Synchronization of EMG and GRF Measurement System Using LabVIEW and Matlab Tools

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Nov 30, 2013 (3 years and 11 months ago)

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Synchronization
of
EMG
and
GRF M
easurement
System
Using

LabVIEW

and
Matlab

Tools


Moulali P
ulimaddi
1, 2
,
Gautam

Sharma
1
,
Neelesh

Kumar
1
,

Amod

Kumar
1
,

A.R.C
. Reddy
2

1
Central Scientific Instruments Organisation, (CSIR) Chandigarh

2
NIT
-
Warangal, Andhra Pradesh

moulali.nitw@gmail.com



Abstract
:


Synchronized

tools [electromyography (EM
G), force plate
and video data
] can produce accurate results fo
r biomechanical
analyses which basically influence the laborat
ory environment.

We
developed

a
system for
acquisition of

synchroniz
ed

EMG and ground
reaction

(force)

da
ta. The purpose of this study i
s to compare

ground
reaction force

(
GRF) and EMG activity (EMG) from gastrocnemius
lateralis (GL), tibialis anterior (TA), biceps femoris
(BF) and vastus
lateralis (VL)
with active surface electrodes attached to right leg

of a
normal subject

walking on
the

Kistler force plate. Dynamic
integ
ration of EMG and force plate can produce multimedia
presentations of human movement that facilitate effective qualitative
and qu
antitative biomechanical analysi
s.

By sy
nchronizing both
EMG and
GRF
,

one

can reduce time errors
which facilitated
acquisition
of both
data

at
the
same interval of time.

S
ynchronization usi
n
g

IR, LEDs and

FSR with different hardware
may

not give proper results
.

B
y this method

some time delay may be
in
corporated in the synchronised
data.

But acquisition of both EMG
and GRF data
through the same NI hardware remove
s

such type of

time

delay.


Through control unit eight channels
of piezoelectric
force plate were

connecte
d to NI data acquisition (NI
-
DAQ
) system
and four active surface electrodes were connected through subject
uni
t

to
the same DAQ
.

The DAQ is connected in digital triggering
mode through an
external

switch arrangement so that
the DAQ can
be triggered to
acquire

data from both the
system at

the same instant
of time.

The a
cquired LabVIEW

data
was analysed

using Matlab tool

for off
-
line analysis
.
Root M
ean
S
quare (RMS), Mean, M
edian
frequencies and

extremum points of vertical component of
GRF

(i.e.
Fz1, Fz2, Fz3)

were evaluated using
self developed software tool on
Matlab
. These parameters were
displayed

using Graphical

user

interface (GUI).


Keywords: Synchronization, EMG,
GRF
.


I. INTRODUCTION


Electromyography (EMG) and force plate data are the most
commonly used for the assessment of skele
tal muscles
activities and

finding kinetic
parameters in medical as well
as

research areas.

[
1
]

EMG is

playing an important role in
analysing muscle physiological behaviour and for
ce plate data
for

evaluating
gr
ound reaction forces.

Technological
developments in software and hardware currently facilitate
the

integration of EMG, f
orce platform

and
motion
capture
. This
dynamic integration provides powerful t
ool for synchronized
analysis in

clinical, sport, and
ergonomics
.

[
2
]

The

synchronization provides comparison of different data side by
side and gives accurate results. The
purpose of this study

is to


synchronize force plate and EMG data from the selected four



muscles.
The prominent component of GRF (i.e. VGRF) and

selected m
uscles

from the lower limb which show

maximum

activity during a gait cycle is

considered in this
study

for
analysis purpose
.

Literature revels that

the synchronization

is
achieved with two different system

using FSR. But in
this
research

work

synchronization

is achieved for two different
systems

(i.e. force and
EMG)

through the
same
NI

hardware
there

by acquiring both the data at the same instant of
time.


Real time data acquisition is done with LabVIEW as the
software platform. The acquired LabVIEW data is th
en
imported to Matlab

for further analysis of different
parameters.
Graphical User Interface (
GUI) is developed to
make

the task user friendly.
It

gives good result

compare with
previous work

and data can be displayed in the same window.
By d
isplaying both the data in the same window help
s

in
analysing the effect of
GRF

in tuning the muscle
activity.
A
s
ubject with

active surface electrodes
attached
to

GL, TA, BF
and

VL

muscle
s

walking

over

the
Kistler
force plate

is shown

in Fig 1
.




Fig 1: Subject with EMG electrodes walking over the
Kistler
force plate


II. METHODS AND MATERIALS


The

synchronization

work consists

of both Hardware as well
as
Software

part
.

A.

Hardware Setup Design


The hardware part consists of

Kistler force plate (Kistler
Instrument
e AG, type 9286BA, Switzerland) and

control unit
(Kistler Instrumente
AG, type
5233A2
)
for

force data

acquisition
.
For the

acquisition

of EMG data

Biometrics base
unit

(
Data Link DLK900,

UK
)
, subject

unit

(
Data Link
DLK900
)

and

EMG active surface electrodes (SX 230
W
)

were used.
Eight
analog
channels from the

control unit of
Kistler

Force
plate

were connected to the
NI
-
DAQ.

Out of the
eight channels
,

four channel
s

are
for

Z
-
component, two for Y
-
component and
last
two for X
-
component.

Similarly four
analog
outputs

from the base unit of Biometrics EMG
acquisition system were connected to the resp
ective connector
location of the same NI
-
DAQ.

All the data acquisition unit
are externally power supplied through their respective adaptor.
In order to acquire the data simultaneously from both the
devices, the
NI
-
DAQ is configured in

digital triggering
mode
.


The NI
-
DAQ is connected to

computer throu
gh the external

USB

cable. Data

is

then
acquired to a

computer through the
developed VI

in
LabVIEW.

The

experimental

hardware
setup
for synchronization of EMG and force pl
ate data is shown in
the Fig 2.




F
ig
2
.

Experimental setup
for sync
hronization
of both EMG

and force
plate
data.



B.

Software Analysis


The LabVIEW VI for synchronization

of EMG and Force
plate data is shown in Fig3.
The

components of GRF
we
re
passed throug
h
the corresponding low pass filter
before being
saved
.

As EMG channel data were devoid of any noise
,

filtering was not performed
and direct acquisition was done
.
All

the data were then complied and stored in text file. The
text file thus obtained is imported to Matlab (version: Matlab
R2008b) for further processing and evaluating different gait
parameters.
When imported in M
atlab

it was seen that there

was a DC offset for the EMG signal but no such effect was

observed for fo
rce signal.

So,
proper

program

code

was
developed
for

removing such DC offset error from the EMG



Fig
3
.
Block diagram of VI
for synchronization of both EMG and force plate
data.


signal.

The application of this code completely removes the
DC offset error. T
his signal

is

then
rectified to
obtain absolute

value

of the signal
. After
that the

rectified signal
is passed
through fourth order Butterworth

low

pass filter to remove
high

frequency

signals.

Low passed filter output is then fed to
a
notch

filter
to

remove

interference due to power supply.
All
the above steps are applied

for pre
-

processing of the EMG
signal.
After the pre

processing
,

two type of analysis

i.e. time
domain and frequency domain analysis were performed for
gait parameter evaluation. From
the
time domain analysis
RMS value of the signal is evaluated whereas
Mean and
Median frequency were calculated

from

frequency domain
analysis.

The flowchart
showing the different steps involved
in EMG data analysis is shown in Fig
4.




Fig 4: Flowchart showing the steps
involved in EMG data analysis



Similarly we are interested

in evaluating the extremum values

of the VGRF
, as

these values are evaluated in a
number
of

kinetic
analyses

for normal gait

estimation
.

S
o

proper
algorithm was developed to estimate the extremun values

(
i.e.
Fz1, Fz2, and Fz3)
,

without

any manual labour.

After
evaluating all the parameters
,

GUI was deve
loped
to display
all of them through the same window, which makes the task
user friendly
.


III. RESULTS


The data integration of both force plate and EMG is extremely

u
seful

when perf
orming clinical gait assessment
,
sports
biomechanical analysis

etc, as

it helps in evaluation of both
the kinetic and EMG parameter simultaneously.
I
n other
words
the effect of GRF on muscle activity is obtained.

The
developed GUI that
helps

in evaluating different
gait
parameter synchronously is shown in Fig 5.

It contain
s

the





Fig

5
.
D
evelope
d GUI for analysi
s of synchronize
d

EMG and force plate data.


load option for importing
a file

one can evaluate force
parameter just by pressing the button “VGRF”.

Similarly the
parameter related to each muscle

(i.e. GA,

TA,

BF,

VL
) can

be evaluated just by selecting the muscle type from the
popup

menu and pressing the required parameters’ button.



IV CONCLUSION



The
developed tool for synchronization of EMG and force
plate data

and their subsequent analysis module will be
helpful for analysing a number of gait parameter
simultaneously.

It also helps us to understand how GRF have
stimulated the muscle activity.

The result obtain from
analysing module are do not exactly match to
those obtained
from the software that are provided along with those system.
It is because the techniques
use for analysis is

not alike

but
effort is

made to utilize same technique so that cross
verification may be done and
the
same result may be
obtained
.

The analysis module is in its developing stage, so we are
trying to incorporate a
number

of
other parameters, which
will
enhance its
performance.



V. REFERENCES


[1].
Q.H Huang, Y.P Zheng, X.Chena, J.F He and J Shi (2007).
A system
for the synchronized recording of sonomyography, electromyography and
joint angle. Open Biomed Eng J.2007; 1: (77
-
84).

[2].
Finch.A.E,

Ariel G.A, and Penny A.M
, Biomechanical integration of
essential human movement paramet
ers
.

[3
].
Levin.O,
Mizrahil.J, Adam.D, Verbitsky.O and Isakov.E.(). On the
correlation between force plate data and EMG in various standing conditions.

[4
].
Sousa.F,
Conceiltao.F, Gonltalyes.P, Carvalho.J.M, Soares.DScarrone.F,
Loss.J, Vilas
-
Boas.J.P(2002). Biomechanical ana
lysis of elementary ballet
jumps; Integration of force plate data and EMG records. ISBS 2002, Caceres
-
Extremadura
-
Spain(175
-
178).