advanced wheel chair vatsal shah
TRANSCRIPT
Advanced Wheel chair
VATSAL SHAH (UG Student)
Electronics & Communication Dept.
INDUS UNIVERSITY
Ahmedabad, India
Abstract— The paper describes a automatically controlled
wheel chair for disabled people. The chair enables the user
to move his chair using his finger & hand. The flex sensors
and accelerometer on the glove generate ASL coded signals
which are decoded & control the chair. It also display the
information intended by the user. Additionally the
information is also converts to speech. The wireless link
between the glove & wheel chair enables any person to
operate. This advanced wheelchair system is used for physically
disabled and deaf/dumb people move around easily and to
communicate with normal people.
Index Terms—Accelerometer and Flex sensor controlled wheel
chair, Speech Synthesizer, American Sign Language, XBee.
I. INTRODUCTION
American Sign Language Detection and Voice Conversion
is implementation for designing a system in which sensor
glove is used to detect the signs of ASL performed by a
user. It is considered as the standard for communication among
deaf/dumb people. Over 100 million people worldwide, with
physical disabilities require the assistance of a wheelchair.
Two different hardware boards are available. One is placed in
the wheelchair (receiver side/robot side) and second one is
placed at the user side (transmitter side). Once the voltage is
received by the microcontroller, it needs to be transmitted over
to the other side of the system, which is the wheelchair. This is
done by the transmitting circuit present on the hand-glove,
hence realizing wireless communication between the chair and
the glove. The glove comprises flex sensors, accelerometer
on the back of the palm to measure dynamic and static gestures
which detect the position of each finger by monitoring the
bending of the flex sensors mounted on them. The sensor
circuit output is then sent to Microcontroller through ADC.
The pre-stored activated and displayed on the LCD and voice
using speaker. These data will provide a medium for normal
as well as deaf/dumb people to communicate more easily in the
society.
The different directions of motions possible are:
1) Forward: Both the motors in the forward direction.
2) Backward: Both the motors in the reverse direction.
3) Left: Left motor backward direction, Right motor in the
forward direction.
4) Right: Right motor backward direction, Left motor in the
forward direction.
In this project we have used t wo microcontrollers, a
speech IC, speaker to produce the output, LCD display
(16x2), ZigBee, Flex sensors.
The remainder of the paper is constructed as follows.
Section 2 introduces the Fingerspelling used in sign
languages. The block diagram description is presented in
section 3. Section 4 details the system description such as the
flex sensors, the accelerometer sensor, the microcontroller, the
XBee and the receiver part which contains the display unit,
the speech synthesis, the motor driver IC. The system flow
chart is described in section 5. Result and Discussion in
described in section 6. Finally, we conclude the paper in
section 7 and outline the future avenues for our work. [5]
II. FINGER SPELLING
As the third or fourth most widely used language in the
United States [1], American Sign Language (ASL) is the
primary communication means used by members of the North
American deaf community. In the ASL manual alphabet,
fingerspelling is used primarily for spelling out names or
English terms which do not have established signs. Most
of the letters are shown as the viewer would see them, but
some (C, D, G, H, K, P, Q, and to a lesser extent F, O, X) are
shown from the side for clarity (Fig. 1). However, it is also
used for emphasis for clarity, and for instruction. The device
only translates the alphabet, but we can customize a hand
movement to mean a particular word. [15] [7]
Fig.1 American Sign Language Hand Gesture
III. BLOCK DIAGRAM
Fig 2.shows the block diagram of a Wireless American Sign
Language Detection and Voice Conversion Flex Sensor
Controlled wheelchair for Physically Disable and Deaf/Dumb
People. Flex sensors which are variable resistance sensor
which are placed on each of the fingers. This sensor is used to
determine the position/angle of the fingers. Accelerometer is
directly interfaced to the digital ports. Microcontroller
processes the data for each particular gesture made.
Microcontroller is used to read data from different sensors and
then transmit these data to the receiver side. If compared data
get the matched then matched gesture sent with text to LCD
screen and speaker [2].
Fig2. Block Diagram
IV. SYSTEM DESCRIPTION
A. Flex Sensor
The Flex sensors (Fig. 3) are sensors that changes in
resistance depending on the amount of bend on the sensor.
They convert the change in bend to electrical resistance; the
more the bend, the more the resistance value increase. They are
usually in the form of a thin strip from 1’’ to 5” long that vary
in resistance; they could be made in a unidirectional or
bidirectional form. [7]
Fig. 3 4.5” Unidirectional Flex Sensor.
As Flex sensors are analog resistors, they work as variable
analog voltage dividers: when the substrate is bent, the sensor
produces a resistance output relative to the bend radius (Fig. 4)
[7] [11]
Fig. 4 Flex Sensor Offers Variable Resistance Readings.
The impedance buffer in the Basic Flex Sensor Circuit is a
single sided Operational Amplifier, used with these sensors
because the low bias current of the Op-Amp reduces error due
to source impedance of the flex sensor as voltage divider
(Fig. 5). Suggested Op-Amps are the LM358 or LM324.
Fig. 5 Basic Flex Sensor Circuit.
Fig. 6 Characteristics of the Flex Sensor [11]
B. Accelerometer Sensor
To detect the letters 'J' and 'Z', which require movement in
addition to hand position, we add an accelerometer to detect
the movement of the glove/hand. The accelerometer
ADXL335 is a small, thin, low power, complete 3-axis
accelerometer with signal conditioned voltage outputs. The
output signals are analog voltages that are proportional to
acceleration. The accelerometer can measure the static
acceleration of gravity in tilt-sensing applications as well as
dynamic acceleration resulting from motion, shock, or
vibration. Deflection of the structure is measured using a
differential capacitor that consists of independent fixed plates
and plates attached to the moving mass. The fixed plates are
driven by 180° out-of-phase square waves. Acceleration
deflects the moving mass and unbalances the differential
capacitor resulting in a sensor output whose amplitude is
proportional to acceleration. [10]
Display Unit
Micro
controller
Speech
Synthesizer
Speaker
Motor
Driver IC
Left Motor
Right Motor
Receiver
Micro controller
Flex Sensor
Accelerometer Sensor
Transmitter
C. Microcontroller
The AT89S51 is a low-power, high-performance 8-bit
microcontroller with 4K bytes of in System Programmable
Flash memory. It is compatible with the industry-standard
80C51 instruction set and pin out. The on-chip Flash allows
the program memory to be reprogrammed in-system.
AT89S51 is a powerful microcontroller which provides a
highly-flexible and cost-effective solution to many embedded
control applications. The AT89S51 provides the following
standard features: 4K bytes of Flash, 128 bytes of RAM, 32
I/O lines, two data pointers, two 16-bit timer/counters, a
five-vector two level interrupt architecture, a full duplex
serial port, on-chip oscillator, and clock circuitry. The Idle
Mode stops the CPU while allowing the RAM,
timer/counters, serial port, and interrupt system to continue
functioning. The Power-down mode saves the RAM con-
tents but freeze the oscillator, disabling all other chip
functions until the next external interrupt or hardware reset.
D. XBee Module
The XBee RF Modules was engineered to meet IEEE
802.15.4 standards and support the unique needs of low-cost,
low-power wireless sensor networks. The modules require
minimal power and provide reliable delivery of data between
devices. The modules operate within the ISM 2.4 GHz
frequency band and are pin-for-pin compatible with each other
and these modules are embedded solutions providing wireless
end-point connectivity to devices. They are designed for
specifically to replace the proliferation of individual remote
controls
Fig. 7 XBee module.
E. Display Unit
A 16 × 2 line LCD is used to display the status of two inputs (flex sensors, speech synthesis). LCD requires less power, provides backlight during lowlight vision. LCD is interfaced with a microcontroller in byte mode (8-bits of command/data are transmitted at a time). [12]
F. Speech Synthesizer
This module of the system is consisted of a microcontroller
(AT89C51), a SP0256 (speech synthesizer) IC, amplifier
circuitry and a speaker. The function of this module is to
produce voice against the respective gesture. The
microcontroller receives the eight bit data from the “bend
detection” module. It compares the eight bit data with the
predefined values. On the basis of this comparison the
microcontroller comes to know that which gesture does the
hand make. Now the microcontroller knows that which data is
send by the bend detection module, and what the meaning of
this data is. Meaning means that the microcontroller knows if
the hand is making some defined gesture and what should the
system speak. The output of the amplifier is given to the
speaker. [12] [8]
G. Motor Driver IC
L293D is a dual H-Bridge driver, so with one IC we can
interface two DC motors which can be controlled in both
clockwise and counter clockwise direction and a motor with
fixed direction of motion. All I/Os are used to connect four
motors [16]. L293D has output current of 600mA and peak
output current of 1.2A per channel. The output supply has a
wide range from 4.5V to 36V. [3]
Fig. 8 H-Bridge Driver
Driver IC has four switching elements within the bridge. These four elements are often called, high side left, high side right, low side right, and low side left (when traversing in clockwise order). The switches are turned on in pairs, either high left and lower right, or lower left and high right, but never both switches on the same "side" of the bridge. [7] [10]
TABLE I. TRUTH TABLE OF L293D
V. FLOW CHART
This section, Flowchart explains the basic working of the
system in a simple way. Initially, the gestures from the gloves
are accepted. This analog output is then converted to digital
output by the ADC of the micro- controller. This output is
then compared to the previously stored data of letters for the
corresponding gestures and it is checked for validity. If
the gestured value matches any of the pre-stored value,
the corresponding value from database is displayed on the
LCD and voice in speaker or else it goes back in the
loop. The figure below illustrates the Flowchart of the system.
[12]
Fig.9 Flow chart of system execution
VI. RESULT AND DISCUSSION
Advanced wheel chair is the prototype for establishing
easy communication between deaf/dumb people and normal
people. This will surely help them to be independent and
confidently express them. When a person wears a band fixed
with accelerometer and bends is finger the wheelchair moves
in corresponding direction based on the bend of the finger. For
different sign detection and conversion better and sophisticated
implementation, a matrix technique has been implemented.
Here, each sensor bend is divided in three distinct parts, viz.
Complete Bend (CB), Partial bend (PB) and Straight (S).
Range of values, associated with each bend of the respective
sensor is calculated and its digital equivalent i s f o u n d o u t .
Table 1 below, depicts the Bend characteristics corresponding
to each of the five fingers, viz. thumb, index, middle, ring
and little. Though the corresponding concept behind the idea
of the matrix technique. The CB, PB and S values for each
sensor are calculated and the range is specified. [15]
TABLE II. VALUES FOR CB, PB, S
BENDS FINGERS CB PB S
1. THUMB <=550 <=550 >550
2. INDEX <=380 381-500 >500
3. MIDDLE <=340 341-450 >450
4. RING <=390 391-480 >480
5. LITTLE <=460 461-500 >500
The accelerometer sensor is calibrated such that it produces
particular analog voltage for a corresponding tilt. At the end
of the research it is expected that we get h i g h e r accuracy
(upto 90-95%) of hand gesture recognition by using sensory
data gloves. So we have combined flex sensor and
accelerometer sensors data together and then fading to the
microcontroller. These both sensor increases accuracy,
reliability as well as comfort to the user.
Fig. 10 Hand Gesture for Wheelchair System [6]
TABLE III. FLEX SENSOR RANGE
FINGER
LETTERS
THUMB
INDEX
MIDDLE
RING
LITTLE
A S CB CB CB CB
B B S S S S
C S PB PB PB PB
D B S CB CB CB
E B PB PB PB PB
F B CB S S S
G B S CB S CB
H B S S CB CB
I B CB CB CB S
J B CB CB CB PB
K S S S CB CB
L S S CB CB CB
M B PB PB PB CB
N B PB PB CB CB
O B PB PB PB S
P S S PB CB CB
Q S S CB CB S
R B S PB CB CB
S B CB CB CB CB
T S PB CB CB CB
U B PB S CB CB
V S PB PB CB CB
W B S S S CB
X B PB CB CB CB
Y S CB CB CB S
Z B S S CB S
Fig. 11 Implementation of an alphabet ‘A’
VII. CONCLUSION AND FUTURE WORK
This automatically controlled chair is a useful for speech
impaired and partially paralysed patients which fill the
communication gap between patients, doctors and relatives.
They can move around easily and any person can operate this
chair by his finger movements. It will give dumb a voice to
speak for their needs and to express their gesture. System
efficiency is improved with wireless transmission is help in
long distance communication. In future work of the system
supporting more no of sign, different language mode. The
various operations like taking turns, starting or stopping
vehicles can be implemented efficiently. This system is going
to develop as hardware and software.
ACKNOWLEDGMENT
I would like to thank my HOD Prof. R N Mutagi, ECE
Department who had been guiding throughout the task to
complete the work successfully, and would also like to thank
Assoc. Prof. Hansa Shingrakhia, ECE Department and other
staff for extending their help & support in giving technical
ideas about the paper and motivating me to complete the
work effectively & successfully.
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