SSVEP Based Wheelchair

Description:

The proposed project is significantly leveraging the lifestyle of the paralytic as well as the patients those are trapped in their body LOCKED-IN-SYNDROME). The subjective family lost hope on the patients and treatment could take enormous time. The severity of a case is also cast on global media. To improve the lifestyle of patients the project proposes a sincere solution. An SSVEP (Steady State Visually Evoked Potential) based wheelchair which has the capabilities to allow the patients to travel, to text, to control.

1. To travel: Patients can utilize the 3D plane of the surface using wheelchair & direction it.
2. To text: Patient can be connected to his old behaviour of being social.
3. To control: Controlling allows patients to access his native household appliances by just sitting on a wheelchair.

This project is not just a liability for the patient but cares as well. Studies say engaging Coma or Locked-in-syndrome patients in their maximum activities or communication they could escape their body jail as soon as possible.

Prerequisites:

1. Basics of Machine Learning
2. Knowledge of Support Vector Machine (SVM)
3. Numpy, Pandas, matplot-lib, scikit-learn libraries.
4. ssvepy library
5. Knowledge of Electromyogram (EMG) and Electroencephalogram (EEG)
6. MATLAB

svm -In machine learning, support vector machines (SVMs, also support vector networks) are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis. A Support Vector Machine (SVM) is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data (supervised learning), the algorithm outputs an optimal hyperplane which categorizes new examples.

Libraries:

ssvepy- A package to analyse MNE-formatted EEG data for steady-state visually evoked potentials (SSVEPs). In details

numpy - NumPy is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object and useful linear algebra, Fourier transform, and random number capabilities More details

pandas - pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with structured (tabular, multidimensional, potentially heterogeneous) and time series data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language. It is already well on its way toward this goal. More details

matplot-lib - Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack. One of the greatest benefits of visualization is that it allows us visual access to huge amounts of data in easily digestible visuals. Matplotlib consists of several plots like line, bar, scatter, histogram etc. In details

scikit-learn - Scikit-learn is probably the most useful library for machine learning in Python. It is on NumPy, SciPy and matplotlib, this library contains a lot of effiecient tools for machine learning and statistical modeling including classification, regression, clustering and dimensionality reduction. More details

Content URLs:

https://docs.google.com/presentation/d/1f5wT5ogvzdL7qsM5y3xUTle8zBdLL3zoe0aGPcci3OM/edit?usp=sharing

Speaker Info:

1. Abhishek Bhanushali is an undergrad student. He has contributed his work on MEAN stack and BCI enthusiasts. He worked on several projects on Brain Computer Interface (BCI) i.e. Electromyogram (EMG) and Electroencephalogram (EEG). He is also fond of AI & ML and made minor projects in this field. His vision is to promote BCI and want to bring this technology all over India.
2. Smit Jethva is an undergrad student of Computer Engineering student. He is highly interested in Machine Learning. He has developed a projects based on Python and Chatbots. He is also a back-end developer and Cloud Technology enthusiasts.

Speaker Links:

1. Smit Jethwa -> LinkedIn | Github
2. Abishek Bhanushali -> LinkedIn | Github