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ELECTROMYOGRAM
Amit Sethi
Pre-doc Rehab Sciences,
MS OTR/L
INTRODUCTION
• Electromyogram (EMG) is a technique for
evaluating and recording the activation signal of
muscles.
• EMG is performed by an electromyograph,
which records an electromyogram.
• Electromyograph detects the electrical potential
generated by muscle cells when these cells
contract and relax.
INTRODUCTION Contd.
EMG Apparatus
Muscle Structure/EMG
ELECTRICAL
CHARACTERITICS
• The electrical source is the muscle membrane
potential of about -70mV.
• Measured EMG potentials range between
< 50 μV up to 20 to 30 mV, depending on the
muscle under observation.
• Typical repetition rate of muscle unit firing is
about 7-20 Hz.
• Damage to motor units can be expected at
ranges between 450 and 780 mV
ELECTRODE TYPES
Intramuscular Needle Electrodes
Extramuscular - Surface
Electrodes
EMG PROCEDURE
• Clean the site of
application of electrode;
• Insert needle/place surface
electrodes at muscle belly;
• Record muscle activity at
rest;
• Record muscle activity
upon voluntary contraction
of the muscle.
EMG Contd.
• Muscle Signals are
Analog in nature.
• EMG signals are
also collected over
a specific period of
time.
Analog Signal
EMG Contd.
EMG processing:
Signal pick up
Computer
Amplification
& Filtering
Conversion of Analog
signals to Digital signals
APPLICATION OF EMG
• EMG can be used for diagnosis of
Neurogenic or Myogenic Diseases.
• You tube link of EMG
SAMPLE EMG DATA
BIOMECHANICS
• Biomechanics is the research and analysis of the
mechanics of living organisms.
• KINEMATICS – The branch of Biomechanics
concerned with describing the motion of bodies.
• KINETICS- The branch of biomechanics concerned
with explaining the causes of body motions.
KINEMATICS Contd.
Data is usually collected
with Motion Capture
Devices over a specific
time period.
 VICON
 Motion Analysis
Corporation
 Qualysis
Typical Set up of Motion Analysis Lab
SAMPLE KINEMATIC DATA
SAMPLE KINEMATIC DATA
SAMPLE KINEMATIC DATA
KINEMATICS DATA ANALYSIS
• Aim: to identify the variability in reaching movement in
normal and stroke individuals.
• Outcome Variable: Elbow Joint Angle.
• Magnitude of variability was analyzed with Std.
Deviation.
• Structure of variability in elbow angles was computed
via IE using MATLAB.
H = Log2 (1/Pi)
Pi = probability that a given event will occur. Pi α1/H.
• Higher values of IE suggest - more uncertainty.
• Lower values of IE suggest- less uncertainty
(increased stability). of
RESULTS
Subject SD Pre
1
4.54
2
3.69
Control
SD Post IE Pre
IE Post
1.80
0.58
0.80
2.67
0.79
0.50
SD = 2.68
IE = 2.33
CONCLUSION
• Variability/Uncertainity in movement is higher in
normals as compared to individuals with Stroke.
• This variability could be correlated with
adaptability in movement which is decreased
upon nervous system damage in Stroke.
• Large data is required to generalize these
results.