Work

Real-time Eeg-based Wheelchair Control System for Enhancing Mobility

Year: 2025

Type: dissertation

Abstract: This thesis proposes a real-time wheelchair-driving system using electroencephalography (EEG) signals via a non-invasive Brain-Computer Interface (BCI). Designed for individuals with mobility impairments, the system interprets brain activity to execute commands like “start,” “stop,” “turn left,” and “turn right.” EEG signals are processed in MATLAB and classified using a Support Vector Machine (SVM) for accurate command recognition. The commands are transmitted via UDP to an Arduino controller, which directs motor actions. This integration of EEG processing, machine learning, and embedded control offers a practical assistive solution, enhancing user autonomy through thought-driven mobility.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15413701

Author: Bagmare, Pratik Sanatan

Language: English

Topic: EEG and Brain-Computer Interfaces

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: green

OpenAlex ID: W6930786690

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