fatigue plot
DESCRIPTION
muscleTRANSCRIPT
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klinini center ljubljanaUniversity Medical Centre Ljubljana
SPS Nevroloka klinikaKO Intitut za klinino nevrofiziologijo
Slovenian-Italian Workshop onQuantitative Needle and
High Resolution Surface EMGUniversity Medical Centre Ljubljana, Division of Neurology
Roberto Merletti, Ph.D. Lab. for Engineering of the Neuromuscular System, Politecnico di Torino, Italy
Basic concepts and applications of multichannel surface EMG
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Prof. Lojze Vodovnik has been one of my many mentors and has strongly influenced my career, my approach to research and my way of thinking about problems.
He has also been a very good friend.I am in debt with him for his teachings.
This lecture is dedicated to his memory.
LISiN, Torino
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1. Surface EMG is not a diagnostic technique and is not intended toreplace needle EMG.
2. Surface EMG is a monitoring technique suitable to study movementand neuromuscular control and to assess muscle changes due toaging, pathology, therapy, training, immobilization, lack of gravity, occupational disorders, etc.
3. Standards are lacking: there have been successful EU efforts toreach consensus and disseminate recommendations (SENIAM, [email protected]), and develop applications (PROCID, [email protected]; NEW, [email protected]; OASIS, [email protected];CYBERMANS, [email protected])
4. There is a need for teaching and training in the medical schools.
WHAT SURFACE EMG IS AND IS NOT
LISiN, Torino
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With respect to the needle technique, the surface technique:
1. Is non invasive, non painful and without risks2. Is global (provides global information)3. Is simple and inexpensive4. Is applicable by non medical personnel5. Can be used over long times during work and sport
activities6. Allows the measurement of quantities not measurable
with needles7. Does not allow the measurement of quantities
measurable with needles8. Is complementary (not a replacement) to the needle
techniqueLISiN, Torino
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At this time (a.d. 2006) the limitations of surface EMG are:
1. Signals are dominated by the contributions of superficial motor units
2. The thickness of skin and subcutaneous fat causesstrong blurring
3. Crosstalk from nearby muscles may be a serious problem
4. Artifacts due to muscle movements (in dynamic contractions) may be very strong
LISiN, Torino
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Main applications of needle EMG
1. Diagnostics based on observations of single (or very few) motor unit action potentials and of their morphology and sound.
2. Fibrillation potentials in denervated fibers
3. Identification of MU territory (macro EMG)
4. All the above can be done or observed in eithersuperficial or deep muscles.
LISiN, Torino
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Main applications of surface EMG1. Biomechanics and movement analysis:
Identification of muscle activation intervals and levels, muscle coordination
2. Muscle fatigue and non invasive fiber typing:Monitoring myoelectric manifestations of muscle fatigue, electrical and mechanical responses of single motor units
3. Muscle physiopathology:Monitoring muscle fiber conduction velocity, motor unit recruitment order
4. Occupational medicine:Monitoring the Cinderellas, postural problems, muscle hyperactivity
5. Rehabilitation, space and sport medicine:Assessment of effectiveness of treatments and training, monitoringmicrogravity related changes and effectiveness of countermeasures
6. Pelvic floor analysis:Detection of sphincter asymmetry, prevention of episiotomy related lesions.
7. Biofeedback:Tension headache, muscle retraining, coordination retraining
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Why EMG processing ?To document differences between individuals and conditions (young-elderly, before-after treatment or training, etc) by reporting EMG descriptors, that is physical variables associated to the EMG signal. To observe central and peripheral phenomena (such as myoelectric manifestations of muscle fatigue, activation patterns, control strategies, etc), to assess effectiveness of treatments.
What descriptors ?2 electrodes: Amplitude (ARV, RMS), frequency (MNF, MDF), amplitude envelope,
activation times during isometric or dynamic contractions.4 electrodes: as above plus conduction velocity (CV), correlation coefficient (CC)
between the signals used for CV estimation.5-16 or more electrodes in a linear array: descriptors of individual motor units
such as location of innervation zone, fiber length, highly accurate CV estimates, firing rate, recruitment pattern, etc.
What conditions ?Isometric conditions: these are special bench-tests to estimate values that are much more difficult to estimate in dynamic conditions (rates of change of descriptors, single Motor Unit features, etc). Dynamic conditions: activation intervals (muscle on-off timing) during movements, envelope detection, etc. These conditions are of greater physiological interest but are affected by artifacts and may not produce reliable results.
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Axon
motoneuron
Schwann cells andRanvier nodes
0
- 70
Action potential(90-100 mVpp)
V m(m
V)
1 ms o 4 mmMuscle fibers
4 m/s = 4 mm/ms 4 m/s = 4 mm/ms
60 m
/s
The Motor Unit (MU)(electrical activity)
Inputs fromother neurons
One muscle: 10-1000 MU One MU: 50-1000 fibers of the same type (I o II)
Space or time
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Subcutaneous tissue
V(x) x
CV
Innervation zone
Muscle-tendon junctions
Skin
Depolarized Zone
- 70 mV
xCV CV
Action potentials travelling towards the tendons
0 mV
Potential distribution on the skin
V(t)
t
-
Subcutaneous tissue
V(x) x
CV
Innervation zone
Tendontermination
Skin
Depolarized zone
- 70 mV
Single differential amplifiers
xCV CV
Monopolar voltages in
space
Propagating single fiber
action potentials
0 mV
+ - + - + - + - + -+ - + - + -Electrode array
V1 V2 V3 V4 V5 V6 V7 V8
X
V1
V2
V5
V4
V3Diff
eren
tial
volta
ges
motoneuron
3 fiber motor unit
Il passaggio delle zone depolarizzate sotto una schiera di elettrodi genera una sequenza di segnali scalati nel tempo di un intervallo pari alla distanza tra punti di prelievo divisa per la velocit di propagazione (3-5 m/s).
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bad
TimeDifferential amplifiers
Array of equally spaced electrodes
bad
bad
good
good
small noisysignals
small noisysignals
small noisysignals
goodsignals
goodsignals
Two electrodes placed symmetrically over the I.Z. give unreliablTwo electrodes placed symmetrically over the I.Z. give unreliable information. e information.
Propagating MUAP
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EMG signals detected with a linear array of 16 electrodes in SD mode. Innervation and termination zones of single MUs are evident.
10 mm
Biceps brachii muscle contracting at 70% MVC
Depolarized zones
50 ms
1 mV
1
15
7
Electrode array
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1 mV
1
15
7
Information may be extracted either from the interferential signal (global level) or from the single MUAP (MU level).
Global analysis and single MU analysis
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Electrode arrays and amplifiers
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Signals from rightand left trapeziusduring typing(project NEW)
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Upper trap. activityduring typingwith forearms
on the desk.
50 ms 0.4 mV 50 ms 0.4 mv
Right Upper Trap
Left upper trap
Upper trap. activityduring typingwith forearms
off the desk.
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16 Electrodes
Pressure sensor
Anal probe
Anal probes(1 array and 3 arrays with16 electrodeseach)
Urethralprobe
Stick-on array forpuborectalis muscle(8 electrodes)
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Anal Probe, MVC, depth 5cm, Electrodes 1,16 dorsal, Example of ventral innervation (under electrode pairs 6-8)
DR
VL
16 1
Probe viewfrom outside
1820 1840 1860 1880 1900 1920 1940 1960
chan
nels
time (ms)
152 V
16
16
1
8
-
0 2000 4000 6000 8000 10000time (ms)
15
8
1
15
8
1
1150 1200 7350 7400
2800 2850 2900 2950 3000 3050 3100 3150 3200
V = ventralL = leftD = dorsalR = right D
LRV
8
15 1 markProbe viewfromoutside100V
S01_02, OD, maleProbe location: near orificeContraction level: MVC
time (ms)
Anal recording, max. voluntary contraction (observe asymmetry)LE
FTR
IGH
TLE
FTR
IGH
T
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a) N = 34
15
13
11
9
7
5
3
1[ch]
10 20 30 40 50 60 70[ms] 0F1TWXA02.SIG
10 20 30 40 50 60 70[ms] 080 80
15
13
11
9
7
5
3
1
[ch]F1TQCA04.SIG
b) N = 40
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200 V
200 V
25 ms25 ms
14 m
m
10 mm
AnalOrifice
1
4
16
12
8
1
4
16
12
8
D1TJPA2.sig 9.6875 - 9.7500 s Max. vol. contraction
D1TWXA2.sig 1.7500 - 1.8125 s Max. vol. contraction
View from outside
depth 4-5 cm1
23
4
5
67
8910
11
12
13
1614
15
D
L R
V
Fig. 1
Ch 1
Ch 2
Ch 3
Ch 4Ch. 11
Ch. 12
Ch. 13
Ch. 14
a) b)
c)d)
4 cm
-
400 V
25 ms
A1
B
A2
C2D1C1 D2
1
4
8
16
12
Anal Orifice
Innervation zone
Terminal zone
D1TISA10.sig6.7500 - 6.8125 s Max vol. contraction
1 23
45
6
891011
12
13
16
1415
D
L R
V
BD
A
C
7
Fig. 3
a b14
mm
10 mm
Depth: 2-3 cm
2 cm
-
AnalOrifice
200 V
25 ms
D
B2B1
A
C
1
4
8
16
12
Innervation zone
Terminal zone
D1TJPA16.sig
2.1250 - 2.1875 s Max vol. contraction
12
345
678910
111213
1614
15D
L RV
B
A
C
D
14 m
m
10 mmFig. 4
depth 2-3 cm
a b
2 cm
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14 m
m
a = 1 cm
Array depth (cm)
AnalOrifice
4-5 0-12-3
1
4
8
16
12
1 23
45
67
891011
1213
16
1415
D
L R
V
(4-5) (2-3) (0-1)
400 V
400 V
400 V
25 msD1TQCA4.sig 0.3125 - 0.3750 s
D1TQCA6.sig1.7500 - 1.8125 s
D1TQCA8.sig 9.1875 - 9.2500 s
aa a aa
Contractionlevel : MVC
Fig. 8
ab c
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14 m
m
10 mmAnal Orifice
Innervation zone
Terminal zone
1 23
45
67
891011
1213
16
1415
D
L R
V
B,DA
C
depth 4-5 cm
Fig. 5
a
400 V
25 ms
AD
C
1
4
8
16
12
B
D1TQCA4.sig 9.3750 - 9.4375 s Max vol. contraction
b
4 cm
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OASIS: possible sphincter damage due to episiotomy
V
Surgical incision
ALow risk
V
AMedium
risk
P V
A
High risk
P
P
InnervationV = vaginal openingP = perineal wallA = anal opening
V
A Very high risk
P
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Myoelectric manifestations of muscle fatigue
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0 100 200 300 4000.0
0.5
1.0
a )
1
23
4
Nor
mal
ized
pow
er
Frequency (Hz)
0 0.25 0.50
-0.1
0.0
0.1 b)
t (s) 0 0.25 0.50
c)Signal b, spectrum n. 4Signal b, spectrum n. 1
t (s)Beginning of the contraction End of the contraction
Spectral evolution of a quasi stationary EMG signal.
Segment bspectrum 1
Segment cspectrum 4
Sustained isometricvoluntary contraction
mV
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EMG power spectrum
The power of the EMG signal is distributed in the frequency range 10-400 Hz
0 100 200 300 400 Hz
Pow
er Harmonics
Power of the harmonics versus their respective frequency.
The spectrum of the EMG signal changes as a function of time during an isometric constant force sustained contraction , because muscle fiber conbduction velocity and motor unit action potential shape change in time. These parameters recover quickly and there change may be small during intermittent contractions.
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0 0.25 0.50
-0.1
0.0
0.1
time (s) 0 0.25 0.50time (s)
mV
Nor
m. p
ower
den
sity
0 100 200 300 400
0.0
0.5
1.0
frequency (Hz)
Power spectral density during a sustained contraction.
Signal at the beginning of an isometric sustained contraction
Signal at the end of an isometric sustained contraction
Myoelectric manifestations of muscle fatigue
During a sustained isometric contraction the surface EMG signal becomes slower, the power spectral density is compressed toward lower frequencies and spectral variables (MNF, MDF) decrease. The decrease of these variables reflects a decrease of muscle fiber conduction velocity and changes of other variables (such as active motor unit pool, degree of synchronization, etc).
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Mean and median spectral Mean and median spectral frequencliesfrequenclies of the of the EMG signal (MNF and MDF)EMG signal (MNF and MDF)
MDF: splits the spectrum into two parts of equal power
MNF: center of gravity line
0 200 400 Hz
(f)dPP(f)df ff00m
=
==02
1f
f
0P(f)dfP(f)dfP(f)df
med
med
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0 100 200 3000
20
40
60
80
100
frequency (Hz)
90s
60s
30s
0s
Centroid lines (Mean frequency)
Contr
actio
n dura
tion
Normalized EMG power spectrum
Mean frequency (MNF) pattern.
Nor
mal
ized
pow
er
One epoch
Example of power spectrum of the EMG of the biceps brachii during a sustained isometric contraction at 60% MVC. The centroid value (MNF) progressively moves towards the lower frequency values demonstrating myoelectric manifestations of muscle fatigue. The rate of change can be taken as an index of fatigue.
Myoelectric manifestations of muscle fatigue
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The Fatigue PlotThe Fatigue Plot
contraction duration
norm
aliz
ed v
alue
s (w
ith re
spec
t to
initi
al v
alue
)
0
100
Root mean square value (RMS)Average rectified value (ARV)
Force or torque
Conduction velocity (CV)Mean spectral frequency (MNF)Median spectral frequency (MDF)
The fatigue plot depicts the time course of some EMG signal variThe fatigue plot depicts the time course of some EMG signal variables ables normalized with respect to their individual initial values. normalized with respect to their individual initial values. It allows comparison of the patterns and rates of change of thesIt allows comparison of the patterns and rates of change of these e variables which reflect muscle properties.variables which reflect muscle properties.
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0 20 40 60 80
40
50
60
70
80
90
100
110
a )+ - 5%
MDF
Torque
70% MVC
IMDF = 78 Hz% o
f ini
tial v
alue
time (s)
0 20 40 60 80 100 120
b )+ - 5%
MDF
Torque
50% MVC
IMDF = 77 Hz
time (s)
Myoelectric and mechanical manifestations of muscle fatigue during voluntary sustained isometric contractions
During strong contractions the pattern of MDF or MNF may beexponential. Initial slope or time constant can be used as indexes of myoelectric manifestations of muscle fatigue. These manifestations begin at the beginning of the contraction and precede and predict mechanical fatigue.
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The Fatigue Plot is the graph of the time course of the EMG variables, normalized with respect to their initial value, during a sustained voluntary or electrically evoked contraction. It describes percent variations of different variables with respect to their initial value. The graphs below show differences observable between two healthy subjects during isometric 70% MVC contractions of the biceps brachii sustained for 30 s.
0 5 10 15 20 25 3040
60
80
100
120
140
160
180
Nor
mal
ized
valu
esw
.r.t.
initi
alva
lues
Nor
mal
ized
valu
esw
.r.t.
initi
alva
lues
Nor
mal
ized
valu
esw
.r.t.
initi
alva
lues
Nor
mal
ized
valu
esw
.r.t.
initi
alva
lues
ARVmean +/-SDCVmean +/-SDMNFmean +/-SD
0 5 10 15 20 25 3080
90
100
110
120
TRQ(70%)MVC +/-SD
0 5 10 15 20 25 3040
60
80
100
120
140
160
180ARVmean +/-SDCVmean +/-SDMNFmean +/-SD
0 5 10 15 20 25 3080
90
100
110
120
Time (sec)
Time (sec)Time (sec)
Time (sec)
TRQ(70%)MVC +/- SD
Subject 1Mean std. dev. of 9 repetitions.Small myoelectric manifestations of muscle fatigue.
Subject 8Mean std. dev. of 9 repetitions.Large myoelectric manifestations of muscle fatigue.
Rainoldi A., Galardi G., Maderna L., Comi G., Lo Conte L., Merletti R., Repeatability of surface EMG variables during voluntary isometric contractions of the biceps brachii, J. Electrom Kinesiol., 9, 105-119, 1999.
The Fatigue Plot during voluntary contractions
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Nor
mal
ized
valu
es
CV
0 5 10 15 20 25 300.4
0.6
0.8
1.0
1.2
1.4
1.6Young subject (60% MVC)
Time (s)
ARV
TRQ
CV
MNF
0 5 10 15 20 25 30
Elderly subject (60% MVC)
Time (s)N
orm
aliz
edva
lues
MNF
TRQ
ARV
0.4
0.6
0.8
1.0
1.2
1.4
1.6
The Fatigue Plot during voluntary contractions
The number of type II (larger) muscle fibers decreases with age. This is reflected by reduced MVC and myoelectric manifestationsof muscle ftigue.
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0 10 20 30-6
-4
-2
0
2
4
6a
Time (ms)
30
1
D10C1
Am
plitu
de (m
V)
0 10 20 30-8
-6
-4
-2
0
2
4
6b
Time (ms)
30
1
D3B1
M-wave changes during electrical stimulation of the tibialis anterior muscle of two individuals for 30 s at 30 pps
Subject a: limited myoelectric manifestations of muscle fatigue
Subject a: marked myoelectric manifestations of muscle fatigue
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0 10 20 30
MDFMNF
CV
RMS
ARV2 t5a3
50
100
150
200
0 10 20 30
CV. MNF. MDF
RMS
ARV
1 t703n1
0 10 20 30
CV
MNF. MDF
RMS
ARV
4 t401n1
Time (s)0 10 20 30
RMS
ARV
MDFMNF
CV
3 t4a3
Time (s)
50
100
150
200
Nor
mal
ized
val
ues
(%)
Nor
mal
ized
val
ues
(%)
Fatigue plots obtained during electrical stimulation of the tibialis anterior of 4 individuals for 30 s at 30 pps
(individual differences are evident)
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Hopf, R.L.Herbort, M. Gnass, H. Gnther, K. Lowitzsch, Fast and slow contraction times associated with fast and slow spike conduction of skeletal muscle fibers in normal subject and in spastic
hemiparesis, Z. Neurol, vol. 206,pp. 193-202,1974.
30 40 50 60 70 803,0
3,5
4,0
4,5
5,0
5,5
r = -0,544p < 0,005y = 5,69 - 0,0296xC
ondu
ctio
n ve
loci
ty (m
/s)
Contraction time (ms)
4.65 m/s
3.47 m/s
Single twitches electrically evoked from the biceps brachii
muscle.
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20 40 60 80 100
4.0
4.2
4.4
4.6
4.8
5.0
5.2
5.4
y = 0.013 x + 3.9r = 0.84 ( p < 0.001 )
Sprinters Distance Runners
Con
duct
ion
velo
city
(m/s
ec)
Relative area of FT fibers (%)
Sadoyama T., T. Masuda, H. Miyata, and S. Katsuta , Fiber conduction velocity and fiber composition in human vastus lateralis, Eur. J. Appl. Physiol. 57, 767-771, 1988.
CVI(x=0) = 3.9 m/sCVII(x=100) = 5.2 m/s
Komi P.V. and Tesch P., EMG frequency spectrum, muscle structure, and fatigue during dynamic contractions in man. Eur J Appl Physiol Occup Physiol, 1979, 42(1):41-50.
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0 5 10 15 200.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
SO = Slow Oxidative fibers (I)FOG = Fast Oxidative Glycolitic fibers (IIa)FG = Fast Glycolytic fibers (IIb)
Fiber Type percentage by area %SO (I) %FOG (IIa) %FG (IIb)
SOL 87.2 4.3 12.8 4.4 0.0 0.0DIA 28.2 2.5 33.9 3.0 38.0 2.3EDL 1.5 0.4 31.9 2.5 66.62.6
Mean st. dev., N = 8 rats
SOL: SoleusDIA : DiaphragmEDL: Ext. digitorum longus
SOL
DIA
EDL
Noe
mal
ized
MD
F
Time (s)
Kupa, S.H. Roy, S.C. Kandarian, C.J. De Luca, Effects of muscle fiber type and size on EMG median frequency and conduction velocity, J Appl Physiol, vol. 79(1), pp.23-32, 1995.
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Hvala Lepa !
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