Post 1: The basics
About the EAdi blog
Having spent my career on topics involving the acquisition, processing, physiology, and implementation of Electrical Activity of the Diaphragm (EAdi), I initiated this blog to try to create a community for those with an interest in EAdi. The blog is intentionally written in a simple way to provide easy access to the topic and to provide basic knowledge that stimulates the interest about EAdi. The main aim is to facilitate the understanding, to generate questions, and to introduce topics for discussion related to the EAdi and its applications. My interest is to initiate good discussions. No question nor topics are too simple discuss. This first blog will address the very basics of electromyography.
Every muscle initiates its contraction by electrical impulses generated by muscle cell membrane potentials. Electromyography (EMG) is the art of measuring these potentials. Many methods are used, including sensors placed on the skin surface, inserted needles or wire electrodes, and esophageal electrodes. A general description of EMG can be found at http://en.wikipedia.org/wiki/Electromyography.
Diaphragm electromyogram (EMGdi)
This term has been used interchangeably for EMG of the diaphragm measured during both spontaneous breathing and during direct muscle or nerve stimulation of the diaphragm. Earliest publications of measurements of the diaphragm’s electrical activity date back to the late 1950’s. PUBMED’s first description of trans-esophageal measurements is from 1959.
Diaphragm electrical activity (EAdi or Edi)
This term was introduced to specifically address the “diaphragm electromyogram” during spontaneous breathing i.e. not related to artificially evoked action potentials. In other words, the EAdi or Edi generally refers to a vital sign related to neural respiratory drive, describing neural respiratory timing or central apnea as well as the magnitude of neural inspiratory efforts.
EMG measurements can be performed by different methods, the most common being the use of either monopolar or bipolar electrode configurations:
- Monopolar electrode recordings: the amplifier measures the signal from one electrode placed in the area of interest and relates it to a ground reference electrode placed in an electrically silent area. This method is for example used for the electrocardiogram (ECG) which generates a synchronized (deterministic) signal with good signal to noise ratio. With regards to the EMG, monopolar recordings are typically limited to intramuscular needle and wire recordings.
- Bipolar electrodes (differential) recordings: the amplifier measures the difference between two electrodes (placed in the area of interest) and relates their difference to ground. The differentiation/subtraction between two electrodes in the signal area cancels signals that affects both electrodes similarly, thus improving the so-called “common-mode-rejection-ratio”. This method is particularly useful for surface and trans-esophageal electrode EMG measurements since signals are weaker than intramuscular recordings.
The single fiber action potential
Each time a motor nerve-ending activates a muscle fiber: it starts an all-or-nothing process of activating ion channels that results in a change in membrane electrical potential propagating away from the endplate (http://en.wikipedia.org/wiki/Membrane_potential). This so-called single fiber action potential acts to initiate the contractile process of the muscle fiber. Both amplitude and propagation velocity of the action potential can be measured.
The motor unit action potential
Since every nerve fiber divides into several endings, where each ending may have a different length, many single fiber action potentials can be induced by the same nerve, however, with a slight time difference due to the difference in length of nerve endings and start positions (synapses) on the muscle fibers. If the time difference (due to the difference in length of nerve endings) is small, the motor unit action potential represents mainly a summation of several single fibers in space (so-called spatial summation), which in turn affects its amplitude.
With the exception of the heart, spontaneous activation of striated muscle occurs via increased motor units recruitment and increased motor unit firing rate. This activation of different motor units is not synchronized. As a spontaneous muscle contraction increases its force generation, the degree of motor unit action potentials recruited and their firing rate will increase and it will be more and more difficult to distinguish single motor unit action potentials, resulting in a typical interference pattern signal.
Increases of signal energy depends on spatial summation of motor unit action potentials as well as on increasing temporal summation.
Compound motor unit action potential
If multiple motor unit action potentials are evoked synchronously (i.e. motor units are stimulated at the same time by phrenic nerve pacing, electromagnetic stimulation etc.), this results in a so-called compound motor unit action potential, a deterministic signal which in some ways is initiated in a similar fashion as the ECG signal. Due to its synchronized initiation, the amplitude of the compound motor unit action potential mainly relates to spatial summation.
Time and frequency domain of the EMG
The EMG can be presented as a continuous signal with time, often referred to as “raw-EMG”. This signal represents amplitudes as well as frequency components of the signal. Such analysis can be relatively simple when dealing with, single fiber, single motor unit, and compound motor unit action potentials, since it could involve simple measures of e.g. amplitude, area, and duration. However, during spontaneous contractions, quantification of the interference pattern EMG is more complicated. To determine the amplitude, signal segments of certain duration are rectified by e.g. applying absolute or square functions such that their area or mean amplitudes can be calculated. Typical measures to describe the amplitude of the inference pattern signal are RMS (the root mean square – energy based measure) and FRA (fully rectified average – linear amplitude measure). For simple quantification of frequency content of the time domain signal, the number of turn-points or zero-crossings can be counted. For more advanced frequency analysis, Fourier transforms, auto-correlation algorithms, and decomposition methods are used.
The next post (#2) will focus more towards the specific acquisition and processing of the EAdi signal.