Bio-Mimetic Behaviour of IPMC Artificial EMG Signal

8/13/2019 Bio-Mimetic Behaviour of IPMC Artificial EMG Signal

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Bio-mimetic Behaviour of IPMC Artificial

Muscle Using EMG Signal

R.K. Jain*, S. Datta*, S. Majumder*, S. Mukherjee**, D. Sadhu**, S. Samanta** and K. Banerjee***Scientists, **Students

DMS/Micro Robotics Laboratory

Central Mechanical Engineering Research Institute, Durgapur-713209, (CSIR), West Bengal, India.Corresponding author e-mail: [email protected]

AbstractAssistive devices such as prosthetic and

orthotic devices as well as micro robotic arm can perform

similar operation of a human arm when these are actuated

by muscle power. The generated force is transferred

through an electro-mechanical system. Most of electro

mechanical devices are heavy and are not compatible with

muscular system. However, an ionic polymer metalcomposite (IPMC) has tremendous potential as an

artificial muscle and is driven by a low voltage range

between -3 to +3 V. In this paper, bio-mimetic actuation of

IPMC is studied. The electric voltage is detected by

electromyographic (EMG) signal through human muscle

and is transferred to IPMC. It is observed that an IPMC

shows similar behaviour and controls of a human fore

arm.

Keywordsbio-mimetic, artificial muscle, IPMC,

actuator and EMG.

I. INTRODUCTIONThe assistive devices such as prosthetic and orthoticdevices need soft actuating systems which arecontrolled through human muscle power. The

emergence of effective electroactive polymer (EAP),also known as artificial muscles can potentially address

this need [1,2]. EAP responds to an electricalstimulation with a significant change of shape or size

and this characteristic behavior can be implemented fordesigning actuation-driving mechanism and improvethe quality of life. Especially, ionic polymer metal

composite can be widely applied to the artificial muscle

This work is supported in part by the Council of Scientific andIndustrial Research (CSIR), New Delhi, India (Grant No. NWP-30,2007-2012) under eleventh five year plan on Modular Re-

configurable Micro Manufacturing Systems (MRMMS) for MultiMaterial Desktop Manufacturing Capabilities.

S. Mukherjee, D. Sadhu, S. Samanta and K. Banerjee are students ofAsansol Engineering College, Asansol, India who are carrying out thefinal year B. Tech Project at CMERI, Durgapur, India. Rests of theauthors are with the Design of Mechanical System Group and MicroRobotics Laboratory, Central Mechanical Engineering Research

Institute (CMERI), Durgapur-713209, West Bengal, India.(Corresponding author email: [email protected]; Tel No +91-343-6452137)

because it is easily manufactured and is driven by

relatively low input voltage (3V) [3]. IPMC bends

towards the anode when subjected to a voltage acrossits thickness due to cation migration towards cathode in

the polymer network. When the polarity is changed, it

bends in the reverse direction. In this aspect, theactuating voltage for IPMC is given through our humanmuscle in place of battery source. For this purpose, anelectromyographic (EMG) signal approach is carried

out to transfer the signal from our muscle power. Inpast, Jou et al. (2006) has studied an articulatory feature

classification of face muscles using surfaceelectromyography [4]. Natarajan et al. (2002),

Karakostas et al. (2003)and Kunju et al. (2009) havemodeled the human arm interface for muscle activity,the quantification index of co-contraction at the knee

during walking gait and walking pattern respectively[5-7]. Daley et al. (1990), Hudgins et al. (2000) and

Light et al. (2002) have focused towards the

microprocessor-based multifunctional myoelectriccontrol system. Abdallah et al. (2009) and Ahsan et al.

(2009) have concentrated on step signal of EMG [6-13].Two-dimensional myoelectric control system of arobotic arm for an upper limb amputee and real-time

upper limb motion from non invasive biosignals with

physical human-machine interactions have been studiedby Celani et al. (2007) and Kwon et al. (2009)

respectively [14, 15]. Naik et al. (2010) has also studied

the pattern classification of myo-electrical signal duringdifferent maximum voluntary contractions using BSStechniques for a blind person [16]. Murphy et al. (2009)

has explored the micro electro-mechanical systemsbased sensor for mechanomyography [17]. Lee et al.s

(2004) and Al-Faiz et al.s (2009) research work arerelated to the control of IPMC system for handprosthesis and arm movement recognition based on

EMG signal respectively [18,19]. In furthercontinuation, we are exploring the bio-mimetic

behavior of an IPMC using EMG for micro robotic arm.

The objective of this paper is to examine the bio-

mimetic behavior of IPMC through EMG signal. Whena forearm moves in different angles, generated signal is

2010 International Conference on Advances in Recent Technologies in Communication and Computing

978-0-7695-4201-0/10 $26.00 2010 IEEE

DOI 10.1109/ARTCom.2010.49

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transferred to IPMC which allows bending. This

bending behavior is utilized in IPMC based microrobotic arm movements for micro manipulation system.

II. FORE ARM BEHAVIORA. EMG signal behavior for fore armDuring actuation of an IPMC, an EMG signal is the

measured electric potential produced by voluntarycontraction of muscle fiber. The frequency range of theEMG signal is within 4 to 900 Hz. The dominant

energy is concentrated in the range of 100 Hz and

amplitude of voltage range is 5.5 mV according to

muscle contraction. Using these parameters, the circuitfor filter signal is designed using MATLAB

SIMULINK software as shown in Figure 1. In blockdiagram, the active EMG signal is taken from muscle

and uniform noise is considered. The electric potentialis first amplified with gain 32 dB and then band passfilter (BPF) is used with frequency range 4 to 900 Hz.

Using band stop filter (BSF), noise signal that arisesdue to AC coupler power is eliminated. The signal is

then passed through an amplifier with gain 60 dB.Subsequently, integrators are used to acquire better

damping signal. The filtered signal is then passed toIPMC through ADC/DAC along with control system.The output signal after filtering is shown in Figure 2. It

shows that the EMG signal is taken from muscle in the

range of 5.5 mV. After filtering the noise, steady statesignal is obtained.

Figure 1 Block diagram of EMG signal behavior

0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000-8

-6

-4

-2

0

2

4

6

8x 10

-3

Time (s)

Vo

ltage

(V)

EMG behaviour Voltage Vs. Time

Figure 2 Voltage corresponding to EMG signal behavior

B. Configuration of fore arm motionThe different configurations ranging from 00to 1800are

considered for measurement of displacement in actualenvironment as shown in Figure 3. The initial

articulation of the arm is formed by having 00betweenthe upper arm and forearm. IPMC actuates in a similarmanner according to the fore arm movement. The

magnified displacement of IPMC strip with fore armposition is obtained as shown in Figure 4. It follows the

exponential curve with maximum displacement 14 mm.This displacement would be utilized as an IPMC basedmicro robotic arm for lifting operation.

(a) (b) (c)

(d) (e)

Figure 3 Schematic layout for different positions of fore arm

Figure 4 IPMC displacement response with fore arm position

III. EXPERIMENTAL SETUPThe testing setup for bio-mimetic behavior of IPMC is

shown in Figure 5. For actuation of IPMC throughhuman muscles, EMG electrodes are positioned at

forearm. EMG electrodes generate the voltage from the

muscles which is then fed into the input port of an ADC

Fore arm position= 00 Fore arm position= 450 Fore arm position= 900

Fore arm position= 1350 Fore arm position= 1800

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Figure 5 Basic testing layout of IPMC actuation through muscles

(Analogto-Digital Converter). Electric field andcurrent are imposed on the two faces of IPMC which is

entered through the IPMC driver circuit. This data isamplified through PXI system along with DAQ

Assistant Express VI in LabVIEW 8.5 software. Thecurrent and voltage analysis of the human flexor carpi

ulnaris and extensor carpi ulnaris muscles is also donethrough oscilloscope.

IV. RESULT AND DISCUSSIONDuring experimentation, the input parameter from

muscle ranging from 5.5 mV is taken throughreferenced single-ended (RSE) signal along with

continuous sampled pulses as shown in Figure 6. Thepulse is amplified with the help of a PXI system. The

amplification factor is 550. The desired output voltagerange is generated through a DAC output port with the

same frequency range. The output signal is connectedto IPMC strip. Due to amplified output voltage from theDAC, an IPMC strip bends in one direction. By

changing the polarity of the signal, the bendingbehavior can be reversed. The input and output

configurations of the IPMC are shown in Figures 7 and8.

Figure 6 EMG placements on fore arm

Figure 7 IPMC configuration before fore arm movement

Figure 8 Bending configuration after fore arm movement

The input flexor and extensor pulses are extracted fromEMG signal which is fed to IPMC and various caseshave been studied as shown in Table-I. It has beenanalyzed that output signal (fed to IPMC) is directlyproportional to flexor and extensor muscles signal whenit is working in either on or off mode.

TABLE-I

THE POWER POLARITY ON BOTH SIDES OF IPMC

The voltage signal behavior is taken from EMG and fedto IPMC for actuation as shown in Figure 9. It is foundthat the trend of IPMC actuation voltage is similar toEMG voltage with amplification factor.

Cases Flexor

muscles

Extensor

muscles

State Polarity

Side A Side B

I Off Off None None None

II Off On Extensor Negative Positive

III On Off Flexor Positive Negative

IV On On None None None

IPMC

IPMC control circuitPXI System

DAQ assistant

ADC/DAC

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0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1-6

-4

-2

0

2

4

6x 10

-3

Time (s)

EMG

Voltage(V)

EMG Voltage Vs Time

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1-3

-2

-1

0

12

3

Time (s)IPMC

ActuationVolta

ge(V) IPMC Actuation Voltage Vs Time

Figure 9 Different voltage responses with time

The EMG voltage VEMG (t)and IPMC actuation voltageVIPMC actuation(t) equations are respectively given below;

0.1

01 01 01

0

( ) (2 )EMGt

V t V Sin f t =

= + (1)

and0.1

02 02 020( ) (2 )

IPMCactuationtV t V Sin f t

== + (2)

Where, V01 is mean value of EMG voltage (V); f01 is

EMG frequency range (Hz) ; tis time (s) ; 01is phasedifference when signal is taken through EMG (radian);V02is mean value of IPMC actuation voltage (V); f02is

IPMC actuation frequency range (Hz); 02 is phase

difference when signal is given to IPMC (radian). Forfinding the frequency range of each signal, the

experimental datas are taken and solved throughMATLAB curve fitting tool. The numerical values are

V01= 0.0047070.0000415, f01= 3.950.018, 01=

2.8840.175, V02= 2.6110.045, f02= 48.50.65 and

02= -0.040040.03. From these datas, it is found that

EMG frequency range (f01) is similar to simulated dataand IPMC actuation frequency range is 48.50.65 Hzwhich is nearly human muscle frequency range. Afterthese observations, it is understood that IPMC behaves

as an artificial muscle and the fore arm movement (interms of voltage) can be transferred to IPMC throughEMG. Thus, IPMC strip can be applicable as micro

robotic arm in micro manipulation application.

V. CONCLUSIONIn this paper, IPMC control system with a bio-mimeticfunction through EMG is discussed. EMG signals are

taken from forearm and actuation of IPMC is obtainedwhen fore arm moves at different angles. To obtain

larger displacement, the voltage signal is amplified atdifferent forearm positions. An EMG signal is

generated by an intended contraction of muscles in theforearm which provides the actuation to an IPMC. An

IPMC acts as both capacitive and resistive elementactuator that behaves like biological muscle. This

feature can be applied in the field of rehabilitation

technology and micro manipulation.

In future, we will focus on developing well equippedmicro robotic arm system. Human fore arm movementcould be transferred into IPMC based micro robotic arm

in a similar manner. It can be concluded that IPMC

behavior shows replacement of an electro-mechanicalsystem like electric motors in the application field ofmicro manipulation.

ACKNOWLEDGEMENT

The authors are grateful to the Director, CentralMechanical Engineering Research Institute (CMERI),

Durgapur, West Bengal, India for granting thepermission to publish this paper. The project is

financially supported by the Council of Scientific andIndustrial Research, New Delhi, India under eleventh

five year plan on Modular Re-configurable Micro

Manufacturing Systems (MRMMS) for Multi MaterialDesktop Manufacturing Capabilities (NWP-30) at

CMERI. Authors are also thankful to Mr. SouvickChowdhury (Project Assistant, CMERI) for assistance

in this project.

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Bio-Mimetic Behaviour of IPMC Artificial EMG Signal

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