This document describes a digital glove system that translates sign language gestures into voice to enable communication between deaf/mute communities and others. The glove uses flex sensors that detect finger bending and sends signals to an Arduino Uno microcontroller. The Arduino compares the signals to pre-programmed gestures and outputs the corresponding word as text on an LCD display and audio from a speaker. The system was able to recognize 32 different words or phrases through unique finger bending patterns detected by the flex sensors. This digital glove provides a low-cost way to facilitate communication for deaf/mute individuals.
Electronic Hand Glove for Speed Impaired and Paralyzed PatientsIEEEP Karachi
This document describes an electronic hand glove designed to help people with speech impairments or paralysis communicate through gestures. It contains flex sensors that detect finger movements and a microcontroller that interprets the gestures using a lookup table to display letters on an LCD screen. The flex sensors are an economical and robust option that converts finger bends into electrical resistance. The glove allows people with signing abilities to communicate without others understanding sign language. It has applications for home devices, security, industries, biomedicine, and virtual reality. The gesture-based control provides an alternative to keyboards/mice and does not require the user or others to understand sign language.
Electronic hand glove for deaf and blindpptgtsooka
This paper propose a methode design an electronic hand glove which would help the communication between deaf and blind. There are around 285millions of visually impaired people in the world and 900,000 of deaf and blind.
The document describes a gesture vocalizer system that uses multiple microcontrollers and sensors to facilitate communication between deaf, dumb, and blind communities and others. The system can detect gestures using a data glove with bend sensors and tilt sensors, analyze the gestures to determine their meaning, synthesize speech corresponding to the gestures, and display the gesture on an LCD screen. It is designed to translate sign language and other gestures into voice and text to help different communities communicate with each other.
This document describes a sign language to voice conversion glove project. The project aims to help facilitate communication between deaf/mute communities and others by translating sign language gestures into speech. The glove uses flex sensors along the fingers connected to a microcontroller that analyzes the gestures and triggers a voice processing chip to output the corresponding word or phrase. The system is powered by a voltage regulator and includes an LCD for feedback. It provides a low-cost and portable way to bridge the communication gap experience by those in the deaf/mute community.
This document describes a sign language translation project using a glove. The goal of the project is to bridge communication between deaf/mute people and others by translating sign language gestures into text and speech using an inexpensive electronic device. The glove will contain flex sensors and an accelerometer to capture hand movements and gestures, which will then be recognized, translated, and output as text on an LCD display and audio from a speaker. A block diagram shows the overall architecture of the glove unit, detection unit, and other components like the power supply. The document discusses the motivation, prime idea, content layout, advantages, and limitations of the project.
This document summarizes a project that aims to enable communication between deaf or mute individuals and those without disabilities. The system uses flex sensors and an IMU placed in a glove to recognize sign language gestures. The gestures are converted to text and speech by a microcontroller interfaced with a speech synthesis chip. Voice inputs are converted to corresponding sign symbols using a speech recognition module. The flex sensors measure finger bending to determine gestures while the IMU provides data on hand position and movement. Programming is done using MPLAB and a C compiler to control the hardware and enable two-way translation between sign language and speech.
This document describes a microcontroller-based gesture vocalizer system that facilitates communication for the deaf, dumb, and blind. It consists of:
1) A data glove with bend sensors to detect finger movements
2) An accelerometer-based tilt detector to sense hand tilting
3) A gesture detector module that analyzes the bend and tilt data and identifies gestures
4) A speech synthesizer and speaker controlled by the microcontroller to vocalize the recognized gestures
5) An LCD display to show the gesture text for the deaf. The system uses microcontrollers, sensors, and other circuits to recognize static finger gestures and hand tilts and convert them into synthesized speech or displayed text.
This document describes a device that helps people with disabilities communicate. It includes gloves with flex sensors that allow people with paralysis to convey words by finger movements. It also has speech-to-text and text-to-speech functions to help deaf and blind users. The device translates sign language, finger movements, or whispered speech into audible words using sensors, microcontrollers, and Bluetooth. This allows people with disabilities to express their basic needs and thoughts without needing a human interpreter.
Electronic Hand Glove for Speed Impaired and Paralyzed PatientsIEEEP Karachi
This document describes an electronic hand glove designed to help people with speech impairments or paralysis communicate through gestures. It contains flex sensors that detect finger movements and a microcontroller that interprets the gestures using a lookup table to display letters on an LCD screen. The flex sensors are an economical and robust option that converts finger bends into electrical resistance. The glove allows people with signing abilities to communicate without others understanding sign language. It has applications for home devices, security, industries, biomedicine, and virtual reality. The gesture-based control provides an alternative to keyboards/mice and does not require the user or others to understand sign language.
Electronic hand glove for deaf and blindpptgtsooka
This paper propose a methode design an electronic hand glove which would help the communication between deaf and blind. There are around 285millions of visually impaired people in the world and 900,000 of deaf and blind.
The document describes a gesture vocalizer system that uses multiple microcontrollers and sensors to facilitate communication between deaf, dumb, and blind communities and others. The system can detect gestures using a data glove with bend sensors and tilt sensors, analyze the gestures to determine their meaning, synthesize speech corresponding to the gestures, and display the gesture on an LCD screen. It is designed to translate sign language and other gestures into voice and text to help different communities communicate with each other.
This document describes a sign language to voice conversion glove project. The project aims to help facilitate communication between deaf/mute communities and others by translating sign language gestures into speech. The glove uses flex sensors along the fingers connected to a microcontroller that analyzes the gestures and triggers a voice processing chip to output the corresponding word or phrase. The system is powered by a voltage regulator and includes an LCD for feedback. It provides a low-cost and portable way to bridge the communication gap experience by those in the deaf/mute community.
This document describes a sign language translation project using a glove. The goal of the project is to bridge communication between deaf/mute people and others by translating sign language gestures into text and speech using an inexpensive electronic device. The glove will contain flex sensors and an accelerometer to capture hand movements and gestures, which will then be recognized, translated, and output as text on an LCD display and audio from a speaker. A block diagram shows the overall architecture of the glove unit, detection unit, and other components like the power supply. The document discusses the motivation, prime idea, content layout, advantages, and limitations of the project.
This document summarizes a project that aims to enable communication between deaf or mute individuals and those without disabilities. The system uses flex sensors and an IMU placed in a glove to recognize sign language gestures. The gestures are converted to text and speech by a microcontroller interfaced with a speech synthesis chip. Voice inputs are converted to corresponding sign symbols using a speech recognition module. The flex sensors measure finger bending to determine gestures while the IMU provides data on hand position and movement. Programming is done using MPLAB and a C compiler to control the hardware and enable two-way translation between sign language and speech.
This document describes a microcontroller-based gesture vocalizer system that facilitates communication for the deaf, dumb, and blind. It consists of:
1) A data glove with bend sensors to detect finger movements
2) An accelerometer-based tilt detector to sense hand tilting
3) A gesture detector module that analyzes the bend and tilt data and identifies gestures
4) A speech synthesizer and speaker controlled by the microcontroller to vocalize the recognized gestures
5) An LCD display to show the gesture text for the deaf. The system uses microcontrollers, sensors, and other circuits to recognize static finger gestures and hand tilts and convert them into synthesized speech or displayed text.
This document describes a device that helps people with disabilities communicate. It includes gloves with flex sensors that allow people with paralysis to convey words by finger movements. It also has speech-to-text and text-to-speech functions to help deaf and blind users. The device translates sign language, finger movements, or whispered speech into audible words using sensors, microcontrollers, and Bluetooth. This allows people with disabilities to express their basic needs and thoughts without needing a human interpreter.
IRJET- Smart Hand Gloves for Disable PeopleIRJET Journal
1) The document describes a smart glove prototype designed to help disabled people communicate through hand gestures.
2) The glove uses flex sensors on the fingers to detect hand gestures and an Arduino microcontroller to convert the gestures to text or pre-recorded voices.
3) The glove has three modes - displaying gesture status, converting gestures to voices, and controlling home appliances wirelessly through hand gestures.
Human Computer Interface Glove for Sign Language TranslationPARNIKA GUPTA
A human computer interface glove was developed with the aim of translating sign language to text & speech. The glove utilizes five flex sensors and an inertial measurement unit to accurately capture hand gestures. All components were placed on the backside of the glove providing the user with full range of motion, and not restricting the user from performing other tasks while wearing the glove.
This document summarizes a senior design project report for a smart glove that translates hand gestures into vocalized speech. The project aims to help deaf and mute people communicate by converting sign language gestures into audio that can be understood by others. The smart glove uses flex sensors on the fingers and an accelerometer to detect hand and finger movements. An AVR microcontroller reads the sensor data and sends it to a speech synthesizer module that outputs the corresponding audio. The report describes the design process, including an overview of the hardware and software components, sensor testing and interfacing, gesture recognition algorithms, and prototype testing. The smart glove aims to improve communication for deaf and mute individuals and reduce barriers between them and others.
The document describes the APR9600 single-chip voice recording and playback integrated circuit from APLUS Integrated Circuits. Key features include 60 seconds of recording time, non-volatile flash memory, random and sequential access of multiple messages, and low power consumption. It provides detailed descriptions of the device's functionality in random access mode and tape mode, including recording and playback procedures in each mode. Block diagrams and pin descriptions are also included to explain the device's internal architecture and interface.
Hand talk (assistive technology for dumb)- Sign language glove with voiceVivekanand Gaikwad
We propose a sign language glove which will assist those people who are suffering for any kind of speech defect to communicate through gesture. The glove will record all the gesture made by the user & then it will translate these gesture into audio form.
This document summarizes a presentation on HandTalk, a technology that aims to help deaf and mute individuals communicate. HandTalk uses a virtual reality glove called the P5 glove that detects finger gestures and converts them to text using gesture recognition software. The text is then converted to speech so hearing individuals can understand the deaf or mute person. The goal is to create an accurate and inexpensive alternative to existing expensive gesture recognition systems. The presentation outlines the hardware, software, user interface, motivation, design, problems with other systems, and future enhancements of the HandTalk system.
This document describes a project to create talking gloves that can translate sign language gestures into text or speech. The gloves would use flex sensors attached to the fingers to detect hand gestures and convert these into alphanumeric characters. A microcontroller would encode the gestures for transmission via RF to a receiver where the signals would be decoded and the recognized gestures converted to voice using voice recognition software. This would allow deaf people to communicate with others using their hands and sign language translated into a form others could understand.
This document describes a sign language translation system using a sensor glove. The glove is fitted with flex sensors that detect finger bending. The sensor outputs are processed by an ARM7 microcontroller and converted to speech using a speaker. When signs are performed, the flex sensor data is compared to a database of signs to determine the word. The recognized word is then displayed on an LCD and voiced using the speaker, allowing deaf people to communicate through sign language translation. The system provides a low-cost way for speech-impaired individuals to communicate using a wearable sensor glove and microcontroller-based translation of signs to voice.
This document describes a seminar presentation on a sign language recognition system for deaf and dumb people. The system uses a microcontroller, flex sensors to detect hand gestures, an ADC to convert analog sensor signals to digital, and a voice processor and speakers to provide audio output of the recognized sign. It recognizes several letters and displays them on an LCD. Potential applications include improving communication for deaf individuals and future work could expand its capabilities.
IRJET- Smart Gloves for Hand Gesture Recognition and Translation Into Text an...IRJET Journal
1. Smart gloves are developed that use flex sensors embedded in the gloves to detect hand gestures representing letters and words in sign language.
2. The detected gestures are sent to a microcontroller which translates them into text messages and sends them via Bluetooth to a smartphone app.
3. The smartphone app then converts the text to audio speech, allowing the gloves to translate sign language gestures into text and audio in real-time for deaf communication.
This document provides an overview of a project to develop a sensor glove that translates sign language gestures into written and spoken words. It discusses the following key points:
- The glove uses copper sensors on the fingers connected to an Arduino microcontroller and RN42 Bluetooth module to detect gestures and transmit data wirelessly to an Android phone application.
- The Android app receives character data from the Bluetooth, translates the characters into words, and displays and speaks the words in both Arabic and English.
- The total estimated cost of materials for the glove prototype is $70, using low-cost components like an Arduino, Bluetooth module, and copper sensors to keep costs minimal.
Microcontroller Based Sign Language Gloveijsrd.com
The people who are speech impaired and paralyzed patients those have difficulty in communication. So that patients cannot speak and hear properly and they have problem in communication to other people who don't understand sign languages. So at that time electronic hand glove is used for communication and for that one hand is used for making position of different fingers using flex sensors. The objective of my project is to develop a electronic device for the people who suffer from speech impairment and paralyzed patients. In this, Flex sensor glove is used and Indian sign language's alphabets make using different position of fingers and thumb and their output are shown in the LCD.
DESIGN OF LOW COST AND EFFICIENT SIGN LANGUAGE INTERPRETER FOR THE SPEECH AND...Dr.SHANTHI K.G
This document describes the design of a low-cost and efficient sign language interpreter for deaf and hearing impaired people. A glove with flex sensors is used to detect hand gestures, which are sent wirelessly via WiFi or XBee to a smartphone app or LCD display. The signals are interpreted as letters, words or sentences to bridge communication between deaf/mute and hearing people. The system aims to make basic communication easier without needing to know sign language.
This document describes a project to create a sensor glove that translates sign language gestures into written and spoken words. The glove uses touch sensors connected to an Arduino microcontroller and RN42 Bluetooth module. The Arduino code defines the sensor pins and sends character data over Bluetooth. An Android app receives the characters, translates them to words, and displays and speaks the words in Arabic and English. The goal is to enable communication for deaf-mute people without relying on their mobile device. The total equipment cost was $70. A video demonstration of the working project is provided.
Generally dumb people use sign language for communication but they find difficulty in communicating with others who don’t understand sign language. This project aims to lower this barrier in communication. It is based on the need of developing an electronic device that can translate sign language into speech in order to make the communication take place between the mute communities with the general public possible. A Wireless data gloves is used which is normal cloth driving gloves fitted with flex sensors along the length of each finger and the thumb. Mute people can use the gloves to perform hand gesture and it will be converted into speech so that normal people can understand their expression. Sign language is the language used by mute people and it is a communication skill that uses gestures instead of sound to convey meaning simultaneously combining hand shapes, orientations and movement of the hands, arms or body and facial expressions to express fluidly a speaker’s thoughts. Signs are used to communicate words and sentences to audience.
Deaf and Dump Gesture Recognition SystemPraveena T
This presentation mainly tells about the problems of those people followed by solution and an overall view of various topics such as market overview,target customers,flow chart,technology used,cost analysis and finally future plans.
An input is anything that is entered into a computer system to produce an output. Common computer inputs include keyboards, mice, microphones, scanners, touchscreens, cameras, bar code scanners, chip and pin readers, magnetic stripe readers, MIDI devices, sensors, and remote controls. Specialist inputs used to aid accessibility include puff-suck switches, braille keyboards, and foot mice.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This document summarizes a student project report on developing "talk gloves" that translate sign language gestures into speech. The report is dedicated to the students' teachers and families who supported them. It acknowledges those who helped with the project, including their supervisor Dr. Falah Mohammed. The report contains chapters on the project's constraints and standards, literature review, methodology used, results and analysis, and conclusions. The talk gloves are intended to help solve communication barriers faced by deaf individuals by allowing translation of sign language gestures into spoken words using a smartphone. The gloves contain sensors on the fingers to detect hand movements which are sent via Bluetooth to an Android app that converts the signals to voice. The project aims to give a voice to the 70 million
This document provides an overview of Open'Act, a consulting, coaching and training firm. It discusses Open'Act's values of innovation, efficiency, engagement and respect. It outlines Open'Act's areas of expertise, including performance, project management, change management and leadership. The document also summarizes Open'Act's strategic plan to become a global business partner focused on innovation and custom solutions.
This document provides guidance on preparing for and delivering effective research and teaching job talks. It discusses the purposes of such talks, which are to inform, excite, and engage the audience while demonstrating a strong fit. The presentation should have a clear message and convey the presenter's passion and comfort with the content. Effective preparation involves understanding the audience, timing, technology, and expectations. The content should flow from the research question to impact, approaches, outcomes, and next steps. Sample structures divide the talk into sections tailored for different audience levels of expertise. Effective teaching demonstrations emphasize accurate yet accessible content and student engagement through organization, pace, enthusiasm and inviting questions. Thorough preparation and practice are emphasized.
IRJET- Smart Hand Gloves for Disable PeopleIRJET Journal
1) The document describes a smart glove prototype designed to help disabled people communicate through hand gestures.
2) The glove uses flex sensors on the fingers to detect hand gestures and an Arduino microcontroller to convert the gestures to text or pre-recorded voices.
3) The glove has three modes - displaying gesture status, converting gestures to voices, and controlling home appliances wirelessly through hand gestures.
Human Computer Interface Glove for Sign Language TranslationPARNIKA GUPTA
A human computer interface glove was developed with the aim of translating sign language to text & speech. The glove utilizes five flex sensors and an inertial measurement unit to accurately capture hand gestures. All components were placed on the backside of the glove providing the user with full range of motion, and not restricting the user from performing other tasks while wearing the glove.
This document summarizes a senior design project report for a smart glove that translates hand gestures into vocalized speech. The project aims to help deaf and mute people communicate by converting sign language gestures into audio that can be understood by others. The smart glove uses flex sensors on the fingers and an accelerometer to detect hand and finger movements. An AVR microcontroller reads the sensor data and sends it to a speech synthesizer module that outputs the corresponding audio. The report describes the design process, including an overview of the hardware and software components, sensor testing and interfacing, gesture recognition algorithms, and prototype testing. The smart glove aims to improve communication for deaf and mute individuals and reduce barriers between them and others.
The document describes the APR9600 single-chip voice recording and playback integrated circuit from APLUS Integrated Circuits. Key features include 60 seconds of recording time, non-volatile flash memory, random and sequential access of multiple messages, and low power consumption. It provides detailed descriptions of the device's functionality in random access mode and tape mode, including recording and playback procedures in each mode. Block diagrams and pin descriptions are also included to explain the device's internal architecture and interface.
Hand talk (assistive technology for dumb)- Sign language glove with voiceVivekanand Gaikwad
We propose a sign language glove which will assist those people who are suffering for any kind of speech defect to communicate through gesture. The glove will record all the gesture made by the user & then it will translate these gesture into audio form.
This document summarizes a presentation on HandTalk, a technology that aims to help deaf and mute individuals communicate. HandTalk uses a virtual reality glove called the P5 glove that detects finger gestures and converts them to text using gesture recognition software. The text is then converted to speech so hearing individuals can understand the deaf or mute person. The goal is to create an accurate and inexpensive alternative to existing expensive gesture recognition systems. The presentation outlines the hardware, software, user interface, motivation, design, problems with other systems, and future enhancements of the HandTalk system.
This document describes a project to create talking gloves that can translate sign language gestures into text or speech. The gloves would use flex sensors attached to the fingers to detect hand gestures and convert these into alphanumeric characters. A microcontroller would encode the gestures for transmission via RF to a receiver where the signals would be decoded and the recognized gestures converted to voice using voice recognition software. This would allow deaf people to communicate with others using their hands and sign language translated into a form others could understand.
This document describes a sign language translation system using a sensor glove. The glove is fitted with flex sensors that detect finger bending. The sensor outputs are processed by an ARM7 microcontroller and converted to speech using a speaker. When signs are performed, the flex sensor data is compared to a database of signs to determine the word. The recognized word is then displayed on an LCD and voiced using the speaker, allowing deaf people to communicate through sign language translation. The system provides a low-cost way for speech-impaired individuals to communicate using a wearable sensor glove and microcontroller-based translation of signs to voice.
This document describes a seminar presentation on a sign language recognition system for deaf and dumb people. The system uses a microcontroller, flex sensors to detect hand gestures, an ADC to convert analog sensor signals to digital, and a voice processor and speakers to provide audio output of the recognized sign. It recognizes several letters and displays them on an LCD. Potential applications include improving communication for deaf individuals and future work could expand its capabilities.
IRJET- Smart Gloves for Hand Gesture Recognition and Translation Into Text an...IRJET Journal
1. Smart gloves are developed that use flex sensors embedded in the gloves to detect hand gestures representing letters and words in sign language.
2. The detected gestures are sent to a microcontroller which translates them into text messages and sends them via Bluetooth to a smartphone app.
3. The smartphone app then converts the text to audio speech, allowing the gloves to translate sign language gestures into text and audio in real-time for deaf communication.
This document provides an overview of a project to develop a sensor glove that translates sign language gestures into written and spoken words. It discusses the following key points:
- The glove uses copper sensors on the fingers connected to an Arduino microcontroller and RN42 Bluetooth module to detect gestures and transmit data wirelessly to an Android phone application.
- The Android app receives character data from the Bluetooth, translates the characters into words, and displays and speaks the words in both Arabic and English.
- The total estimated cost of materials for the glove prototype is $70, using low-cost components like an Arduino, Bluetooth module, and copper sensors to keep costs minimal.
Microcontroller Based Sign Language Gloveijsrd.com
The people who are speech impaired and paralyzed patients those have difficulty in communication. So that patients cannot speak and hear properly and they have problem in communication to other people who don't understand sign languages. So at that time electronic hand glove is used for communication and for that one hand is used for making position of different fingers using flex sensors. The objective of my project is to develop a electronic device for the people who suffer from speech impairment and paralyzed patients. In this, Flex sensor glove is used and Indian sign language's alphabets make using different position of fingers and thumb and their output are shown in the LCD.
DESIGN OF LOW COST AND EFFICIENT SIGN LANGUAGE INTERPRETER FOR THE SPEECH AND...Dr.SHANTHI K.G
This document describes the design of a low-cost and efficient sign language interpreter for deaf and hearing impaired people. A glove with flex sensors is used to detect hand gestures, which are sent wirelessly via WiFi or XBee to a smartphone app or LCD display. The signals are interpreted as letters, words or sentences to bridge communication between deaf/mute and hearing people. The system aims to make basic communication easier without needing to know sign language.
This document describes a project to create a sensor glove that translates sign language gestures into written and spoken words. The glove uses touch sensors connected to an Arduino microcontroller and RN42 Bluetooth module. The Arduino code defines the sensor pins and sends character data over Bluetooth. An Android app receives the characters, translates them to words, and displays and speaks the words in Arabic and English. The goal is to enable communication for deaf-mute people without relying on their mobile device. The total equipment cost was $70. A video demonstration of the working project is provided.
Generally dumb people use sign language for communication but they find difficulty in communicating with others who don’t understand sign language. This project aims to lower this barrier in communication. It is based on the need of developing an electronic device that can translate sign language into speech in order to make the communication take place between the mute communities with the general public possible. A Wireless data gloves is used which is normal cloth driving gloves fitted with flex sensors along the length of each finger and the thumb. Mute people can use the gloves to perform hand gesture and it will be converted into speech so that normal people can understand their expression. Sign language is the language used by mute people and it is a communication skill that uses gestures instead of sound to convey meaning simultaneously combining hand shapes, orientations and movement of the hands, arms or body and facial expressions to express fluidly a speaker’s thoughts. Signs are used to communicate words and sentences to audience.
Deaf and Dump Gesture Recognition SystemPraveena T
This presentation mainly tells about the problems of those people followed by solution and an overall view of various topics such as market overview,target customers,flow chart,technology used,cost analysis and finally future plans.
An input is anything that is entered into a computer system to produce an output. Common computer inputs include keyboards, mice, microphones, scanners, touchscreens, cameras, bar code scanners, chip and pin readers, magnetic stripe readers, MIDI devices, sensors, and remote controls. Specialist inputs used to aid accessibility include puff-suck switches, braille keyboards, and foot mice.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This document summarizes a student project report on developing "talk gloves" that translate sign language gestures into speech. The report is dedicated to the students' teachers and families who supported them. It acknowledges those who helped with the project, including their supervisor Dr. Falah Mohammed. The report contains chapters on the project's constraints and standards, literature review, methodology used, results and analysis, and conclusions. The talk gloves are intended to help solve communication barriers faced by deaf individuals by allowing translation of sign language gestures into spoken words using a smartphone. The gloves contain sensors on the fingers to detect hand movements which are sent via Bluetooth to an Android app that converts the signals to voice. The project aims to give a voice to the 70 million
This document provides an overview of Open'Act, a consulting, coaching and training firm. It discusses Open'Act's values of innovation, efficiency, engagement and respect. It outlines Open'Act's areas of expertise, including performance, project management, change management and leadership. The document also summarizes Open'Act's strategic plan to become a global business partner focused on innovation and custom solutions.
This document provides guidance on preparing for and delivering effective research and teaching job talks. It discusses the purposes of such talks, which are to inform, excite, and engage the audience while demonstrating a strong fit. The presentation should have a clear message and convey the presenter's passion and comfort with the content. Effective preparation involves understanding the audience, timing, technology, and expectations. The content should flow from the research question to impact, approaches, outcomes, and next steps. Sample structures divide the talk into sections tailored for different audience levels of expertise. Effective teaching demonstrations emphasize accurate yet accessible content and student engagement through organization, pace, enthusiasm and inviting questions. Thorough preparation and practice are emphasized.
This power point is in the form of lecture notes on Application of Newton's laws. I have discussed four examples on the application of Newton's law. I expect this power point helps students of A level physics to understand calculations related to Newtons law easily
El documento resume las respuestas de un grupo de estudiantes a preguntas sobre la evolución de las primeras sociedades humanas, el desarrollo de la agricultura y la domesticación de animales, y el origen de la propiedad privada y el intercambio de bienes y servicios. El grupo discute cómo el trueque probablemente comenzó espontáneamente debido a la escasez y cómo los valores de los bienes emergieron de la necesidad y el trabajo. También creen que la propiedad privada surgió cuando los humanos se hicieron sedentarios y
Este documento presenta ejemplos de uso de preposiciones de lugar en inglés y español, incluyendo "on, in, over, under, in front of, behind, between, near" y sus traducciones respectivas al español para indicar la ubicación de objetos y animales domésticos comunes.
Increase Online Sales by Optimizing Your Email Experience Return Path
Email is the bedrock in which all other digital channels rely on to meet their goals and objectives, whether that’s increasing traffic to your website, increasing your social followers, creating a cohesive customer journey, or turning prospects into qualified leads. Only by optimizing the email customer experience will a brand be able to increase its online sales overall. Guy Hanson, Senior Director Professional Services at Return Path has summarized 10 tactics every email marketer should use today.
The document describes a smart glove system for deaf and mute people that uses flex sensors and an Arduino board to translate sign language gestures into text or speech. The system captures gestures using flex sensors on a glove connected to an Arduino board. The Arduino board transforms the gestures into text or speech using a text-to-speech converter. An Android app is also proposed to receive the translated messages and output them as voice, allowing deaf people to communicate with others. The system aims to provide an easy and portable way for speech and hearing impaired individuals to communicate.
This project aims to develop a smart glove interpreter to facilitate communication between deaf or impaired people and normal people using wireless data transmission. The glove is fitted with flex sensors that detect gestures which are processed by a microcontroller to provide voice outputs or messages based on the gesture. It allows impaired people to control devices or send alerts. The system works by mapping different finger flexing patterns detected by flex sensors to specific text messages or voice outputs. This provides an easier means of communication for impaired individuals.
The document describes a smart assistance glove designed for disabled people using flex sensors and Arduino/Raspberry Pi modules. The glove detects finger gestures via flex sensors and displays corresponding commands on an Android app with audio output. Data is transmitted wirelessly between the Arduino and Raspberry Pi. An emergency alert can also be sent via GSM module. The goal is to help those with communication barriers communicate more easily.
This document describes an advanced wheelchair system that allows disabled users to control a wheelchair through gestures detected by sensors on a glove. The glove uses flex sensors and an accelerometer to detect finger bending and hand movements, translating them into signals that wirelessly control the wheelchair's movement and allow it to display text and synthesized speech of the user's intended commands. The system is designed to help both physically disabled and deaf/dumb users communicate and move independently through automatic wheelchair control based on hand gestures.
1) The document describes an advanced wheelchair system that uses a sensor glove and voice recognition to allow disabled users to control the wheelchair and communicate through gestures and synthesized speech.
2) The sensor glove uses flex sensors and an accelerometer to detect finger positions and gestures, which are wirelessly transmitted to control the wheelchair's movement and display text and speech.
3) The system is intended to help physically disabled and deaf/mute users move independently and communicate more easily.
Smart Remote for the Setup Box Using Gesture ControlIJERA Editor
The basic purpose of this project is to provide a means to control a set top box (capable of infrared
communication), in this case Hathway using hand gestures. Thus, this system will act like a remote control for
operating set top box, but this will be achieved through hand gestures instead of pushing buttons. To send and
receive remote control signals, this project uses an infrared LED as Transmitter. Using an infrared receiver, an
Arduino can detect the bits being sent by a remote control. And to playback a remote control signal, the
Arduino can flash an infrared LED at 38 kHz. With this project we can design a gesture controlled remote by
using a glove, it can be fixed to the hand, we can send any signal of any length, at any related frequency, and
thus we can design a universal remote
IRJET- Smart Speaking Glove for Speech Impaired PeopleIRJET Journal
This document describes a smart speaking glove system for speech impaired people that uses flex sensors on a glove to detect gestures and convert them to synthesized speech output. The flex sensors detect finger bending and send signals to a microcontroller. The microcontroller matches the signals to predefined gestures and messages stored in its database and outputs the corresponding message to an LCD display and speaker. It also includes an emergency function using a GPS and GSM modules to track the user's location and send a message if they activate a panic switch.
This document describes a hand gesture vocalizer system that aims to help deaf, blind, and speech impaired people communicate more easily. The system uses flex sensors on a glove to detect finger bending gestures and an accelerometer to detect hand tilting gestures. A microcontroller identifies the gestures and sends the output to an LCD display and via Bluetooth to an Android phone to vocalize the gesture as speech. The system was designed and developed by students to address communication barriers for people with disabilities by translating common sign language gestures into audio and text outputs. It achieved gesture detection and translation but had limitations in vocabulary size and accuracy. Future work could explore expanding its capabilities for more advanced communication.
IRJET- IoT based Portable Hand Gesture Recognition SystemIRJET Journal
This document describes a portable hand gesture recognition system to help deaf and mute people communicate. The system uses flex sensors on a glove to detect hand gestures. An Arduino microcontroller matches the gestures to a database and sends the output to a smartphone via Bluetooth. The smartphone app then converts the text to speech so others can understand the user's message. The system is meant to overcome communication barriers for those unable to speak or hear by translating sign language gestures into audible speech in real-time.
IRJET- Smart Gloves to Convert Sign Languages to Vocal OutputIRJET Journal
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Patients with speech disorders often find it difficult to communicate their needs to the general audience. These patients include the mute, senior citizens, paralyzed, and patients with diseases such as dysarthria, aphasia, to name a few. To satisfy their requirements, the Gesture Gloves have been designed. These gloves ease the communication, without much ado, by engendering predefined gestures to voice. The input is in the form of hand gestures which are converted to text and speech. The gloves are equipped with multiple flex sensors that produce varying resistance for every gesture made by the person.
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This document describes a smart glove system designed to help disabled persons communicate more easily. The gloves contain flex sensors on each finger that detect hand gestures. The flex sensor data is sent to an Arduino Leonardo microcontroller which analyzes the gestures and outputs corresponding speech from a speaker or displays text on an LCD screen. An emergency gesture can also trigger alert messages by GSM module. The system aims to reduce communication barriers for the deaf or paralyzed by translating gestures into audio or text that others can understand.
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This document describes a system to convert sign language gestures to speech using flex sensors and an Arduino microcontroller. The system uses a glove fitted with flex sensors that detect the degree of bending of the fingers. The sensor output varies with the amount of bend and is converted to resistance values. The Arduino reads the sensor values and compares the gestures to a database to determine the matching sign. It then outputs the corresponding word or phrase as audio speech using a voice module. The flex sensors measure finger movements and positions to recognize static and dynamic signs. When a sign is identified, the Arduino triggers the voice module to vocalize the sign, allowing deaf people to communicate via translated sign language. The system aims to help break down communication barriers
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conference1final
1. Abstract— Dumb people mostly use sign language for
communication but they find difficulty in communicating with
others who don’t understand sign language. This paper aims to
bridge this barrier in communication. It is based on the need of
developing an electronic device that can translate sign
language into voice in order to make the communication
possible between the mute communities with the general public
possible[7]. A Digital glove is used which is normal cloth of
driving gloves attached with Flex sensors along the length of
each finger and the thumb.
Mute people can use this glove to perform hand gesture
and it will be converted into a particular pattern so that normal
people can understand their meaning. A gesture in a sign
language is a particular movement of the hands with a specific
shape made out of them. In this project Flex Sensor plays the
important role, Flex sensors are sensors that change in
resistance depending on the amount of bend on the sensor and
corresponding output is generated in form of text displayed on
LCD and in form of audio played through speaker[4].
Index Terms—Flex Sensor, Arduino Uno, LM386.
I. INTRODUCTION
In our daily life, we have to interact with different kinds
of the people through regional or global language. This
communication is effective because both people know the
language, but in case of dumb, mute people problem is
arrived as maximum people are unaware of sign language.
So we are going to design the system through which
everyone can able to understand sign language without
extra efforts using Arduino Uno and Flex sensor. This
system will be helpful in malls, hospitals and mute schools.
A. Technical Background
The gesture recognition can be done either by image
processing technique or using sensor based network. In
image processing, expensive camera is used as input and
captured image taken as variable parameter with more
complex computation as it involves more data.
In previously sensor based technique, tri-axial
accelerometer along with electromyogram (EMG) sensor
was used [5]. Due to cost of tri-axial accelerometer and
EMG, was not affordable by laymen. As the finale module
was also not much handy and recognized limited gestures,
made to design more handy and wide system. Our project
employs a similar kind of hand gloves with Flex sensor but
much more handy and can precisely determine many hand
gestures.
B. Proposed Solution
We kept a solution for above mentioned problem in three
phase i.e sensing phase, processing phase and output
phase. In sensing phase, Flex sensor senses the physical
characteristic and converts it into electrical signal which
passed to processing unit. The controller is used here is
Arduino Uno which gives an digital output in form of text
displayed on LCD and in form of audio played through a
speaker.
Figure 1.1 Block diagram for proposed solution
.
C. Organisation
The next session describes about the proposed solution. It
explains a feasible solution, can implement using
hardware. The third section provides the various hardware
and ICs used in the project. A brief explanation of software
implementation is elaborated in section 3.2. The fourth
section discusses the result which is obtained. The last
section is deals with conclusion along with the strength,
limitation and future scope.
II. PROPOSED SOLUTION
Mute people use hand sign to convey the message to
other. A glove fitted with flex sensor is used to translate
the signs made by the person into speech. The gloves is
continuously in operating mode whenever, a particular
gesture pattern is made by user, an equivalent electrical
signals are given by the sensor. These signals are passed to
analog i/p ports of Arduino Uno controller. For 32 different
gestures, signals are different. A range of 10-bit ADC values
are assigned for each gesture. The corresponding word is
stored in sd card memory. The role of controller is
comparing the received signals with stored values and
displaying the corresponding word on LCD. The
corresponding word is also played through speaker. The
block diagram of proposed solution is shown in fig 2.1
Figure 2.1 Block diagram
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Digital Glove For Mute People
Abhijit A. Kathwate, Prof.C.Y.Patil
Instrumentation and Control Dept.
jeetkathwate@gmail.com, cypatil@gmail.com
2. III. HARDWARE IMPLEMENTATION
A. Gloves
Any kind of cotton glove can be used for the purpose of
our project. A special kind of nylon gloves would be better
as they increase the easiness of movement of fingers.
B. Flex Sensor
Flex sensors are attached to the glove by using needle
and thread. It requires 5-volt input and output between 0
and 5 V, the resistivity varies with the sensor’s angle of
bend and the voltage output changes accordingly. The
device can activate the sensors from sleep mode, enables
them to power down when not in use and greatly
decreasing power consumption. It will only change
resistance in one direction. An unflexed sensor has a
resistance of about 10 kilo ohms. As the flex sensor is bent,
the resistance increases to 18- 25 kilo ohms at 90 degrees.
The sensor measures 0.25 inch wide, 4.5 inches long and
0.18 inches thick[1].
Figure 3.1 Flex sensor
C. Arduino Uno
The reason behind selecting Arduino uno as controller:
The Arduino Uno is a microcontroller board based on
ATmega328. It has 14 digital input/output pins, out of
which 6 can be used as PWM outputs, 6 analog inputs, a 16
MHz ceramic resonator, a reset button. It contains
everything needed to support the microcontroller, can
simply connected with a USB power cable with a AC-to-DC
adapter or battery for power source. The LCD, SD card and
a speaker can easily interfaces with Arduino Uno. Since the
size of Arduino Uno is small, makes the circuit more
compatible for user to handle.
D. SD Card
While interfacing SD card with Arduino Uno, following
connections need to be done [8]. Connect GND to ground,
3.3v to 3.3v, CLK to Pin 13 on your Arduino, MISO to pin
12, MISI to pin 11, and CS to pin 10. You can use a different
pin, as long as you have to remember to change the pin in
SD.begin().
Figure 3.2 Schematic of SD card interfacing
E. Speaker
The project accesses a series of .WAV files on an SD Card
and plays them according to input gesture when pin 9 of
the Uno is pulled high ( as speaker is directly triggered
using LM386 ). We tried to play 31 different .WAV files [9]
using Arduino TMRpcm.h library.
Figure 3.3 Speaker Interfacing using LM386
IV. SOFTWARE IMPLEMENTATION
A. Algorithm
The device is powered up through 5V and hand gesture
is fetched by user. Signals are generated and ADC
conversion is started, controller is made to wait till
conversion gets over. This process is continued till
maximum accuracy achieved by system. The generated
ADC values define the angle to which the joint are bent
like straight or 90 degree bending. Thus a series of new
digital values, either digital 1 or digital 0 obtained which
compared with previously stored values. This enables the
device in both static and dynamic hand gesture recognition
in the form of text visualized on LCD and audio played
through a speaker. The flowchart of the algorithm is
shown in figure 4.1
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3. V. RESULTS
The values of ADC without tuning the 5 Flex sensors are
obtained are mapped with logic 0 and logic 1 is shown in
following table:
Logic 0 ADC values less than count of -200
Logic 1 ADC values greater than count of -200
Table 5.1 Mapping of ADC values
Since the output voltage is taken across the
potentiometer, when the resistance of the sensor
increases, the voltage drop across potentiometer
increases. Hence the ADC value should increase
accordingly, resulting shifting to positive count. Observing
the table 5.2, the logic values are shown with respect to
each word with each finger.
Table 5.2 Configuration of OUTPUT
Sr
No
Words Thum
b
Fore Middle Ring Sm
all
1 Well Done 0 0 0 0 0
2 Miss You 0 0 0 0 1
3 Love You 0 0 0 1 0
4 Sad 0 0 0 1 1
5 Happy 0 0 1 0 0
6 Run 0 0 1 0 1
7 Keep Quit 0 0 1 1 0
8 Stop 0 0 1 1 1
9 Start 0 1 0 0 0
10 Ready 0 1 0 0 1
11 Take Care 0 1 0 1 0
12 Gn 0 1 0 1 1
13 Good
Morning
0 1 1 0 0
14 All The
Best
0 1 1 0 1
15 Congrat 0 1 1 1 0
16 Beautiful 0 1 1 1 1
17 Bye 1 0 0 0 0
18 Help 1 0 0 0 1
19 Thank You 1 0 0 1 0
20 Fine 1 0 0 1 1
21 No 1 0 1 0 0
22 Yes 1 0 1 0 1
23 Good 1 0 1 1 0
24 Bad 1 0 1 1 1
25 Welcome 1 1 0 0 0
26 Go 1 1 0 0 1
27 Nice 1 1 0 1 0
28 Up 1 1 0 1 1
29 Down 1 1 1 0 0
30 Sorry 1 1 1 0 1
31 Hello 1 1 1 1 0
Few pictures of project are shown in Figure 5.1. Figure
5.1a shows the tuning of a digital glove with LED. As there
is a bending of Flex sensor, logic 0 is assigned to LED,
resulting LED gets off and reverse action occurred when
Flex sensor remains unfetched.
Figure 5.1a Tuning with LED
Figure 5.1b shows LCD module of the project and also
the PCB of the same is been created.
Figure 5.1b LCD module
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4. VI. CONCLUSION
This digital glove is a handy module which facilitates easy
communication for mute/deaf people with everyone. This
module communicates exactly as designed version in the
form of words/phrases. These phrases are heard as voice
and can also be read on the LCD16*2. This module does
not impose any extra effort for the knowledge of any
technical details for its use. This module built a foundation
of a more robust base and portable module to
communicate as sentences.
A. Advantages
The cost of final module is quit affordable i.e. costing just
7000 INR. The power consumption of the module is very
low, measuring the precisely the movements of finger.
Since the gesture is translated into both voice and text, a
conversion can be held between anyone even in between
a mute and deaf or in between a blind and mute.
B. Limitations
This module only works with words/phrases, does not
communicate in the form of sentences. The device
performs quit slowly as compared with normal speaking
people. This module is only dedicated for those people
who knows configuration of words with gestures. Few
standard gestures are slightly differs causes
misinterpretation.
C. Future Scope
Implementation of a digital glove for both hands will
expand the library of words that can be used for
communication. Addition of camera in the system can port
facial expression in the more appropriate meaning of
words. Noise reduction can be improved using noise
removal technique.
ACKNOWLEDGEMENT
We would like to thank ''Adhar Muk Badhir Vidyalaya,
Pune'' for providing an information related to deaf mute
people. This information is related with different
commands which we targeted it as output with respect to
different gestures. We would also like to thank HOD
INSTRU, COEP for providing us space and lab facility. We
would like to thank our mentor Prof Dr.C Y Patil.
REFERENCES
[1] Saggio, Giovanni. "Bend sensor arrays for hand movement
tracking in biomedical systems." In Advances in Sensors and
Interfaces (IWASI), 2011 4th IEEE International Workshop on, pp.
51-54. IEEE, 2011
[2] Tanyawiwat, Netchanok, and Surapa Thiemjarus. "Design of
an assistive communication glove using combined sensory
channels." In Wearable and Implantable Body Sensor Networks
(BSN), 2012 Ninth International Conference on, pp. 34-39. IEEE,
2012.
[3]Dipietro, Laura, Angelo M. Sabatini, and Paolo Dario. "A survey
of glove-based systems and their applications." Systems, Man,
and Cybernetics, Part C: Applications and Reviews, IEEE
Transactions on 38, no. 4 (2008): 461-482
[4]Praveenkumar S Havalagi, Shruthi Urf Nivedita.”The amazing
digital gloves that give voice to voiceless.”International journal of
advance in engineering and technology(March
2013),vol.6,issue.1,pp 471-480.
[5]Masaguppi, Shruti C., and D. R. Ambika. "Virtual Talk for Deaf,
Mute, Blind and Normal Humans." in India Educators'
Conference (TIIEC), 2013 Texas Instruments, pp. 316-320. IEEE,
2013.
[6]Delliraj, M., and S. Vijayakumar. "Design of Smart e-Tongue for
the physically challenged people." in Recent Trends in
Information Technology (ICRTIT), 2013 International Conference
on, pp. 306-311. IEEE, 2013.
[7]Prapat Parab, Sanika Kinalekar, Rohit Chavan, Deep Sharan,
Shubhadha Deshpande."Hand Gesture Recognition using
Microcontroller & Flex Sensor." in International Journal Of
Scientific Research And Education , pp. 518-522. March 2014.
[8] http://arduino.cc/en/Reference/SD
[9] http://playground.arduino.cc/SmartWAV/SmartWAV
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