Advanced Biomechanics of
Physical Activity (KIN 831)
Electromyography (EMG)
Material included in this presentation is derived primarily from two sources:
* http://www.delsys.com/library/tutorials.htm
* Nigg, B. M. & Herzog, W. (1994). Biomechanics of the musculo-skeletal system. New York: Wiley & Sons
* Winter, D.A. (1990). Biomechanical and motor control of human movement. (2nd ed.). New York: Wiley
& Sons
Electromyography (EMG)
• Electro – electrical
• Myo – muscle
• Graphy – record
-------------------------------------------------------Electromyography – involves recording the
electrical activity of muscle
Electromyogram – electrical signal associated
with the contraction of a muscle
Selected
Historical
Events Related
to EMG
• Andreas Vesalius,
“father of modern
anatomy”, appearance
and geography of
dead muscle, 1555
Selected Historical Events
Related to EMG
• William Croone, in De Ratione Motus
Musculorum concluded from nerve section
experiments that the brain must send a signal to
the muscles to cause contraction, 1664
• Physiologists became excited over the phenomena
produced by electrical stimulation of muscles,
1740
Selected Historical Events
Related to EMG
• Albrecht von Haller (1708-1777) summarized
many of the earlier studies in his treatise on
muscular irritability.
• Robert Whyatt (1714-1766) reported clinical
observations on a patient treated by
electrotherapy.
• “Animal electricity” was proposed as a substitute
for the “animal spirits” which earlier experiments
believed to be the activating force in muscular
movement.
Selected Historical Events
Related to EMG
• Luigi Galvani (1737-1798) studied the effects of
atmospheric electricity upon dissected frog muscles.
He concluded that the movement of the muscle was
the result of its exterior negative charge uniting with
the positive electricity which proceeded along the
nerve (1786). Galvani’s Commentary on the Effects
of Electricity on Muscular Motion (1791 or 1792) is
probably the earliest statement of the presence of
electrical potentials in nerve and muscle. He
showed that electrical stimulation of muscular
tissues produced contraction and force. He is
considered the “father of experimental neurology.”
Galvani’s
demonstrations
of the effects of
electricity on
muscles of
frogs and sheep
(De viribus
electricitatis in
motu musculari
commentarius,
1792)
Selected Historical Events
Related to EMG
• “animal electricity” became the absorbing
interest of the physiological world. The greatest
name among the early students of the subject
was Emil DuBois-Reymond (1818-1896). He
laid the foundation of modern electrophysiology.
He was probably the first to discover and
describe that contraction and force production of
skeletal muscle were associated with electrical
signals originating from the muscles (1849).
Selected Historical Events Related
to EMG
Guillaume Benjamin
Amand Duchenne
(1806-1875) set out
to classify the
functions of
individual muscles
through electrical
stimulation. He
recognized the
problem of
attempting to isolate
muscle contractions.
Duchenne’s book, Physiology des Movements (1865), has been
acclaimed “one of the greatest books of all time.” He was probably
the first to perform systematic investigations of muscular function
using an electrical stimulation approach.
Guillaume
Benjamin Amand
Duchenne de
Boulogne
investigating the
effect of electrical
stimulation of the
left frontalis muscle
on one of his
cooperative
(prisoner) subjects
Selected Historical Events
Related to EMG
• Wedinski (1880) demonstrated the existence of
action currents in human muscle. Practical use
had to await the invention of a sensitive string
galvanometer (W. Einthoven - 1906).
Selected Historical Events
Related to EMG
• The physiological aspects of EMG were first
discussed (1910-1912) by H. Piper of Germany
• E.D. Adrian, in an article in Lancet (1925, vol. 2,
pp. 1229-1233) entitled “Interpretation of the
Electromyogram” demonstrated for the first time
that it was possible to determine the amount of
activity in a human muscle at any stage of
movement.
Selected Historical Events
Related to EMG
• Toward the end of WWII, with marked improvement
of electronic apparatus; anatomists, kinesiologists,
and orthopedic surgeons began to make increasing
use of EMG. The first study that gained wide
acceptance was that of Inman, Saunders, and Abbott
who reported their work on the movements of the
shoulder region in “Observation on the Function of
the Shoulder Joint” in the Journal of Bone and Joint
Surgery (1944, vol. 26, pp. 1-30).
We
have
come
a long
way!!!
Selected Historical Events
Related to EMG
• During the 1950’s and beyond , EMG for
kinesiological studies became widespread.
EMG of
normal
gait???
Note the
use of
event
markers
in the
foot.
Selected
Historical
Events Related
to EMG
• John Basmajian
(1921- ) wrote the
bible of
electromyography
entitled Muscles
Alive. He and Carlo
De Luca summarized
the existing
knowledge and
research on muscle
function as revealed
by EMG studies.
Copper
screen
cage to
inhibit
noise in
the EMG
signal
Typical multifactorial
gait-recording
showing:
A. Angular
accelerometer on the
left leg
B. Vertical
accelerometer
C. Horizontal
accelerometer
D. Strain gauge
tensiometer on left
gastrocnemius
E. EMG of left
gastrocnemius
Electromyography is a seductive muse because it provides
an easy access to physiological processes that cause the
muscle to generate force, produce movement and
accomplish the countless functions which allow us to
interact with the world around us. The current state of
Surface Electromyography is enigmatic. It provides many
important and useful applications, but it has many
limitations which must be understood, considered and
eventually removed so that the discipline is more
scientifically based and less reliant on the art of use. To
its detriment, electromyography is too easy to use and
consequently too easy to abuse.
C. J. De Luca, 1993
Schematic Representation of a Recording an EMG
Signal from a Single Muscle Fiber
•Measure of changes in
electrical potential across
the muscle fiber
•At rest, potential ≈ -90mv
•With sufficient stimulation
potential inside cell rises to
≈ 30-40mv
•Change in potential (fiber
action potential) can be
recorded
•Action potentials from
multiple fibers in a motor
unit are simultaneously
recorded
•Signal from depolarization
of a motor unit is called
motor unit action potential
Electrophysiology of Muscle Contraction
1. Motor unit action potential (muap) – change
in electrical potential across the muscle fiber
membranes when a motor unit is stimulated
beyond a critical threshold
2. Electrodes placed inside (indwelling) or on
the surface of a muscle record the algebraic
sum of all muap’s transmitted along muscle
fibers that reach the electrodes
3. Motor units far away from the electrode have
their muap attenuated (i.e., are smaller)
4. Motor units of a muscle are controlled by
motor neurons activating them at their motor
end plates
Electrophysiology of Muscle Contraction
5. End plate potential (EPP) – depolarization of
post synaptic membrane
6. EPP that reach a threshold initiate action
potential in muscle fiber membrane
7. Depolarization of the transverse tubular
system and sarcoplasmic reticulum results in a
depolarization wavealong the direction of the
muscle fibers
8. EMG records the depolarization and
subsequent repolarization
Two Categories of Electrodes
1. By placement of electrode:
• Surface
• Indwelling (needle)
Delsys Surface Electrodes
Delsys
Surface
Electrodes
Comparison between Recording Areas of Two
Types of Surface Electrodes
• Indwelling (needle)
Steps in making a bipolar
fine-wire electrode
(Basmajian and Stecko, 1962)

Surface vs. Indwelling Electrodes
• Surface
– Non-invasive
– Detect average activity
of superficial muscles
and give more
reproducible results
– Metal (silver/silver
chloride) disk or bar
– May be subject to
cross-talk (EMG
signals from motor
units of other muscles
near by
• Indwelling
– Invasive
– Used to detect EMG
signal from small
muscles and deep
muscles
– Fine hypodermic
needle with insulated
wire conductors
– May be subject to
cross-talk
Preparation of Skin for Surface Electrodes
1. Reduce electrical impedance of skin
•
•
Shave the area
Apply rubbing alcohol or abrasives to remove
dead skin and oils
2. Use electrode gel and pressure, adhesive
tapes and/or elastic bands to affix
electrode to skin
Categories of Electrodes
2. By electrode configuration:
• Monopolar – records difference in voltage
relative to ground
• Bipolar – two contacts to measure electrical
potential, each relative to a common ground,
most common electrode type
• Multipolar
Biphasic Signal
Signal associated with single electrode and
ground
Triphasic Signal
Signal associated with voltage difference when two electrodes are
used at one site
Factors Affecting EMG Signal
• Propagation velocity of wave front (≈ 4m/s)
– Fatigue results in decreased propagation velocity
• Distance between electrodes
• Depth of muscle fibers being recorded
• Electrode surface area
– Larger surface area  longer duration of muap
– surface electrodes record longer muap than
indwelling electrodes (≈ 3-20ms)
• Size of muscle fibers being recorded
– Larger fibers have larger signals
Preferred electrode location is between motor point
(innervation zone) and the tendonous insertion.
Amplitude and frequency
spectrum of EMG
signal affected by
electrode placement
with respect to:
A Myotendonous junction
D
B, C Edge of muscle
B C
Preferred location:
D Midline of belly
between innervation
zone and myotendonous
junction - greatest
amplitude detected
A
Factors to Consider in Recording
EMG Signals
• EMG signal is summation of muap’s
• Goal is to have signals that are undistorted
(linear amplification) and free of noise
(biological – ECG, other muscles; man-made –
power lines, machinery) and artifacts (false
signals from electrodes and cabling – movement
artifacts from touching electrodes or moving
cables)
• Large signals  5-10 mV; small signals  100 V
Factors to Consider in Amplifying
EMG Signals
• Amplifier gain – ratio of output voltage to input
voltage (gain of 1000: 2 mV  2 V)
– Linear amplification over entire band width
– Do not overdrive the amplifier system (large signals
clipped off)
– Full range frequency response for amplifier should be
fast enough to handle highest EMG frequencies
• Amplifier input impedance –resistance
– High so as not to attenuate the EMG signal
*Report magnitudes of voltage as they are sensed at
the electrodes; not amplified signal
Factors to Consider in Amplifying
EMG Signals
• Frequency response
– Amplify without attenuation all frequencies
• Frequency spectrum of EMG signals from 5 to 2000 Hz
• Recommended range for surface electrodes – 10 to 1000 Hz
• Recommended range for indwelling electrodes – 20 to 2000 Hz
– Bandwidth of amplifier difference between upper and
lower cutoff frequencies
– Possible filtering of signals to avoid unwanted noise
Want frequencies of EMG signals to fall
within range where all frequencies are
linearly influenced by gain
5 Hz
2000 Hz
Power density spectrum – mathematical conversion of EMG signals from time to frequency
domain for analysis of the frequency content of the signal
•Higher frequency content of indwelling electrodes because of closer spacing of electrodes
and their closer proximity to active muscle fibers
•Most of EMG signal concentrated in band width between 20 and 200 Hz
•Problem with power lines because frequency is in middle of band width
•Movement artifact (0-10 Hz) can be filtered without adversely affecting desired EMG signal
Factors to Consider in Amplifying
EMG Signals
• Common mode rejection
– Human body good conductor; acts as antenna to
electromagnetic radiation
– Want to eliminate extraneous signals
– Unwanted signals picked up simultaneously at
two locations can be eliminated resulting in
amplification of only difference in voltage
associated with EMG signal
• Desired amplified signal = A[(Vhum + emg1) - (Vhum +
emg2)] = A[emg1 – emg2]
Analog to Digital Conversion and
Sampling an Analog Signal
Analog EMG signal
Digital display of analog
EMG signal sampled at 2 kHz
Sampling a 1 V, 1 Hz sinusoid at 10 Hz
Recreating the sinusoid at 10 Hz
Sampling a 1 V, 1 Hz sinusoid at 2 Hz
Recreating the sinusoid at 2 Hz
Sampling a 1 V, 1 Hz sinusoid at 4/3 Hz
Recreating the sinusoid sampled at 4/3
yields a 1/3 Hz signal. The original 1 Hz
signal is undersampled.
The Nyquist Frequency
Signals should be sampled at no
less than twice the original
frequency.
Fourier
decomposition of
maup
•Original signal in red
•Superimposed signal in
blue is the mathematical
summation of the 10
sinusoids above
•Exact reconstruction
would require an infinite
number of sinusoids, but
10 provides appropriate
accuracy
time
Signal is in time domain because it expresses voltage
as a function of time.
Signal of muap from previous slide is in the frequency
domain because it describes amplitudes of the
frequency contained in it.
Unprocessed EMG Signals
• Useful for determining:
– Onset and turn-off of muscle contraction
– Pattern of contraction of muscles
– Electromechanical delay (EMD)
Why Process EMG Signals?
• Raw signals resemble noise (stochastic)
• Raw signals fluctuate around 0 voltage ( V over
time  0)   V over time for all EMG records
are the same; no differentiation
• Processed signals may be correlated to parameters
of muscle contraction being studied (e.g., force,
fatigue)
Processing EMG Signals in the
Time Domain
• Rectification
– Half wave – eliminate negative values; only positive
signals are used
– Full wave – absolute value of all signals used
• Preferred because no information is eliminated
• Often used in further processing
• Smoothing
– Filtering signal to eliminate selected frequencies
• Low pass filter – allows low frequencies to pass untenanted, but
removes most of the high frequencies
• High pass filter – allows high frequencies to pass untenanted, but
removes most of the low frequencies
• Window or notch filter
Some Common
EMG Processing
Absolute value of
EMG signal
Full wave rectified and
low pass filter
Area under voltage
time curve
Area under voltage
time curve with time
reset 
Area under voltage
time curve with time
reset 
Examples of EMG Signal Processed in the Time Domain
Processing EMG Signals in the
Time Domain
• Integration
– Integration – measures the area under the volt-time
curve
t T
IEMG =
EMG t  dt


t
• Reset at regular intervals of time
• Reset at regular intervals of pre-established area (Vsec)
Processing EMG Signals in the
Time Domain
• Root Mean Square
– Frequently used in studying muscular fatigue
– Calculation
• Sum of squared raw data values of EMG signal
• Determine mean of sum
• Take square root of the mean
 1 t T

2
RMS =   EMG t dt 
T t

1
2
Processing EMG Signals in the
Frequency Domain
• Power density spectra
– Frequency domain important because frequency
content of EMG signal shown to be reduced with
fatigue
– Power density spectra of EMG signal obtained
using Fast Fourier Transformation technique
– Mean and median frequency, bandwidth, and peak
power frequency examples of use of power density
spectra
Example
of EMG
Signal
Processed
in the
Frequency
Domain
Frequency spectrum of EMG signal detected from the tibialis
anterior muscle during a constant force isometric contraction at 50%
voluntary maximum.
Power density spectrum of EMG signal obtained from
Fast Fourier Transformation (FFT)
Mean and Median Frequencies
• Mean frequency – that frequency where the
product of the frequency value and the amplitude
of the spectrum is equal to the average of all such
products throughout the complete spectrum; used
mainly to monitor muscle fatigue
• Median frequency – that frequency that divides
the power density spectrum into two regions
having the same amount of power; preferred for
detecting muscle fatigue
– Less sensitive to signal noise
– Less sensitive to aliasing
– More often more sensitive to biochemical and
physiological factors in muscle during sustained
contractions
Meaning of EMG Signals
•
•
Logical to assume that EMG signals relate
to biomechanical variables (e.g., muscle
contraction force, muscle fatigue)
Quandary: EMG signal is the result of
many physiological, anatomical, and
technical factors
Meaning of EMG Signals
•
5 cardinal questions
1. Is the signal detected and recorded with
maximum fidelity?
2. How should signal be analyzed?
3. Where does the detected signal originate?
(cross talk, electrode placement on muscle)
4. Is signal stationary?
5. Where does the measured force originate?
(influence of synergists and antagonists)
Relationships between EMG Signals
and Biomechanical Variables - Force
• Qualitative relationship not questioned in
scientific literature; quantitative nature
hotly debated
• Quantitative relationship difficult to show
– Difficulties measuring EMG and force of
muscle contraction
– Problem with temporal disassociation of
muscular contraction and EMG signal (EMD)
Relationships between EMG Signals
and Biomechanical Variables – Force
• Isometric contraction
– Can eliminate problems with problems with
measurement of force of contraction and EMG
– Can eliminate temporal dissociation by
sampling in middle of steady state contraction
– Despite ability to eliminate or reduce problems
• Different relations between force and EMG seen
–
–
–
–
Muscle specific relationships with EMG?
Force measured indirectly?
Activity of antagonists or synergists?
Signal processed differently in each study
– Linear and non-linear relationships found
Electromechanical Delay (EMD)
Rat Muscle
Soleus – slow twitch, high aerobic, slow fatiguing
Extensor digitorum longus – fast twitch, high glycolytic, fast
fatiguing
*Note dramatic delay of force time rise
under same stimulation conditions
Relationships between EMG Signals
and Biomechanical Variables – Force
• Dynamic contractions (concentric,
eccentric, isokinetic)
– Few studies with unrestrained movement
– Because of problems, most studies of isokinetic
contraction
• Constant angular velocity  constant velocity of
muscle shortening
• Constant angular velocity  constant velocity of
contractile element shortening
– EMG amplitude associated with negative work
considerably less than positive work
Relationships between EMG Signals
and Biomechanical Variables –Fatigue
• Fatigue – “point” at which force of contraction
can not be maintained
• Problems in measuring fatigue
– Which muscle is fatigued?
– Variable recruitment and utilization of motor units
– Fatigue both psychological and physiological
phenomena
Relationships between EMG Signals
and Biomechanical Variables –Fatigue
• Fatigue is associated with a shift in the frequency
spectrum of the EMG signals to lower
frequencies
– Lower conduction velocities of some or all action
potentials
– Slower motor units remain active while faster motor
units drop out
– Motor units tend to fire more synchronously
•Diagrammatic
explanation of spectral
modification which
occurs in EMG signal
during sustained
contractions
•Muscle fatigue index is
represented by the
median frequency of the
spectrum
Factors
Causative
Extrinsic
•Electrode
Intermediate
•Differential
electrode filter
•Motor point
•Detection volume
•Fiber
orientation
•Tendon
Intrinsic
•Number of active
motor units
•Motor unit firing rate
(synchronization)
•Fiber type Lactic acid
(pH)
•Blood flow
•Signal crosstalk
•Subcutaneous tissue
•Amplitude
(RMS/ARV)
•Number of motor
units detected
•Muscle
activation
(on/off)
•MUAP amplitude
•MUAP duration
•Conduction
velocity
•MUAP shape
•Fiber diameter
•Electrode Fiber
location
•Muscle fiber
(net
force/torque)
•Muscle fiber
interactions
•Motor unit firing
rate
•Superposition
Interpretation
•Number of active
motor units
•Motor unit twitch
force
•Configuration
•Muscle edge
Deterministic
EMG
Signal
•Spatial filtering
•Recruitment
stability
•Spectral
variables
(median/mean
frequency)
•Muscle fatigue
•Muscle
biochemistry
•Other factors
Schematic of factors affecting EMG signal – influences and interactions, C.J. De Luca, 1993