Myoelectric Leg for Transfemoral Amputee

IJSRD - International Journal for Scientific Research & Development| Vol. 1, Issue 5, 2013 | ISSN (online): 2321-0613
All rights reserved by www.ijsrd.com 1112
Abstract-- This paper will review the works on Surface
Electromyography (SEMG) signal acquisition and
controlling as well as the uses of SEMG signals analysis for
Transfemoral amputee’s people. In the beginning, this paper
will briefly go through the basic theory of myoelectric signal
generation. Next, the signal acquisition & filtering
techniques applied for SEMG signal will be explained. Then
after this EMG signal control or actuate the myoelectric leg
who was suffering from Transfemoral amputee using
microcontroller. This paper gives the better controlling
SEMG signal and also very smooth and easy controlling of
the Prosthetic leg motor using Myoelectric Controller.
Key Words: Myoelectric Controller, Transfemoral Amputee,
Electromyography (SEMG), Knee Angle, Flexion,
Extension.
I. INTRODUCTION
The electric signal produced during muscle activation,
known as the myoelectric signal, is produced from small
electrical currents generated by the exchange of ions across
the muscle membranes and detected with the help of
electrodes. Electromyography is used to evaluate and record
the electrical activity produced by muscles of a human body.
The instrument from which we obtain the EMG signal is
known as electromyograph and the resultant record obtained
is known as electromyogram [1]. The nervous system
always controls the muscle activity (contraction/relaxation).
Hence, the EMG signal is a complicated signal, which is
controlled by the nervous system and is dependent on the
anatomical and physiological properties of muscles. Figure
1 shows the typical EMG signal.
Fig. 1: EMG Signal
II. ORIGIN OF MYOELECTRIC SIGNAL
The nervous system is both the controlling and
communications system of the body. This system consists of
a large number of excitable connected cells called neurons
that communicate with different parts of the body by means
of electrical signals, which are rapid and specific. The
nervous system consists of three main parts: the brain, the
spinal cord and the peripheral nerves. The neurons are the
basic structural unit of the nervous system and vary
considerably in size and shape.
Neurons are highly specialized cells that conduct messages
in the form of nerve impulses from one part of the body to
another. A muscle is composed of bundles of specialized
cells capable of contraction and relaxation. The primary
function of these specialized cells is to generate forces,
movements and the ability to communicate such as speech
or writing or other modes of expression. Muscle tissue has
extensibility and elasticity. It has the ability to receive and
respond to stimuli and can be shortened or contracted.
Muscle tissue has four key functions: producing motion,
moving substance within the body, providing stabilization,
and generating heat.
Three types of muscle tissue can be identified on
the basis of structure, contractile properties, and control
mechanisms: (i) skeletal muscle, (ii) smooth muscle, and
(iii) cardiac muscle. The EMG is applied to the study of
skeletal muscle. The skeletal muscle tissue is attached to the
bone and its contraction is responsible for supporting and
moving the skeleton. The contraction of skeletal muscle is
initiated by impulses in the neurons to the muscle and is
usually under voluntary control. Skeletal muscle fibers are
well-supplied with neurons for its contraction. This
particular type of neuron is called a “motor neuron” and it
approaches close to muscle tissue, but is not actually
connected to it. One motor neuron usually supplies
stimulation to many muscle fibers. Figure 2 shows the motor
unit.
Fig. 2: A motor unit consist of one motor neuron and all
the muscles fibre it stimulates.
The human body as a whole is electrically neutral; it has the
same number of positive and negative charges. But in the
resting state, the nerve cell membrane is polarized due to
differences in the concentrations and ionic composition
across the plasma membrane. A potential difference exists
between the intra-cellular and extracellular fluids of the cell.
Myoelectric Leg for Transfemoral Amputee
Kirtan P. Parekh1
Jignesh B. Vyas2
1,2
Department of Biomedical Engineering
1, 2
Government Engineering College, Gandhinagar, Gujarat, India

(IJSRD/Vol. 1/Issue 5/2013/0019)
In response to a stimulus from the neuron, a muscle fiber
depolarizes as the signal propagates along its surface and the
fiber twitches. This depolarization, accompanied by a
movement of ions, generates an electric field near each
muscle fiber. An EMG signal is the train of Motor Unit
Action Potential (MUAP) showing the muscle response to
neural stimulation. The EMG signal appears random in
nature and is generally modeled as a filtered impulse process
where the MUAP is the filter and the impulse process stands
for the neuron pulses, often modeled as a Poisson process
[2].
III. PROPOSED SYSTEM
Aimed at improving the quality of life for amputees, this
paper is providing the development of EMG sensor for
Transfemoral amputation as well as to make myoelectric
controller which is explain below. Two channels of MES are
collected from the thigh using gelled surface electrodes.
Electrodes are placed equidistant at thigh for knee flexors
and knee extensors.
The two MES channels are fed through
instrumentation amplifier (AD620), with the limited gain.
Outputs of the pre-amplifiers are fed into amplifiers with
limited bandwidth set at 50 Hz to 1 kHz. These filtered
signals are than rectified and these rectified signals send to
the separator comparator for flexion and extension
movement. After these signals are also fed to the
microcontroller which are send to the motor driving circuit
and this motor driving circuit consist of separate relay for
flexion and extension movement and after these relay
signals send to the motor which is attached on prosthetic leg.
Fig. 3: Generalized Block Diagram of Myoelectric
controller
A. Electrode Placement
There are two types of electrodes for obtaining EMG
signals, inserted (invasive) electrodes and surface (non-
invasive) electrodes. The ease of use of surface electrodes
makes their implementation for this project preferable.
Surface electrodes come in many varieties, with most
characterized by the number of contacts. Some different
types of surface electrodes are monopolar, bipolar, tripolar
and multipolar, all of whose geometry is described by their
name. For the purpose of this paper a multichannel bipolar
electrodes are used along with a reference electrode in order
to implement the differential amplifier.
Here to mimic the natural leg movement
myoelectric signals are collected from knee flexor and
extensor since these muscle groups are directly responsible
for the knee movement of interest. Two differential
myoelectric signal channels were recorded using surface
electrodes. One channels were used to record potentials for
flexors and the other one are used to record for extensor.
The desired position for electrodes is on the belly of the
muscle and not on the outer edge of the muscle where other
muscles could interfere with the muscle under examination.
Here, we were taking EMG in four places in patient’s body.
This four muscle names are: Rectus Femoris and vastus
medialis are responsible for the extensor movement while
other two are biceps Femoris (Short head) and are
responsible for Extensor movement.
Fig. 4: Electrode Placement
B. Signal acquisition & filtering Technique
In this section consist of the Instrumentation amplifier,
Bandpass filter, Notch filter, Non-inverting Differential
amplifier and Bridge rectifier. The preferred method of
amplification for this application is differential amplification
using a bipolar electrode and instrumentation amplifier. It is
this methods ability to remove electromagnetic noise that
the body has picked up that make it the most attractive for
this application.
Here the instrumentation amplifier AD620 of
Analog Devices is selected for this design due to its high
CMRR at high gain. The AD620 is a low cost, high
accuracy instrumentation amplifier that requires only one
external resistor to set gains of 1 to 10,000.Here Limited
gain of approximately 25 is designed as we don’t want to
amplify noise with the signal.
After, we are use Bandpass filter reject common-
mode signals using differential amplifiers, a Bandpass filter
are required to increase the signal-to-noise ratio and reject
other physiological signals, such as the electrocardiogram
(ECG) signal and axon action potential (AAP). A filter is a
device designed to attenuate specific ranges of frequencies,
while allowing others to pass, and in so doing limit in
some fashion the frequency spectrum of a signal. The
frequency range(s) which is attenuated is called the Stop
band, and the range which is transmitted is called the Pass
band. The EMG signal falls within the audio frequency
range 10 Hz to 5 KHz. The prominent frequency range
from 40 Hz to 1 kHz has to be isolated to be then
processed. Hence, filters play a vital role in signal
conditioning part of this project.
Notch filter is basically a narrow band reject filter
and is commonly used for the rejection of power line
frequency hum. Here we have used the notch filter with
twin-T network. One T-network is made up of two resistors,
and a capacitor, while the other uses two capacitors and a
registers. Raw EMG signal contains noise and its amplitude
is in microvolt range. At the pre amplifier stage we had set
limited gain as signal contains noise so we need further
amplification of filtered signal. So output of the notch filter
is given to differential amplifier. After we use Bridge
Rectifier all negative signals are converted in to the positive
signal.

C. Myoelectric controller
In order to successfully achieve prosthesis, an effective
control technique is very important in order to drive the
electric motors in the mechanism. With the advent of
modern microcontroller technology, the control options
available today have never been so effective. For
implementing the desired control to the motors, the
amplified EMG signal in analog form has to be converted
into digital format because microcontroller only understand
digital signal (0 and 1). After this, the motors are driven
with the help of a microcontroller through the thresholding
technique. These techniques will be discussed in detail in
this section. In this section, we discuss Comparator,
microcontroller and motor driving circuit.
1) Comparator
Microcontroller only understands the digital signal, so first
we are convert the EMG signal to the digital form. Here, we
should use comparator for converting the ANALOG signal
into the digital format. A comparator compares a signal
voltage applied at the input of an op-amp with a known
reference DC voltage V ref given at the other input. It is an
open-loop operation, i.e., there is no feedback path in the
case of a comparator. Comparators can be classified into
two types, namely non-inverting and inverting. Here,
Inverting comparator is used.
The signal input is given to the inverting input terminal and
the reference voltage is given to the non-inverting input
terminal. When the input voltage is greater than the
reference voltage that time output of the comparator goes
negative Vsat pulse. When input signal is less than
V ref output becomes positive Vsat. Here we set reference
voltage according to our EMG signal amplitude or our
thresholding voltage. Here, we used separate comparator for
flexion and extension and V ref of the comparator are
different.
2) Microcontroller
A Micro-controller is simply a “Computer on a Chip”. A
CMOS-based 8-bit Atmel AT89C51 single-chip serves as
the microcontroller of the system; it accepts the digitized
EMG signals and is programmed to control the Geared DC
motor. The use of micro controller in the proposed design is
to distinguish the different signals results from the different
movements of the limb. We make use of the microcontroller
in our design because of advantages of microcontroller from
our prospective as follow:
1) Programming is Easy and can be used for
multipurpose use. Classification of the signals for different
movement control can be implemented easily and it can also
be used to control the prosthesis via the Geared DC motor.
2) The Product is of a small size so consumes less
space. The prosthetic device used is not only function well
but also cosmetically good and consume less weight with
less space. So this advantage makes the design more
stressful.
3) The system designed with very little effort and is
easy to troubleshoot and maintain.
3) Thresholding and Motor Driving Circuit
The control of prosthesis leg is provided through the
thresholding technique [3]. Once the signal is received from
comparator, taking all necessary considerations as described
before, a suitable threshold is applied to that particular
output of the EMG signal. Before applying the threshold,
output of the EMG signal is to be observed properly. A
threshold value should then set be accordingly. It is
recommended to set the threshold value to a point which is
less than half the output of the EMG signal.
Fig. 5: Hardware of Myoelectric controller
When the output signal of the EMG exceeds this threshold,
the microcontroller should set an output pin to ’1’ and ‘0’
otherwise [3]. E.g. if the maximum value of the output of
the EMG signal is 2.24V then we can set a threshold of
0.90V. This signal is forwarded to a motor relay driver in
order to drive the respective electric motors of a prosthetic
mechanism. The motor driver should be designed or selected
according to our requirements of electric motor. Usually a
motor driver which can drive a 12V motor and handle up to
4A current can adequately meet requirements for a
prosthetic leg.
Here, we use the relay based motor driving circuit
which is easily drive the Geared DC motor on prosthetic leg.
When the flexion signal comes then relay 1 is actuate and
Motor run on clockwise direction and if the extension signal
comes then relay 2 is actuate and motor run on Anti
clockwise direction. Here, we are use Geared DC motor
which has 230 rpm at 12 V supply and its gives 30Kg/cm
torque which easily convenient for the prosthetic leg.
IV. RESULTS AND CONCLUSIONS
A useful way of acquiring EMG signals and motor drive has
been explained in this paper. Modern microelectronics and
controllers have enabled us to develop efficient control of
prosthetic robotic mechanisms.
As an earlier, we discuss the control of a
myoelectric leg. There are two primary motions of the
human knee leg, flexing and extending. For flexion,
electrode should be placed on Flexor biceps Femoris (Short
head) and for extension; the electrode should be placed on
Extensor Rectus Femoris. As both muscles exhibit different
signal patterns, therefore, a multi-channel input scheme
should be employed, so that both signals are gathered
independently. Both signals should be observed carefully
and a suitable threshold should be set after filtering and
amplification. The same procedure is to be followed in order
to develop control of all other movement of leg i.e. by
placing EMG electrodes on specific muscles which control
them, allowing us to classify different motions of the leg [4].
The signal observed from a subject with a moderate built is
shown in Table 1. Table 1 provides the EMG signal

response from each of the subject’s knee joint muscles after
amplification and threshold set for their control [3].
When a human uses a prosthetic, he desires to use his
natural limb movements to control the mechanism. In order
to achieve this, EMG provides the perfect assistance to
allow a subject to make normal movements using a
prosthetic apparatus, hence, efficient controllers and
improved algorithms are essential for enhanced control of
the device. Given the fact that EMG was introduced more
than 30 years ago, the research community has a come a
long way in coming up with innovative techniques,
hardware solutions and advanced procedures to design,
control and utilize these signals to produce resourceful
prosthetic means to tackle disabilities and amputations
effectively.
Sr..
No.
Knee/Leg Muscle Name
Peak
voltage
Readin
g before
contrac
ting (V)
Peak
voltage
Readin
g after
contrac
ting (V)
Thre
shold
Set
(V)
1
Knee
(Flexing)
Biceps
Femoris
(Short head)
0.12 1.82 0.60
2
Knee
(Flexing)
Semimembran
osus
0.20 1.98 0.70
3
Knee
(Extending
)
Rectus
Femoris
0.44 2.12 0.84
4
Knee
(Extending
)
vastus
medialis
0.40 2.62 1.00
Table 1: EMG signals observed and the threshold in terms
of voltage
REFERENCES
[1] Musslih LA.Harba and Goh Eng Chee, “Muscle
Mechanomyographic and Electromyographic Signals
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Propagation Velocity”, Engineering in Medicine and
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of the IEEE, 2002.
[2] M. B. I. Reaz, M. S. Hussain and F. Mohd-Yasin,
“Techniques of EMG signal analysis: detection,
processing, classification and applications’’, biology
proceedings, pp11-35, 2006.
[3] Zahak Jamal, Asim Waris, Shaheryar Nazir, Shahryar
Khan, Javaid Iqbal, Adnan Masood and Umar Shahbaz
“Motor Drive using Electromyography for Flexion and
Extension of Finger and Hand Muscles” 4th
International Conference on Biomedical Engineering
and Informatics, Vol. 3 pp. 1287-1291,2011.
[4] Finger independently” Proceedings of MOVIC, 9th
International Conference on Motion and Vibration
Control, 2008.
[5] Dr. Scott Day, ‘’Important Factors in surface EMG
measurement’’,2002http://www.andrewsterian.com//21
4/EMG_measurement_and_recording.pdf
[6] Measurement of human leg joint angle through motion
based on electromyography (EMG) signal Dr. Yousif I.
Al-Mashhadany2, IJCCCE, and VOL.11. NO.2, 2011.
[7] O. Bida, “Influence of Electromyogram (EMG)
Amplitude Processing in EMG Torque Estimation”,
M.Sc Thesis, WORCESTER POLYTECHNIC
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[8] Books: Op-amps and linear integrated circuits,
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Myoelectric Leg for Transfemoral Amputee

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Myoelectric Leg for Transfemoral Amputee