Fatigue Plot

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

[email protected]

Basic concepts and applications of multichannel surface EMG

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

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

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

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

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

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

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.

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

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).

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

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

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

Electrode arrays and amplifiers

Signals from rightand left trapeziusduring typing(project NEW)

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.

16 Electrodes

Pressure sensor

Anal probe

Anal probes(1 array and 3 arrays with16 electrodeseach)

Urethralprobe

Stick-on array forpuborectalis muscle(8 electrodes)

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

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

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

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

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

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

Myoelectric manifestations of muscle fatigue

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

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.

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


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).

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

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.


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.

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.

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

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.

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

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)

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.

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.

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.

Hvala Lepa !

[email protected]

www.lisin.polito.it

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Fatigue Plot