ABSTRACT
 The scientific researches in the field of rehabilitation engineering are increasingly providing
mechanisms in order to help people with disability to perform simple tasks of day-to-day.
 Several studies have been carried out highlighting the advantages of using muscle signal in order to
control rehabilitation devices, such as experimental prostheses.
 This project use of forearm surface electromyography (sEMG) signals for classification of several
movements of the arm using just three pairs of surface electrodes located in strategic places.
 Electromyography (EMG) is the control interface for modern, upper limb prosthetics.
 Signal classification by Artificial Neural Network.
 Cost effective

INTRODUCTION
 The development of systems managed by myoelectric signals with the intention to reproduce the human arm
movement is far from perfect, which makes it the target of many investigations
 Control of prosthesis based on the intention of the user .
 Amputees are able to generate standardized myoelectric signals.
 The proposed system uses only 3 pairs of electrodes .
 More precise than conventional limb prosthetic

BACKGROUND INFORMATION
 Current Prosthetic Hand using Technology
BCI TECHNOLOGY
 The mind-to-movement system that allows a quadriplegic man to control a computer using
only his thoughts is a scientific milestone. It was reached, in large part, through the brain gate
system.
 The Brain Gate System is based on Cyber kinetics platform technology to sense, transmit,
analyze and apply the language of neurons.
 The principle of operation behind the Brain Gate System is that with intact brain function, brain
signals are generated even though they are not sent to the arms, hands and legs.

MYO ELECTRIC HAND
 Myo electric uses a battery and electronic motors to function.
 Once it is attached, the prosthetic uses electronic sensors
to detect minute muscle nerve, and EMG activity.
 It then translates this muscle activity (as triggered by the user) into information that its
electric motors use to control the artificial limbs movements.
 The end result is that the artificial limb moves much like a natural limb, according
the mental stimulus of the user.
 The user can even control the strength and speed of the limb’s movements and grip by
varying his or her muscle intensity.

LITERATURE SURVEY
 Classification of Surface Electromyographic Signal for Prosthesis Control
Application
2010 IEEE EMBS Conference on Biomedical Engineering & Sciences (IECBES 2010
KualaLumpurMalaysia, Siti A. Ahmadi, Asnor J. Ishak, Sawal Ali
 This describes the classification stage of an electro myographic (EMG) control system for prosthetic
hand application.
 Moving ApEn was used as main method to extract features from the two channels of surface EMG
signal at the forearm of the upper limb.

BLOCK DIAGARAM OF WORKING FLOW
Signal
Acquisition
USB
interface
Sensor
PIC microcontroller
PC
MATLAB
analysis controlling
Motor drive

CIRCUITS
Usb connection MOTOR PIC 16F87A
POWER
SOURCE
EMG
SENSOR
POWER
EMG SENSOR

PROTOTYPE 1
MATERIAL USED
SILICONE
 Similar to human Wrist Shape
 Not enough strong
 More flexible
 Poor holding power
DESIGNING THE HAND

PROTOTYPE 2
MATERIAL USED
THERMOPLASTICS AND POLYSTYRENE
 Poor Design
 Less Gripping
 Poor Finger Movements
 Not Flexible

PROTOTYPE 3
 Less weight
 Easy to carry
 Easy movements
 Can hold objects
 Elastic Band for Automatic closing
 Upgradable
MATERIALS USED
THERMOPLASTICS WOOD ETC.

FEASIBILITY OF THE TOPIC
The costs of commercially available myoelectric hands are very high, ranging in price from 3-4
lacs.We were able to develop a prototype hand with similar functionally to the more
sophisticated myoelectric hands on the market.It roughly costs up to fifty thousand rupees . A
new technology is devised for manufacturing the Prosthetic hand while making it easily
affordable.

PLATFORM OF THE TOPIC
HARDWARE
 Microcontroller
 EMG sensor
 EMG electrode and pads
 Servo motor
 PVC pipe
 Nylon string

SOFTWARE
MATLAB
MPLAB
PROTEUS

FUTURE ENHANCEMENT
Individual Motors
Powerful microprocessors
Proportional Speed Control
Four Wrist Options
Soft finger pads
Innovative palm design
Durable construction

Project plan
Work done
 Selection of the Materials.
 Designing the prosthetic.
 Shipment of the Hardware parts.
 Prepared the initializing and training codes for the working.
 Completed the source code for motor drive.
 Developed the prototype

CONCLUSION
 The proposed system uses only 3 pair of electrodes for the signal acquisition process.
 The signal processing comprises of initialization, training and testing.
 Artificial Neural Network is configured with three hidden layers
 The no: of values for input sector is equal to the no: of output sector.
 Particular data sets of EMG from amputees are loaded for the processing.

Prosthetic hand using Artificial Neural Network

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