniques for EMG

Applies high-pass, low-pass, and notch filters to remove noise while preserving signal content. Teaches filter parameter selection based on recording context.

Lesson 3 • Frequency-Domain Analysis

Applies Fourier transforms to extract spectral features including median and mean frequency. Links spectral shifts to muscle fatigue and fiber type composition.

Lesson 4 • Time-Frequency Analysis Methods

Introduces short-time Fourier transform and wavelet analysis for non-stationary EMG. Enables tracking of spectral changes during dynamic muscle contractions.

Lesson 1 • Normal MUAP Reference Values

Presents age- and muscle-specific normative MUAP data and their statistical derivation. Provides the baseline against which pathological deviations are judged.

Lesson 2 • Quantitative EMG Techniques

Applies automated MUAP decomposition and multi-MUAP analysis for objective quantification. Reduces examiner bias and improves diagnostic reproducibility in clinical EMG.

Lesson 3 • Spontaneous Activity Identification

Identifies fibrillation potentials, positive sharp waves, fasciculations, and complex repetitive discharges. Correlates spontaneous activity types with specific pathological processes.

Lesson 4 • Recruitment and Firing Rate Analysis

Analyzes recruitment threshold, firing rate, and interference pattern during graded contractions. Links recruitment behavior to upper and lower motor neuron integrity.

Lesson 1 • Neuropathy and Radiculopathy Patterns

Distinguishes axonal, demyelinating, and mixed neuropathy patterns using NCS criteria. Correlates EMG paraspinal and limb findings with specific radiculopathy levels.

Lesson 2 • Myopathy and NMJ Disorder Diagnosis

Identifies short-duration, low-amplitude MUAPs and early recruitment characteristic of myopathy. Differentiates pre- and post-synaptic NMJ disorders via repetitive stimulation patterns.

Lesson 3 • Late Responses and Special NCS Techniques

Covers F-wave, H-reflex, and blink reflex methodology and clinical significance. Extends NCS capability to proximal nerve segments and reflex arc assessment.

Lesson 4 • Lesion Localization Strategies

Applies NCS and EMG findings to localize lesions to root, plexus, or peripheral nerve levels. Teaches systematic anatomical reasoning for electrodiagnostic localization.

Lesson 1 • EMG Normalization Methods

Compares maximum voluntary contraction, submaximal, and dynamic normalization approaches. Enables valid amplitude comparisons across subjects, sessions, and muscles.

Lesson 2 • EMG-Force and EMG-Torque Relationships

Examines linear and non-linear EMG-force relationships under isometric and dynamic conditions. Supports load estimation and muscle force modeling in occupational and sports contexts.

Lesson 3 • Gait and Functional Task Analysis

Integrates EMG with kinematics and kinetics to analyze muscle function during gait and daily tasks. Develops skills for interpreting muscle coordination patterns in rehabilitation contexts.

Lesson 4 • Muscle Onset and Offset Timing

Applies threshold-based and statistical methods to detect muscle activation onset and offset. Links timing accuracy to biomechanical event synchronization and motor control analysis.

Lesson 1 • High-Density Surface EMG

Introduces multi-electrode grid arrays for spatial mapping of motor unit territories. Extends conventional surface EMG to decomposition and muscle imaging applications.

Lesson 2 • EMG Biofeedback and Rehabilitation

Applies real-time EMG feedback to motor relearning, neuromuscular re-education, and pain management. Connects signal processing outputs to therapeutic intervention design.

Lesson 3 • Prosthetics and Human-Machine Interfaces

Covers EMG-driven prosthetic control, pattern recognition, and myoelectric signal classification. Prepares students for emerging roles in assistive technology and neural engineering.

Lesson 4 • Structured EMG Report Writing

Defines required report components: history, technique, findings, and impression sections. Trains concise, unambiguous language that supports clinical decision-making by referring providers.