The Rectus Femoris Muscle Fatigue through Mechanomyographic

Time-Frequency Response in Paraplegic Subject

Preliminary Results

Eddy Krueger

, Eduardo M. Scheeren

, Guilherme N. Nogueira-Neto

Agnelo Denis Vieira

and Percy Nohama

CPGEI, Universidade Tecnológica Federal do Paraná, Sete de Setembro Ave 3165, Curitiba, PR, Brazil

PPGTS, Pontifícia Universidade Católica do Paraná, Imaculada Conceição St 1155, Curitiba, PR, Brazil

Keywords: Mechanomyography, Fatigue, Functional Electrical Stimulation, Spinal Cord Injury, Cauchy Wavelet.

Abstract: The purpose of this study is the evaluation of mechanomyographic (MMG) time-frequency response of

rectus femoris muscle of a paraplegic subject during an isometric electrically-elapsed fatigue protocol. An

accelerometer sensor was used to measure the vibration of muscle during voltage-controlled functional

electrical stimulation application at 1 kHz pulse frequency (20% duty cycle) 70 Hz modulated frequency

(20% duty cycle). A load cell (50 kgf) measured the force signal with the participant seated on a bench with

the hip and knee angle set to 90º. During the protocol the electrical output voltage was adjusted to keep the

force at 30% of maximal stimulated contraction (MSC). When the electrical stimulation was unable to keep

the force above approximately 10% of MSC the protocol was ceased. Ten seconds with unfatigued (initial

period) and fatigued (final period) muscle, MMG signal was processed with Cauchy wavelet transformation

(bandpass 5-100 Hz). For fatigue conditions of paraplegic subject, MMG signal presents concentration

energy to lower frequencies mainly to 11.31 Hz band frequency.

1 INTRODUCTION

Muscular fatigue produces electromechanical

modifications on neuromuscular tissue as the

incapacity to generate force required in contraction

(Cè et al., 2013). Muscular fatigue of people with

complete spinal cord injury (SCI) can be detected by

using force information (Gerrits et al., 1999);

however, to elicit the muscular contraction the main

way is applying the functional electrical stimulation

(FES).

Unfortunately, the stimulating electrical current

produces interference on the acquisition of feedback

signals such as electromyography (Faller et al.,

2009) that registers the bioelectrical signal of

neuromuscular tissue. Alternative way to acquire the

muscular response of paraplegics with complete

lesion is by means of mechanomyography (MMG)

(Nogueira-Neto et al., 2013), which is a technique

based on mechanical oscillations of muscles during

contraction. So, it is immune to electrical

interference yielded during FES application (Seki et

al., 2003).

The goal of the research discussed in this paper is to

verify if there is any frequency band of time-

frequency response that has higher energy in rectus

femoris muscle of a paraplegic subject during an

isometric electrically-elapsed fatigue protocol to

improve the knowledge of muscle physiology.

2 METHODS

2.1 Volunteer

This study was approved by Human Research Ethics

Committee of Pontifícia Universidade Católica do

Paraná (PUCPR) under register 2416/08. The

participant involved in the research was 38 years

old, weight: 88 kg, height: 179 cm and diagnosed

with incomplete spinal cord injury at T3-T4

radicular level acquired twenty years earlier by

gunshot. The left lower limb of the volunteer

underwent a physical evaluation classifying it as

level B (without voluntary contraction) in

accordance with the American Spinal Injury

239

Krueger E., M. Scheeren E., N. Nogueira-Neto G., Denis Vieira A. and Nohama P..

The Rectus Femoris Muscle Fatigue through Mechanomyographic Time-Frequency Response in Paraplegic Subject - Preliminary Results.

DOI: 10.5220/0004804102390243

In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS-2014), pages 239-243

ISBN: 978-989-758-011-6

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

Association (AIS) impairment scale (from A to E).

In the day of test, the volunteer did not use any drug

that could change his motor condition.

2.2 Electrical Stimulation

The custom electrical stimulator produced

monophasic rectangular wave with amplitude

controlled stimulation pulses. The parameters

configured were pulse frequency: 1 kHz (20% duty

cycle); burst (modulating) frequency: 70 Hz (20%

duty cycle).

2.3 Instrumentation

The MMG system used had a triaxial accelerometer

sensor (Freescale

MMA7260Q MEMS with 800

mV/G sensitivity at 1.5 gravitational acceleration -

13x18mm, 0.94 g) and the Z-axis (transverse to the

muscle belly displacement) was used as the signal

process. The electronic circuits allowed 2.2x

amplification. A load cell (50 kgf ≈ 500 N), of S

shape aluminium body, with four strain gages in full

Wheatstone bridge, was used to measure force. After

the skin preparation (trichotomy and cleaning),

MMG sensor was positioned over the belly of rectus

femoris (RF) muscle using double-sided adhesive

tape. The placement was equidistant between the

anterosuperior iliac spine and the top of the patella.

The self-adhesive electrodes with different sizes

were positioned on the thigh over the knee region

(anode with 5 x 9 cm) and over the femoral triangle

(cathode with 5 x 5 cm) to stimulate the quadriceps

muscle via femoral nerve.

2.4 Experimental Protocol

The volunteer was positioned seated on a bench with

the hip and knee angle set to 90º. After the

placement of the FES electrodes on the left limb a

minimum of 10 min rest was respected to skin-

electrode impedance balance (Reilly, 1992). The

MMG sensor was positioned over the rectus femoris

muscle belly. The load cell was attached on the leg

through band strips and a Velcro strap belt was

positioned in trunk for volunteer stabilization. The

instrumentation layout is illustrated in Figure 1.

Firstly, the maximal stimulated contraction

(MSC) force was performed by increasing the

electrical stimulating magnitude (approximately 3

V/s to avoid motoneuron adaptation/habituation)

until the force started to level off. Twenty-minutes

rest interval was respected to avoid interference on

fatigue protocol. The protocol was initiated with 0V

of electrical stimulating, them it was controlled to

keep the force in 30% of MSC (30MSC). When the

electrical stimulating was unable to keep the force

over 30% of 30 MSC (approximately 10% of MSC)

the protocol was ceased (Gerrits et al., 1999).

Figure 1: Experimental set up and instrumentation layout.

2.5 Data Processing and Analysis

The signal process was realized by custom-written

MatLab

software version R2008a. Ten seconds

window was chosen at initial instant when the

30MSV was reached (unfatigued muscle). Ten

seconds window was chosen at final instant before

30% of 30MSV force (fatigued muscle). The MMG

signal was processed with a third-order Butterworth

filter with bandpass of 5-100 Hz (spectral range of

muscular vibration). The signal was processed in

eleven bands of Cauchy wavelet (CaW) transform

(von Tscharner, 2000) (2.07, 5.79, 11.31, 18.63,

27.71, 38.54, 51.12, 65.42, 81.45, 99.19 and 118.63

Hz) and the root mean square (analysis window

length: 1s) was computed for each CaW band. Data

were normalized by the first second at the initial

moment to each frequency band in order to show

signal variations.

3 RESULTS

The volunteer did not show any spastic event during

the protocol application. In order to reach the MSC

force (31.5 kgf), the output stimulator voltage was

set to 190 V. The green line in Figure 2 shows the

target force (30% MSC), the blue line indicates the

threshold of 10% MSC and the red line indicates the

BIOSIGNALS2014-InternationalConferenceonBio-inspiredSystemsandSignalProcessing

240

response of the force obtained during the protocol.

After 50 s of applying the electrical stimuli, one may

observe the inability of the muscle to sustain its

strength in the target area even with the increase of

the electrical stimulation.

Figure 3 shows the MMG time-frequency

response: at first stage (first 10 s – A and B) two

frequency bands are prominent, at 11.31 Hz and at

65.42 Hz; the latter one is probably due to myofibers

oscillation in accordance with burst frequency (70

Hz – tetanic frequency). At last stage (last 10 s – C

and D) under fatigue conditions, the frequency band

around 11.31 Hz shows an enhancement in energy

concentration (seen as higher intensity value) near

the final setpoint protocol.

Figure 4 illustrates normalized data. At first stage

(A and B), the lower frequency components show

greater energy content (from 5.79 to 11.31 Hz); at

final stage (C and D), under fatigue conditions, the

same components (from 5.79 to 11.31 Hz) also show

greater energy concentration near the final set point

protocol. The frequency components around 65.42

Hz in normalized data do not show variation along

the protocol, possibly because few myofibers

achieve oscillation in this vibration frequency.

4 DISCUSSION

At initial stage (unfatigued), the frequency

components around 65.42 Hz show content

concentration, as well as the band at 11.31 Hz,

probably due to myofibers oscillation in accordance

Figure 2: Force (red line) during the protocol. Force goal control (green line), inferior force threshold (blue line).

Figure 3: 3D (A and C) and 2D (B and D) MMG time-frequency responses of rectus femoris muscle. A and B: ten initial

seconds of FES-force-controlled application (unfatigued muscle). C and D: ten final seconds of FES-force-controlled

application (fatigued muscle). The color bar shows the maximum value (21 mVrms) in dark red color and the values below

10% of maximum (0.21 mVrms) are in white color. Force: red line in 2D image.

(A)

(B)

(C)

(D)

TheRectusFemorisMuscleFatiguethroughMechanomyographicTime-FrequencyResponseinParaplegicSubject-

PreliminaryResults

241

Figure 4: Normalized 3D (A and C) and 2D (B and D) MMG time-frequency responses of rectus femoris muscle. Data

normalized by the first second. A and B: ten initial seconds of FES-force-controlled application (unfatigued muscle). C and

D: ten final seconds of FES-force-controlled application (fatigued muscle). The color bar shows the maximum value (3.2

normalized data) in dark red color and the values below 10% of maximum (0.32 normalized data) are in white color. Force:

red line in 2D image.

with modulated frequency (70 Hz tetanic frequency).

The same event occurs when modulated frequency is

set to 50 Hz. At this situation the signal shows a

peak energy at the range of 51.12 Hz and other peak

at 11.31 Hz (Krueger et al., 2013b) as in our

previous study. These events on signal are not due to

FES interference, because the electrical stimulator

intensity is increased along the protocol application

and the energy variation around 65.42 Hz keeps

practically the same content (normalized data in

Figure 4).

At final stage (fatigued), both Figures 3 and 4

indicate the increase of energy at lower frequencies

(mainly 11.31 Hz) when the muscular fatigue occurs

(Tarata, 2003; Gandevia et al., 1995). Using the

FES-control based on knee joint angle rather than on

force the result is the same (Krueger et al., 2013a).

This lower frequency energy concentration may be

due to motor units coherence (Yao et al., 2000)

when myofibers vibrate in phase during contraction

in fatigue state. Moreover, the increased energy for

low frequency bands in the last seconds of protocol

may be associated with a decrease in muscle fibre

conduction velocity, that is a peripheral factor,

related to the occurrence of muscle fatigue as occurs

with able-bodied subjects (Schillings et al., 2003).

5 CONCLUSIONS

During fatigue conditions the mechanomyographic

signal of rectus femoris muscle from a paraplegic

subject presents a greater energy concentration at

lower frequencies (mainly 11.31 Hz band

frequency). This fatigue information in paraplegic

subject (without voluntary contraction) is helpful to

knowledge's improvement regarding muscular

physiology after spinal cord injury.

ACKNOWLEDGEMENTS

We would like to thank CNPq and SETI-PR for

important funding and financial support.

REFERENCES

Cè, E., Rampichini, S., Agnello, L., Limonta, E.,

Veicsteinas, A. & Esposito, F. 2013. Effects of

temperature and fatigue on the electromechanical

delay components. Muscle & Nerve, 47, 566-576.

Faller, L., Nogueira-Neto, G. N., Button, V. L. D. S. N. &

Nohama, P. 2009. Muscle fatigue assessment by

mechanomyography during application of NMES

protocol. Revista brasileira de Fisioterapia, 13, 422-

429.

(A)

(B)

BIOSIGNALS2014-InternationalConferenceonBio-inspiredSystemsandSignalProcessing

242

Gandevia, S. C., Enoka, R. M., Mccomas, A. J., Stuart, D.

G. & Thomas, C. K. 1995. Fatigue: Neural and

Muscular Mechanisms, New York, Springer Us.

Gerrits, H., De Haan, A., Hopman, M., Van Der Woude,

L., Jones, D. & Sargeant, A. 1999. Contractile

properties of the quadriceps muscle in individuals with

spinal cord injury. Muscle & Nerve, 22, 1249-1256.

Krueger, E., Scheeren, E., Lazzaretti, A. E., Nogueira-

Neto, G. N., Button, V. L. S. N. & Nohama, P. Year.

Cauchy wavelet-based mechanomyographic analysis

for muscle contraction evoked by fes in a spinal cord

injured person. In: IASTED, ed. 10th IASTED

International Conference on Biomedical Engineering,,

February 13 - 15, 2013a Innsbruck, Austria. 237-42.

Krueger, E., Scheeren, E., Nogueira-Neto, G. N. &

Nohama, P. Year. Time-Frequency Muscle Responses

Elicited by Different FES Modulating Frequencies in

Paraplegics. In: 18th IFESS Annual Conference,

2013b Donostia-San Sebastian, Spain. Serbia:

Academic Mind, 249-252.

Nogueira-Neto, G., Scheeren, E., Krueger, E., Nohama, P.

& Button, V. L. 2013. The Influence of Window

Length Analysis on the Time and Frequency Domain

of Mechanomyographic and Electromyographic

Signals of Submaximal Fatiguing Contractions. Open

Journal of Biophysics, 3, 178-190.

Reilly, J. P. 1992. Electrical stimulation and

electropathology, Cambridge, USA, Cambridge

University Press.

Schillings, M. L., Hoefsloot, W., Stegeman, D. F. &

Zwarts, M. J. 2003. Relative contributions of central

and peripheral factors to fatigue during a maximal

sustained effort. European Journal of Applied

Physiology, 90, 562-568.

Seki, K., Ogura, T., Sato, M. & Ichie, M. Year. Changes

of the evoked mechanomyogram during electrical

stimulation. In: Annual Conference of the

International Functional Electrical Stimulation

Society, 2003 Brisbane.

Tarata, M. T. 2003. Mechanomyography versus

electromyography, in monitoring the muscular fatigue.

Biomedical Engineering Online, 2, 3.

Von Tscharner, V. 2000. Intensity analysis in time-

frequency space of surface myoelectric signals by

wavelets of specified resolution. Journal of

Electromyography and Kinesiology, 10, 433-445.

Yao, W., Fuglevand, R. J. & Enoka, R. M. 2000. Motor-

unit synchronization increases EMG amplitude and

decreases force steadiness of simulated contractions.

Journal of Neurophysiology, 83, 441-452.

TheRectusFemorisMuscleFatiguethroughMechanomyographicTime-FrequencyResponseinParaplegicSubject-

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