TALKING GLOVE FOR MUTE PEOPLE

A glove is designed to recognize hand gestures of mute people and convert them into corresponding audio. The hand gestures of the mute people are recorded through a glove which the mute person wears. The glove contains flex sensors which generate electrical signals. The electrical signals are f

Project Title

TALKING GLOVE FOR MUTE PEOPLE

Project Area of Specialization

Wearables and Implantable

Project Summary

A glove is designed to recognize hand gestures of mute people and convert them into corresponding audio. The hand gestures of the mute people are recorded through a glove which the mute person wears. The glove contains flex sensors which generate electrical signals. The electrical signals are forwarded to Raspberry pi. The Raspberry pi processes the signals and computes features such as bend angles and hand positions. An Artificial Intelligence (AI) network is trained on bend angles and hand positions by coding in Python and then the trained model is burnt into the Raspberry pi. The Raspberry pi receives test signals from the glove, computes features and classifies the signals into corresponding sound category. Pakistan Sign Language (PSL) is used in this project because every country has its own sign language with specific meaning. The hand gestures of PSL recognized are time, price, water, sleep, fine and what. It is a step towards reducing gap between speech impaired people and society. The speech impaired people with this wearable glove will no longer be considered an inferior part of the society.

Project Objectives

The objectives of this project are:

• To design a glove that recognizes hand gestures of mute people
• To convert the hand gestures of mute people into corresponding audio signals
• To overcome communication gap between mute people and society

Project Implementation Method

The proposed system consists of three main steps. In the first step input signals are recorded using sensors such as flex sensors which are placed on each finger of the hand. The sensors measure the bend angle of the fingers as they are made up of variable resistors, whose resistance varies with respect to fingers bending. With increase in the bend, the resistance also increases. An MPU6050 unit is used, which is a complete 6-axis Motion Tracking Device. It combines 3-axis Gyroscope, 3-axis Accelerometer fixed on the back of palm of the hand.  Accelerometer measures the tri axial orientation of the fingers and gyroscope measures the yaw, pitch and roll. In the second step the values (electrical signals) received through above sensors are given to Python, where an Artificial Intelligence model is trained and then burnt into Raspberry pi. The Raspberry pi receives the test signals from the hand of mute person via glove and using the Artificial Intelligence model classifies the hand gesture into one of the category mentioned above. In the third step, an audio signal is generated corresponding to the gesture category recognized by the Raspberry Pi.

Benefits of the Project

With Taking Glove the Mute People will  face no difficulty to communicate with others. Infact they will be able to talk again via talking glove. The Glove can be used to encourage and understanding of Pakistan Sign language and the mute people will no longer be consider as an inferior part of  the society.

Technical Details of Final Deliverable

1. Glove
   1. Five Flex Sensors
      1. 3xflex sensors each of 4.5 inches and two flex sensor of 2.2 inches
   2. 1xAccelerometer and Gyroscope unit
2. 1xRaspberry Pi 3B+
3. 1xPower Bank unit of rating
   1. Output Voltage 5v
   2. Maximum output current 2A
4. 1xBluetooth Speaker module
   1. Up to 10 m

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Telecommunication

Other Industries

Medical

Core Technology

Wearables and Implantables

Other Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Good Health and Well-Being for People, Industry, Innovation and Infrastructure

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com