Parkinson Disease

Android Application Demo (Pls wait the gif takes time to load)

To detect if the person has Parkinson's disease and make the process easy

Study the dataset and build a model to classify the drawings of a healthy and affected person

Once we take the input which is the shapes drawn by the user then the model will classify the shapes according to the previous data and give output as result

Use the training dataset to make prediction and help patient for further diagnosis.

We take input from the user the shapes he draws on paper in the form of image.

We use Convolutional Neural Network from kearas library of tensorflow to read and process data and and convert it to model to predict result to analyse

We classify if the person has Parkinson disease or not on the model we have trained on the dataset

The Tensorflow Model is Converted to Tensorflow Lite Model and Used in Android App

TensorFlow Lite is comprised of a runtime on which you can run pre-existing models, and a suite of tools that you can use to prepare your models for use on mobile and embedded devices.

It’s presently supported on Android and iOS via a C++ API, as well as having a Java Wrapper for Android Developers.

Additionally, on Android Devices that support it, the interpreter can also use the Android Neural Networks API for hardware acceleration, otherwise it will default to the CPU for execution.