Advanced Wheel chair with voice recognition and transmissionc pujitha,m sukanyaElectronics & Communication Dept. PADMAVATI UNIVERSITYtirupati, India chinthalapujitha@gmail.com 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 theinformation 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 TermsAccelerometer 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 andthe 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 two microcontrollers, a speech IC, speaker to produce the output, LCD display (16x2), ZigBee, Flex sensors. BLOCK DIAGRAM 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

SYSTEM DESCRIPTION A. Flex Sensor The Flex sensors 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. 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 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 . Suggested Op-Amps are the LM358 or LM324.

CHARACTERISTICS OF FLEX SENSOR

fig:flex sensor glove 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.C. Microcontroller and wifi moduleThe 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. WiFi Modules connects to your host CPU over SPI/SDIO/UART interface and helps you to save one extra CPU cost by directly integrating the low footprint SDK and network stack on your CPU. These low-power, low-cost modules are sized to fit within your products. Multiple antenna options and reference starter kits are available to minimize costs and accelerate time-to-mark.The 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 D. 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). E. 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 ofthis 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. 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. Range of values, associated with each bend of the respective sensor is calculated and its digital equivalent is f o un d out. 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 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 higher 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 . 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. REFERENCES [1] M. Sternberg, The American Sign Language Dictionary, Multicom, 1996. [2] Ambikagujrati, Kartigya Singh, Khushboo, Lovika Soral, Mrs. Ambikapathy, Hand-Talk Gloves With Flex Sensor: A Review, International Journal of Engineering Science Invention, Volume 2 Issue 4, Pp 43-46, April 2013. [3] Shruti Warad, Vijayalaxmi Hiremath, Preeti Dhandargi, Vishwanath Bharath, P.B.Bhagavati, Speech and Flex Sensor Controlled Wheelchair for Physically Disabled People unpublished. [4] Dr.Shaik Meeravali, M. Aparna, Design and Development of A Hand-Glove Controlled Wheel Chair Based On MEMS, International Journal of Engineering Trends and Technology (IJETT) Volume 4 Issue 8, August 2013. [5] Sv Anusha, M Srinivasa Rao, P V Ramesh, Design and Development of A Hand Movement Controlled Wheel Chair, Global Journal of Advanced Engineering Technologies, Vol1, Issue4-2012. [6] Ajinkya Raut, Vineeta Singh, Vikrant Rajput, Ruchika Mahale, Hand Sign Interpreter, The International Journal Of Engineering And Science (IJES) B, Vol.1 Issue 2, Pages 19-25, 2012. [7] Jamal Haydar, Bayan Dalal, Shahed Hussainy, Lina El Khansa, Walid Fahs, ASL Fingerspelling Translator Glove, IJCSI International Journal Of Computer Science Issues, Vol. 9, Issue 6, No 1, November 2012. [8] Ata-Ur-Rehman, Salman Afghani, Muhammad Akmal, Raheel Yousaf, Microcontroller and Sensors Based Gesture Vocalizer, Proceedings of the 7th WSEAS International Conference on SIGNAL PROCESSING, ROBOTICS and AUTOMATION (ISPRA '08), University Of Cambridge, UK, February 20-22, 2008. [9] Anbarasi Rajamohan, Hemavathy R., Dhanalakshmi M., Deaf- Mute Communication Interpreter, International Journal of Scientific Engineering and Technology, Volume 2 Issue 5, 1 May 2013. [10] S. Tameemsultana and N. Kali Saranya, Implementation of Head and Finger Movement Based Automatic Wheel Chair, Bonfring International Journal of Power Systems and Integrated Circuits, Vol. 1, Special Issue, December 2011. [11] Praveenkumar S Havalagi, Shruthi Urf Nivedita, The Amazing Digital Gloves That Give Voice To The V oiceless, International Journal Of Advances In Engineering &Technology, Mar. 2013.