Robotic arm controlled

Robotic arm controlled

INTRODUCTION

This project involves the work of a, robotic arm controlled using the muscle signals (Electromyogram - EMG). This work is in the field of rehabilitation engineering. This robotic arm is designed to do grasping movement alone. Every muscle fiber has ability to generate action potential which can be recorded and used to control the robotic arm with the help of a Peripheral interface controller- PIC. Such robotic arms controlled using the human EMG signals can be useful for amputated persons at least to a level where they can do their own works like grasping a object, eating etc.

1.1 Description:

Human hand is attached with a sensor which is capable of acquiring the muscle signals. Since the muscle signals EMG is of very low amplitude of mV, it needs to be amplified to a very high level. For this reason only we chose a differential amplifier to amplify the EMG signals to range of several volts. Also we used band pass filter of range 10hz-500hz so that unwanted signals can be remove. A twin T notch filter was used in the circuit in addition to other filters to remove the 50hz power line interference. After acquiring the signals we processed the signal using LABVIEW 9.0, using which we smoothened the signal and was able to find a clear threshold level. Taking the processed signals as input to the PIC, we were able to control the Robotic arm.

EMG Based Robotic Systems:

Robots are currently used in all kinds of dangerous environment and high end factories where they need everything to be automated. The situation is changing and now as a revolution Robotic arm for amputated persons are increasing steeply. We need to give a cheap and yet sophisticated, robotic arm which can be controlled by the amputated person as he wishes. This will help those people who are living in a life of darkness without being able to do their own work.

Here we describe an EMG based control method of a robotic manipulator as an adaptive human supporting system that consists of a finger control part used in grasping movement. This robotic arm has facility to get input from the processed signal from labview. The grasping movement of the robotic arm is based on the contraction of the person. So as a person contracts his hand the amplitude level increases than when it is in relaxed state, this is the principle which we are using to perform the grasping acting when muscle is contracted.

The assembly consists of a signal processor which smoothens the signal and gives a clear envelop, using which threshold can be detected. Then the PIC programming which says that if the input to PIC is above fixed threshold, then the motor is switched on for a particular time till it can complete an 90 degree movement which finishes the grasping. When the signal is below the threshold the PIC is programmed in such a way that motor returns to its original position. Seeing the speed of rotation needed, angle of rotation and amount of weight to be moved or hold, we used a DC motor of 12V power supply.

· Table 1.1Bioelectric Signals

Parameter

Primary Signal Characteristics

Type of Electrode

Electrocardigraphy(ECG)

Frequency range:0.05 to 120 Hz

Signal amplitude:0.1 to 5 µV

Typical Signal:1 µV

Skin Electrode

Electroencephalaography(EEG)

Frequency Range:0.1 to 100 Hz

Signal Amplitude: 2 to 200 µV

Typical Signal:50 µV

Scalp Electrodes

Electromyography(EMG)

Frequency Range:5 to 2000 Hz

Signal Amplitude:0.1 to 5 µV

Needle Electrodes

Electroretinography(ERG)

Frequency Range:dc to 20 Hz

Signal Amplitude:0.5 µV to 1 µV

Typical Signal:0.5 µV

Contact Electrodes

Electro-Oculography

Frequency Range:dc to 100 Hz

Signal Amplitude: 10 to 3500 µV

Typical Signal:0.5 µV

Contact Electrodes

1.2 Basic Bio-Medical Instrumentation System:

The basic purpose of a biomedical instrumentation system is to measure the parameter required, and find any deviation in the parameter so that any abnormality can be found easily. The main intention of instrumentation design is that it can be life saving equipments at times. Any abnormalities of vital organs like Heart, if found before it reaches the danger level can be a life saving one.

Measurand:

The physical parameter from the human body that the instrumentation system measure's is called the measurand. The source for the measurand is the human body(skin, muscles, ECG, EEG, etc,.) which generates a various number of vital signals. The measurand may be on the surface of the body or it may be blood pressure in the chambers of heart.

Transducer/Sensor:

A transducer is a device that converts one form of energy to another. It is the basic or most important one in the measurement because of the material and purpose it is made for. Selection of the transducers is very important as it decides the acquisition level of the signal we need. For example, Ecg needs to measured with surface electrodes placed on chest. The primary function of the transducer is to provide a usable output in response to the measurand which may be a specific physical quantity, property or condition. In practice, two or more transducers may be used simultaneously to make measurements of a number of physiological parameters.

Another term ‘SENSOR' is also used for Transducer in the instrumentation of medical equipments. Normally, a sensor converts a physical form of energy to an electrical signal. The sensor must be minimally invasive and interface with the human body with minimum extraction and loss of energy.

Signal Conditioner:

Converts the output of the transducer which acquires the physical parameter in to an electrical quantity or energy which will be suitable for the operation of display or recording system. Signal conditioners may vary in complexity levels of the cirucit and applications from a simple resistance network or impedance matching device to multi stage circuits and other complex circuitry. Signal Conditioning includes several functions, most of the mathematical signal processing works lik amplifying, filtering, conversion to digital form, etc can be done. They amplify the signals as needed in order to increase the sensitivity of the equipment.

Display System:

Display system is the one which gives a visible form of the signal we acquire may be through graphical representations, charts or graphs or other methods.Although most of the display systems in current use are in visual forms, some are even in audio forms like in doppler method and EMG based bio feedback systems etc. In addition of the above, the processed signal after signal conditioning may be passed on to:

Alarm System-

With upper and lower adjustable thresholds to indicate when the measurand goes beyond preset limits.

Data Storage-

To store the data for future reference. It may be a hard copy on paper or on magnetic or semiconductor memories.

Data Transmission-

using standard interface connections so that information obtained may be carried to other parts of an integrated system or to transmit it from one location to another.

Chapter-1

INTRODUCTION

This project involves the work of a, robotic arm controlled using the muscle signals (Electromyogram - EMG). This work is in the field of rehabilitation engineering. This robotic arm is designed to do grasping movement alone. Every muscle fiber has ability to generate action potential which can be recorded and used to control the robotic arm with the help of a Peripheral interface controller- PIC. Such robotic arms controlled using the human EMG signals can be useful for amputated persons at least to a level where they can do their own works like grasping a object, eating etc.

1.1 Description:

Human hand is attached with a sensor which is capable of acquiring the muscle signals. Since the muscle signals EMG is of very low amplitude of mV, it needs to be amplified to a very high level. For this reason only we chose a differential amplifier to amplify the EMG signals to range of several volts. Also we used band pass filter of range 10hz-500hz so that unwanted signals can be remove. A twin T notch filter was used in the circuit in addition to other filters to remove the 50hz power line interference. After acquiring the signals we processed the signal using LABVIEW 9.0, using which we smoothened the signal and was able to find a clear threshold level. Taking the processed signals as input to the PIC, we were able to control the Robotic arm.

EMG Based Robotic Systems:

Robots are currently used in all kinds of dangerous environment and high end factories where they need everything to be automated. The situation is changing and now as a revolution Robotic arm for amputated persons are increasing steeply. We need to give a cheap and yet sophisticated, robotic arm which can be controlled by the amputated person as he wishes. This will help those people who are living in a life of darkness without being able to do their own work.

Here we describe an EMG based control method of a robotic manipulator as an adaptive human supporting system that consists of a finger control part used in grasping movement. This robotic arm has facility to get input from the processed signal from labview. The grasping movement of the robotic arm is based on the contraction of the person. So as a person contracts his hand the amplitude level increases than when it is in relaxed state, this is the principle which we are using to perform the grasping acting when muscle is contracted.

The assembly consists of a signal processor which smoothens the signal and gives a clear envelop, using which threshold can be detected. Then the PIC programming which says that if the input to PIC is above fixed threshold, then the motor is switched on for a particular time till it can complete an 90 degree movement which finishes the grasping. When the signal is below the threshold the PIC is programmed in such a way that motor returns to its original position. Seeing the speed of rotation needed, angle of rotation and amount of weight to be moved or hold, we used a DC motor of 12V power supply.

· Table 1.1Bioelectric Signals

Parameter

Primary Signal Characteristics

Type of Electrode

Electrocardigraphy(ECG)

Frequency range:0.05 to 120 Hz

Signal amplitude:0.1 to 5 µV

Typical Signal:1 µV

Skin Electrode

Electroencephalaography(EEG)

Frequency Range:0.1 to 100 Hz

Signal Amplitude: 2 to 200 µV

Typical Signal:50 µV

Scalp Electrodes

Electromyography(EMG)

Frequency Range:5 to 2000 Hz

Signal Amplitude:0.1 to 5 µV

Needle Electrodes

Electroretinography(ERG)

Frequency Range:dc to 20 Hz

Signal Amplitude:0.5 µV to 1 µV

Typical Signal:0.5 µV

Contact Electrodes

Electro-Oculography

Frequency Range:dc to 100 Hz

Signal Amplitude: 10 to 3500 µV

Typical Signal:0.5 µV

Contact Electrodes

1.2 Basic Bio-Medical Instrumentation System:

The basic purpose of a biomedical instrumentation system is to measure the parameter required, and find any deviation in the parameter so that any abnormality can be found easily. The main intention of instrumentation design is that it can be life saving equipments at times. Any abnormalities of vital organs like Heart, if found before it reaches the danger level can be a life saving one.

Measurand:

The physical parameter from the human body that the instrumentation system measure's is called the measurand. The source for the measurand is the human body(skin, muscles, ECG, EEG, etc,.) which generates a various number of vital signals. The measurand may be on the surface of the body or it may be blood pressure in the chambers of heart.

Transducer/Sensor:

A transducer is a device that converts one form of energy to another. It is the basic or most important one in the measurement because of the material and purpose it is made for. Selection of the transducers is very important as it decides the acquisition level of the signal we need. For example, Ecg needs to measured with surface electrodes placed on chest. The primary function of the transducer is to provide a usable output in response to the measurand which may be a specific physical quantity, property or condition. In practice, two or more transducers may be used simultaneously to make measurements of a number of physiological parameters.

Another term ‘SENSOR' is also used for Transducer in the instrumentation of medical equipments. Normally, a sensor converts a physical form of energy to an electrical signal. The sensor must be minimally invasive and interface with the human body with minimum extraction and loss of energy.

Signal Conditioner:

Converts the output of the transducer which acquires the physical parameter in to an electrical quantity or energy which will be suitable for the operation of display or recording system. Signal conditioners may vary in complexity levels of the cirucit and applications from a simple resistance network or impedance matching device to multi stage circuits and other complex circuitry. Signal Conditioning includes several functions, most of the mathematical signal processing works lik amplifying, filtering, conversion to digital form, etc can be done. They amplify the signals as needed in order to increase the sensitivity of the equipment.

Display System:

Display system is the one which gives a visible form of the signal we acquire may be through graphical representations, charts or graphs or other methods.Although most of the display systems in current use are in visual forms, some are even in audio forms like in doppler method and EMG based bio feedback systems etc. In addition of the above, the processed signal after signal conditioning may be passed on to:

Alarm System-

With upper and lower adjustable thresholds to indicate when the measurand goes beyond preset limits.

Data Storage-

To store the data for future reference. It may be a hard copy on paper or on magnetic or semiconductor memories.

Data Transmission-

using standard interface connections so that information obtained may be carried to other parts of an integrated system or to transmit it from one location to another.

Chapter-2

Literature Survey

Various research activities have been conducted in the field of electromyography and few of its applications in specific areas are presented here:

2.1 AnEMG-ControlledGraphicInterface ConsideringWearability

Here EMG signal is used to control a graphical interface by classifying the wrist motion using fuzzy min-max neural network.

An Excerpt:

“Human Computer Interaction (HCI) technology using a bioelectric signal such an electromyogram (EMG), an electroencephalogram (EEG) and an electrooculogram (EOG) is considered an alternative to conventional input devices such as a keyboard or a mouse. Among these bioelectric signals, an EMG can be used as a control source for an intuitive and natural HCI because EMGs represent electrical activity of muscles.”

2.2Bioelectric Control of a 757 Class High Fidelity Aircraft Simulation

It demonstrates bioelectric flight control of 757 class simulation aircraft landing at San Francisco International Airport. The physical instrumentality of a pilot control stick is not used. A pilot closes a fist in empty air and performs control movements which are captured by a dry electrode array on the arm, analyzed and routed through a flight director permitting full pilot outer loop control of the simulation.

An Excerpt:

“The basic block shows the steps used to record, extract and sense flight control gestures. The Bioelectric signals passed through three steps to be interpreted as gestures: pre- processing, feature vector formation, and gesture recognition. The pre-processing stages consist of electrode placement and filtering. The remaining two steps, forming feature vectors and recognizing gestures, have many potential implementations. Typical features used for signals includes moving averages of absolute values, neural network weights, Auto-Regression (AR) and mel-cepstrum coefficients, principal components, weighted factors, measures of slope and acceleration of transform coefficients, Short-Time Fourier Transforms (STFT), and wavelet decompositions. Pattern recognition models that might be used to perform pattern recognition include simple threshold indicators, neural networks, linear separators, or HMMs.”

2.3 Using Singular Eigen values of Wavelet Coefficient as the input of SVM to recognize motion Patterns of the Hand

An Excerpt:

“Considering the non-steady character of electromyography signal, wavelet transform is employed to analyze electromyography on the basis of acquired signals that have been preprocessed earlier, consequently singular value decomposition of a wavelet coefficient matrix is adopted to extract features of surface electromyography and the Directed Acyclic Graph Support Vector Machine algorithm is utilized to implement the multi-motion pattern recognition of surface electromyography.”

2.4 WaveletAnalysisofSurface ElectromyographySignals

An Excerpt

“Fast Fourier Transform (FFT) is one of the most common methods for analyzing the signal whether it is filtered or not. Another DSP technique is referred to as Wavelet analysis, a method that is gaining more use in analyzing SEMG signals. Both DWT and WPT use analytical wavelets called “mother wavelet,” which comes in different sets or “families.” Wavelet analysis has the advantage over FFT as it provides the frequency contents of the signal over the time period that is being analyzed. SEMG signals were collected from a muscle under sustained contractions for 4 seconds with different loads. The raw signals were analyzed using FFT, DWT and WPT in Lab VIEW® using its Signal Processing Toolset. Using Wavelet analysis the SEMG signal was decomposed into its frequency content form and then was reconstructed.”

Chapter-3

Theory of Electromyography

Electromyography is a discipline that deals with the detection, analysis and use of electrical signal that emanates from skeletal muscles. The electromyography is studied for various reasons in the medical field. Even a superficial acquaintance with scientific literature will uncover various current applications in fields such as neuro physiology, kinesiology, motor control, psychology, rehabilitation, medicine and biomedical engineering.

The EMG signal is the electrical manifestation of the neuromuscular activation associated with the contracting muscles. The signal represents the current generated by the ionic flow across the membrane of the muscle fibers which propagates through the intervening tissues to reach the detection surface of the electrode located in the environment.

It is an exceedingly complicated signal which is affected by anatomical and physiological properties of muscles and the control scheme of the nervous system, as well as characteristics of the instrumentation used to detect and observe it.

Most of the relationships between the EMG signal and the properties of contracting muscles that are currently in use have evolved serendipitously. The lack of proper description of the EMG signal is probably the greatest single factor that has hampered the development of electromyography in to a precise discipline.

3.1 APPLICATIONS:

  • To test the nerve and muscle activity
  • To determine nerve conduction velocity to test nerve damage/compression
  • To obtain firing characteristics of nerves.
  • Analysis of motor unit action potentials
  • To analyze the extent of nerve damage, muscular damage
  • It is useful for gym trainees and sport persons to evaluate growth and development of specific muscles.
  • It is useful for energy/fatigue analysis of industrial workers for time-motion-rest cycle evaluation for an efficient working environment.
  • Usually passenger pilots are checked for their EMG levels before they take up a flight in order to ensure fatigue level of the pilot is at safe level.

3.2 MUSCLES:

About 40% of the human body is skeletal muscles and another 10% is smooth muscles of internal organs and cardiac muscles from the heart. Here we are interested in characterizing the function of skeletal muscles. The primary function of skeletal muscles is to generate force. Because of this, they are excitable. Thus skeletal muscles have 2 fundamental properties. They are excitable(able to respond to stimulus) and contractible(able to produce tension).A skeletal muscle consists of numerous fibers with diameters ranging from 10 to 80 µm. Each muscle fiber contains hundreds to thousands of myofibrils .Each myofibril has about 1500 myosin filaments and 3000 actins filaments lying side by side.

3.3 Cell Potential:

The nervous system is comprised of neuron cells. Neurons are the conducting elements of the nervous system and are responsible for transferring information across the body. Only these and muscle cells are able to generate potentials and therefore are called excitable cells. Neurons contain special ion channels that allow the cell to change its membrane potential in response to the stimuli the cell receives.

3.4 Receiving Potential:

All cells in the body have a cell membrane surrounding them. Across this membrane there is an electric charge referred to as the resting potential. This electric impulse is generated by differential ion permeability of the membrane. In the cells, potassium (k+) channels allow diffusion of k+ ions out of the cell while Sodium(Na+) ions diffuse in to the cell. This Na+-K+ pump, which requires ATP to operate, pumps two K+ ions in to the interior of the cell for every 3 Na+ ions pumped out. K+ and Na+ ions are continuously diffusing across the membrane from where they were just pumped, but at a slower rate. Since there are more K+ ions inside the cell than outside, a potential exists.

3.5 Action Potential:

Some cells, such as skin cells are not excitable. Other cells such as nerve and muscle cells are excitable. When a simulating electric field acts on an excitable cell, the Na+ permeability increases, Na+ enters the cell interior and the entering positive charge depolarizes(reduces to approximately zero),the transmembrane potential. Later the K+ permeability increases and K+ ions flow out to counter this effect. The Na+ gates close followed by the K+ gates. Finally, the resting potential is regenerated. The action potential lasts about 1ms in nerves and about 100 ms in cardiac muscle. It propagates in nerves at about 60 m/s and carries sensations from the periphery toward the brain via sensory nerves. Through motor nerves, the brain commands muscles to contract. We can calculate the action potential propagation velocity v=d/t where

Figure shown here represents the role of voltage-gated ion channels in the action potential. The circled numbers on the action potential correspond to the 4 diagrams of voltage-gated sodium and potassium channels in a neuron's plasma membrane.

3.6 Motor Unit:

The most fundamental unit of a muscle is called the Motor Unit. It consists of an alpha-motoneuron and all the muscle fibers that are enervated by the motoneuron's branches. The electrical signal that emanates from the activation of muscle fibers of a motor unit that are in the detectable vicinity of an electrode is called MOTOR UNIT ACTION POTENTIAL (MUAP).This constitutes the fundamental unit of the EMG signal.

A Schematic representation of the genesis of a MUAP is presented above. There are many factors that influence the shape of MUAP. Some of these are

  1. The relative geometrical relationship of the detection surface of the electrode and the muscle fiber of the motor unit in its vicinity.
  2. The relative position of the detection surfaces to the innervated zone, which is the region where the nerve branches contact the muscle fibers.
  3. The size of muscle fibers, because amplitude of individual action potential is proportional to the diameter of the fiber, and
  4. The number of muscle fibers of an individual motor unit in the detectable vicinity of the electrode.

The last two factors have particular importance in clinical applications. Considerable work has been performed to identify morphological modifications in the MUAP shape resulting from modifications in the morphology of the muscle fibers or the motor unit such as regeneration of motoneurons. Although usage of MUAP shape analysis is common practice among neurologists, interpretation of the result is not always straight forward and relies heavily on the experience and disposition of the observer.

To sustain muscle contraction, the motor unit must be activated repeatedly. The resulting sequence of MUAP's is called Motor Unit Action Potential Train(MUAPT).So, EMG signal can be synthesized by linearly summing the MUAPT's as they exist when they are detected by the electrode where mathematically generated MUAPT's are added to yield the signal at the bottom.

3.7 MUSCLE CONTRACTION:

As an action potential travels along a motor nerve to muscle fibers, it initiates an action potential along the muscle fiber membrane, which depolarizes the muscle fiber membrane and travels with in the muscle fiber. The Subsequent electro-chemical reaction with in the muscle fiber then initiates attractive forces between the actin and myosin filaments and causes them to slide together. This mechanism produces muscle contraction.

Tension is developed in the muscle as it contracts. There are 3 types of contraction

  • Isometric
  • Concentric
  • Eccentric

Isometric or Static Contraction means a muscle contracts without change in its length. Concentric Contraction occurs when a load is less than the isometric force produced by the muscle and the load shortens the muscle. Eccentric Contraction occurs when the load is greater than the isometric force and elongates the contracting muscle.

CHAPTER 4

SYSTEM HARDWARE

4.1 INTRODUCTION

The basic block here describes the whole system in which EMG electrodes attached to human hand is acquired and amplified using Instrumentation Amplifier. Then filtering is done to remove 50Hz interference noise and selective frequencies are allowed using wide Band Pass filter. Then filtered signal is fed to a comparator or Analog to Digital Converter which serves as a input for the microcontroller to actuate the six servo motors of a Robotic Arm.

4.2 EMG SENSOR/EMG ELECTRODES:

Different kinds of medical instruments require different types of electrodes. For instance, the ECG requires surface electrodes; the EMG uses either surface electrodes or needle electrodes. Electrodes are actually a type of transducer, which extracts the signals. We can obtain the EMG signal simply by placing a surface electrode on the skin enveloping the muscle or by applying an inserted electrode in the muscle.

ELECTRODE CONFIGURATION

The two electrode configurations are

  1. Monopolar configuration
  2. Bipolar configuration

In the monopolar configuration, one electrode is placed on the particular muscle site. Other one is a reference electrode, which is placed on a site with minimal electric association with the inserted site. The drawback of this monopolar configuration is that it detects not only the signal from the muscle of interest but also unwanted signals from around the muscle of interest.

In the bipolar configuration, two electrodes with a small distance between each other are placed in the muscle to pick up the local signals within the muscle of interest. A differential amplifier amplifies the signals picked up from the two electrodes with respect to the signal picked up by a reference electrode. Because the interference signals from a distant source are essentially equal in magnitude and phase as detected by the two electrodes, the common mode rejection capability of the differential amplifier eliminates the unwanted signals.

TYPES OF ELECTRODES

Electrodes used in EMG can be classified into two types:

  1. Surface electrode (or Skin) and
  2. Inserted (Wire or Needle) electrode.

SURFACE ELECTRODES

Surface electrodes may be constructed as either passive of active units. In passive units electrodes consist of detection surface that senses the current on the skin through its skin-electrode interface. In the active configuration, the input impedance of the electrode is greatly increased by electronic means, rendering it less sensitive to the impedance of the electrode-skin interface. The electrode impedance can be reduced by applying conducting gel in the skin-electrode interface and can be further reduced by removing the dead surface layer on the skin along with protective oils; this is best done by light abrasion of the skin. Active electrodes are one which can be either resistively or capacitively coupled to the skin. Although the capacitively coupled electrodes have the advantage of not requiring a conductive medium, they have a higher inherent noise level. Also these electrodes do not have long-term reliability. For these reasons they have not yet found a place in electromyography. The disadvantages of surface electrodes are that they cannot effectively detect signal from muscles deep beneath the skin and that because of poor selectivity, they cannot eliminate cross-talk from adjacent muscles

4.2(a) Surface Electrode 4.2 (b) Needle Electrode

Surface Electrodes are applied inTime-Force relationship of EMG signal, Kinesiological studies of surface muscles, Neurophysiologic studies of surface muscles, Psycho physiological studies, interfacing an individual with external electromechanical devices.

Applications of Needle Electrodes are in manipulating MUAP Characteristics and also in the manipulation of Control properties of motor units (firing rate, recruitment) and find its field in exploratory clinical electromyography.

Wire Electrodes are applied in Kinesiological study of deep muscles, neurophysiologic studies of deep muscles, limited studies of motor unit properties and in Comfortable recording procedure for deep muscles.

Needle and wire electrodes are common in EMG detection. They have diameter in the order of 150 to 25 micrometers. Because of the extremely small surface they are used to pick up action potentials from single motoneurons and are also painless. They are highly non-oxidizing, stiff wire with insulation. Alloys of Platinum, Silver, Nickel and Chromium are preferable. The alloy of 905 Platinum with 10% Iridium offers appropriate combination of chemical inertness.

COMPARISON OF ELECTRODES

Attributes

Indwelling

needle

fine wire

surface (Ag-AgCl)

surface area

arge area behaves like a string of point electrodes; each 'point' picks up the same signal, slightly delayed in time; the sum is a longer duration waveform.

small area picks up more discrete signals without producing long duration waveform

Pick up zone

imited to 0.5 cm to 1.5 cm; can record only from superficial muscles

necessary for recording from deep muscles

"cross talk" (pickup of signals from adjacent muscles)

more common

ess common

Choice of electrode placement

For electrode to detect a muap, it must travel in a direction such that the distance between impulse and electrode changes

Therefore, electrodes should be aligned with expected direction of impulse (or aligned perpendicular to impulses that should be excluded)

SELECTION of Electrode Material

Generally, Noble metals like Gold, Silver, and Platinum are chosen because of their Corrosion resistance. Silver has better mechanical strength. Platinum is used for pacemaker casing. Stainless steel and their alloys are possible alternatives for their low cost and good strength.

4.2.2. CONDUCTIVE GEL

Many types of electrodes require additional conductive gel to enhance the electrical connection. However, older types of conductive gel contained some ingredients that increased the chance of bacterial growth, such as, polysaccharides and some kind of thickener, which are food for bacteria. Most conductive gel consists of sodium chloride, which provides good electrical contact. However, chloride ion can cause skin irritation.

Antibacterial and antifungal ingredients are added into the conductive gel to prevent bacterial growth. The ingredients, such as, methyl P-Hydroxyl benzoate, zephiran chloride and xylenol have been added to prevent and retard bacterial growth.

Important properties that conductive gel should possess are:

  1. Has low moisture vapor transmission rate so that the gel can stay moist during use and for the shelf life.
  2. The gel should have some antibacterial/fungi or disinfected with gamma ray to prevent microorganism and mold growth.
  3. Have ionic salts or surfactants so that it provides low electrolyte-skin impedance. Causes less skin irritation.

4.2.3 Placement of Electrodes:

EMG ELECTRODES

Electromyogram Sensor is made of Ag/AgCl electrodes and it consists of a 3-pin jack to connect to Instrumentation Amplifier.

Here we have one electrode as a common ground placed on the wrist end of the hand and other two electrodes separated from each other by few inches placed on

  1. Extensor Carpi Radialis
  2. Flexor Carpi Radialis-2 Pairs
  3. Biceps Brachi

CHAPTER-5

INSTRUMENTATION AMPLIFIER

The important features of Instrumentation Amplifier which make it popular in Biomedical Applications are:

  • High gain Accuracy.
  • High Common Mode Rejection Ratio.
  • High Gain stability with low temperature coefficient.
  • Low DC offset.
  • Low Output impedance.

The instrumentation amplifier used for this project is LM324.The Instrumentation Amplifier consists of three identical Operational Amplifiers. The first two amplifiers are working in the non-inverting mode but their inverting terminals are not grounded. The feedback loops are connected with the inverting terminals. The third Operational Amplifier will act as Differential Amplifier. The instrumentation amplifier is designed to have high input impedance. All the resistors are Metal Film Military Grade Resistors with tolerance level of 0.1%. All the Capacitors are Tantalum Capacitors with tolerance of 1%. The values of Resistors and the Capacitors are exactly identical to ensure high CMRR. The Values of R, C are chosen such that the Time Period T=2 Seconds. The high input impedance of 10 MegaΩ is provided by resistors R2, R3, and R4. The Capacitors C1, C2, C3 are provided to reduce any DC offset

5.1 LM324 DESCRIPTION:

It consists of four independent high gain frequency compensated operational amplifiers. This LM324 is a product of national semiconductor. The internal circuit consists of so many transistors, resistors and capacitors. Usually an op-amp is a five terminal device. It has two input terminals and one output terminal. One input terminal with a (-) sign is called inverting terminal and other input with (+) sign is called the non-inverting terminal. The other two terminals are power supply terminals.

5.2 GAIN CALCULATIONS :

R7=R8 = a R6 ; R9=R10 ; R11=R12= b R9

We assume the input1 as V1, input2 as V2 and the output of the third operational amplifier as V5. Let the output of the amplifiers prior to C4 and C5 be V3 and V4 respectively.

V3 / R6 = 1 + (R7 / R6) V1 - R7V2

V3 / R6 = 1 + (aR6/ R6) V1 - aR6V2

V4 / R6 = 1 + (R8 / R6) V2 - R8V1

V4 / R6 = 1 + (aR6 / R6) V2 - aR6V1

V5 / R9= (V4 - V3) bR9

V5 = (V2 - V1) (1 + 2a) b

Therefore, a net gain of (1 + 2a) b can be achieved and the gain may be easily adjusted without disturbing the circuit symmetry by varying the resistor R6

For this project we have fixed the value of the R6=500 ohm and R7=R8=50K.

R11=R12=50K and R9=R10=10K. Therefore, a=100 and b=5

Hence, substituting back in the formula, we get a net gain of (1+200)5 =1005.

5.3 COMMON MODE REJECTION RATIO CALCULATIONS:

The Common Mode Rejection Ratio (CMRR) is given by the ratio of Differential Gain to the Common Mode Gain. For the value of CMRR to be extremely high, as it is required for EMG signal, the differential gain has to be made as high as possible and common mode gain as low as possible. The Instrumentation Amplifier components were varied by trial and error method to get the best possible CMRR. After meticulous testing we came up with a CMRR of 45,000. The test results are shown below.

5.3.1. DIFFERENTIAL GAIN TEST:

Sinusoidal signal was fed to the two input terminals individually. First, Input1 was given a signal of amplitude 10mV with respect to ground but Input2 grounded. The output was recorded to be 4.5V. The same was done for Input2 with Input1 grounded. Similar result was recorded. Therefore, Differential Gain= Output/Input=4.5V/10mV= 450.

5.3.2. COMMON MODE GAIN:

For common mode common signal was fed for the two Input terminals with respect to the ground. For an input sinusoidal signal of amplitude 2V the output was recorded to be 20mV.

Therefore, Common mode Gain =output/input=20mV/2V=0.01

Thus,

CMRR=Differential Gain/Common Gain=450/0.01=45,000.

CMRR (dB) = 20 log10 (45,000). = 93Db.

CHAPTER-6

FILTER

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 with in the audio frequency range 10Hz to 10 KHz. The prominent frequency range from 10Hz to 5 KHz has to be isolated to be then processed. Hence, Filters play a vital role in signal conditioning part of this project.

6.1. TYPES OF FILTERS

The filters are generally classified into four types:

  1. Low pass filter
  2. High pass filter
  3. Band pass filter
  4. Band elimination filter

6.2. FILTERS USED IN THE ELECTROMYOGRAPH:

The inherent noise of the Electrical mains i.e., the 50 Hz signal is first filtered out using a Notch Filter. After the 50 Hz signal is attenuated, the signal is then passed through a band-pass filter and the prominent frequencies between 10 Hz and 500Hz is filtered out.

6.3. NOTCH FILTER:

The notch filter used in the Electromyography is a classic pattern which is generally used for attenuating the electrical hum in the environment. It is a narrow band-reject filter. The Notch filter used for this purpose is a Twin-T type filter. This improves the Q-factor of the filter appreciably.

The above circuit shows a Twin-T notch filter. The resistors R, R1, R2 are military grade resistors with 0.1% tolerance. The capacitors are tantalum capacitors with 1% tolerance level. As an EMG is a precision instrument, the components forming the circuitry should be closely matched. The op-amps in the above circuit are a part of a single IC, LM324. This IC houses 4 identical op-amps.

6.3.1. DESIGN:

The frequency to be notched is given by the formula, f = 1/ (2*pi*R*C)

Where R and C are the values of resistor and capacitor forming the Twin-T network.

The value of capacitance is normally kept low as the cost of a capacitor increase with increase in size. Hence, by fixing the capacitor value, the resistance is calculated.

ng the value of ' values of resistor and capacitor forming the Twin-T network.
een 10 Hz and 5 KHz is filtered out.
By fixing the value of ‘C' as 11nanofarads, the value of R was determined to be

278Kohms for f = 50Hz.

6.3.2. TESTING OF NOTCH FILTER:

The notch filter designed has to be tested for a wide frequency band from 10Hz to 10 KHz. It has to attenuate the design frequency of 50Hz power supply noise. The designed filter can be tested with the help of a Cathode ray oscilloscope. A sinusoidal input of amplitude 20V was fed at the Vi and the frequency was varied from 10Hz to 10 KHz in steps. The output from the terminal Vo was observed on cathode ray oscilloscope. The amplitude of the output had a sharp fall to 50mV at a frequency of 50Hz. As the frequency was increased beyond 50Hz the amplitude again increased. The response was as shown below.

6.4. WIDE BAND PASS FILTER:

The wide band Pass filter is a Butterworth filter. It consists of a high-pass filter followed by a low-pass filter. The high pass filter attenuates the frequency greater than the upper cutoff frequency. The output of the high pass filter is then passed through the low pass filter. The low pass filter attenuates the frequencies less than the lower cutoff frequency.

6.4.1. DESIGN:

The wide band Pass filter is a Butterworth filter. It consists of a high-pass filter followed by a low-pass filter. The cut-off frequencies are 10Hz and 500 Hz. The high pass filter attenuates the frequency greater than the upper cutoff frequency. The output of the high pass filter is then passed through the low pass filter. The low pass filter attenuates the frequencies less than the lower cutoff frequency. Thus, the output of the wide band pass filter has a flat conduction band with the gain remaining constant for almost the whole of the band width.

We first design the Low pass filter. The higher cut-off frequency is2KHz.

Therefore, fh= 500 Hz

fh= 1/ (2 * Pi * R1 * C1)

Let us assume the value of the capacitor C1 = 0.1micro Farads.

i.e.500 Hz = 1/ (2 * Pi * 0.1* 10-6 * R1)

We get, R1=796Ω (820Ω)

For designing the High Pass Filter, let us assume the value of C2 = 0.1µF.

fl = 10 Hz for the High pass filter.

fl = 1/ (2 * Pi * R2 * C2)

.i.e. 10 Hz = 1/ (2 * Pi * R2 * 0.1* 10-6)

We get, R2=1.59MegaΩ

6.4.3. CHARACTERISTICS:

The output of the wide band pass filter has a flat conduction band with the gain remaining constant for almost the whole of the band width.

The pass band lies between the upper cut off frequency, fh and lower cut off frequency, fl .It is seen from the figure that the gain remains constant through out the pass band and has a sharp rise/fall in the stop bands.

6.4.4. TESTING:

The Wide Band pass Filter was tested with a Cathode Ray Oscilloscope for frequency range of 1Hz to 2 KHz. The gain was found to be constant for the entire bandwidth

LABVIEW AS A TOOL FOR PROCESSING

abview is a very good and impressing tool in signal processing. We are using labview as a tool for processing of the EMG which we get from the input. Using Labview the signal can be processed to any level we want. The main advantage of this software is that we can see the output visually and it is real time, which makes it a very useful tool. Labview is a tool which is a graphical programming software. It can be interfaced with any hardware using the data acquisition software.

We acquired the signal and after filtering the signals we sent it to the data acquisition system of the labview. Through which signal was sent to labview on real time. Then using the software other filters were used for further processing. Then butterworth smoothening filter of around 200 order was used to get a very clear smoothening, so that the threshold can be found easily. The smoothened signal was seen visually in the graph plotted on real time. The final processed signal was taken as a output from the analog output ports Ao1 and Ao0. This output was then sent to the PIC which has an inbuilt A to D converter.

Acquiring signals in LABVIEW:

Using the NI-DAQ provided specially for data acquisition there was no problem in acquiring the input signals. Just the input port in which we are giving the input is need to be specified in the system designed. Rest of the work will be done by the system it self.

Processing Signals: Using the graphical icons and heading by heading subdivision of almost all mathematical and signal processing tools it is nearly a simple and easy way to process the signals.

REASONS TO CHOSE LABVIEW:

  • We would get a better idea if we use digital filters, so we chose labview
  • Using labview we designed a system for processing EMG as required
  • Visually clear signals can be seen, so that next step of processing can be done with eae
  • Output after processing the signal can be taken outside the DAQ using the analog and digital output ports available in the DAQ.

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