Inspiration

Millions of people across the world suffer from various mobility impairments caused by Amyotrophic Lateral Sclerosis (ALS), brainstem stroke, brain or spinal cord injury, cerebral palsy, muscular dystrophies, multiple sclerosis, and many other diseases. A large portion of these people heavily rely upon wheelchairs to get on with their day to day activities. These people are dependent on others in order to move A large number of patients are not prescribed wheelchairs at all, either because they find it physically difficult to control the manual wheelchair. In our work with Brain Controlled Wheelchairs, we target a population who are—or will become—unable to use conventional interfaces, due to severe motor–disabilities

What it does

BrainHack Wheelchair is a Smart Wheelchair controlled with your Brain. It uses a Brainwave Reader to read your Brainwaves.

The Brainwaves are then decoded into the Android app into Attention, Meditation, Eye Blink Strength and Raw values.

The direction of the Wheelchair is then controlled with your Attention Level and Eye Blinks.

JUST FOCUS to move the robot FORWARD, and Blink your eyes twice to turn it LEFT !!

The Wheelchair is controlled with a Raspberry pi...

And it has a Camera too for live image processing !

How I built it

The mobile App contains the necessary libraries to process the incoming Brainwaves. The Headset measures our Attention Values on a scale of 0-100

When the attention of the subject reaches a predefined threshold, the Wheelchair starts moving forward

In Order to turn Right, the user blinks twice in a span of 1 second above a threshold of 100.

It uses a android phone camera for live video processing of its surroundings. The application uses Tensorflow Lite and Ojject Detection API to processs the video. It can detect multiple objects within an image, with bounding boxes. Recognizing 80 different classes of objects.

Accomplishments that I'm proud of

Finally completed the entire project

What I learned

How to Hack Brainwaves and decode them How to use Tensorflow efficiently How to make an android app

What's next for Brain Controlled Wheelchair with Tensorflow

Future possible implementation: Auto Pilot Mode - Think about a Destination such as Kitchen or Hall and it will get the user there in Autonomous Mode usiing Tensorflow Object Detection

Emergency Braking System - If user abruptly closes his eyes sensing some danger, then the Wheelchair will stop

Staircase Climbing Mode - To assist the elderly to help climb the stairs uImage Processing

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