Page 169 - AI for Good Innovate for Impact

AI for Good Innovate for Impact

Use Case 24: Brain-wave driven wheelchair for paralysis patients

using EEG and ML� 4.1-Healthcare

Country: India

Organization: VIT Chennai

Contact Person(s):

Aaron David Don, aarondaviddon12@ gmail .com,
Joshua Banchamin, joshuabanchamin@ gmail .com,
Khoushal, khoushal2610@ gmail .com,
Pratyaksh Lodhi, pratyakshlodhi2@ gmail .com,
Dr. Suganya G, suganya.g@vit.ac.in,
Dr. Nithya Darisini P.S, psnithyadarisini@ vit .ac .in.

1 Use Case Summary Table

Item Details
Category Healthcare

Problem Addressed Patients with paralysis tend to be too dependent on others for
their mobility. Their dependence on a caretaker and their inability
to even carry out basic motor motions is a huge strain on their
loved ones financially and resource-wise. Moreover, this absolute
reliance on others is a huge drain on the mental health of the
patients, which in turn deters their chances of healing and living.
Our product is a wheelchair which helps paralysis patients move
around using just the power of their brain.
Key Aspects of Solution This project harnesses Electroencephalogram (EEG) and machine
learning technology to achieve this truly noble system. The EEG
is used to collect brainwave data from subjects. This data is
pre-processed and used to train an ML model, which classifies
a live stream of EEG data into various classes mapped to various
actions/motions, which is passed to a microprocessor, which in
turn actuates these signals by controlling the relevant actuators.
Technology Keywords EEG, machine learning, signal processing, ESP32, L298, Arduino,
Raspberry PI, Internet of Things (IOT).

Data Availability Private
Metadata (Type of Data) EEG-signals: Waves
Dataset to train ML model: Text

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