Neuro-Controlled Wheelchair with Integrated Voice Communication Support

Individuals suffering from quadriplegia, spinal cord injuries, Amyotrophic Lateral Sclerosis (ALS), or severe paralysis often retain full cognitive function but lose the ability to control their limbs, making conventional joystick-based wheelchairs unusable for them. This paper proposes a Neuro-Controlled Wheelchair with Integrated Voice Communication Support that uses a non-invasive EEG headset to capture the user's brain signals and translate them into wheelchair movement commands such as forward, backward, left, right, and stop. A microcontroller processes the classified EEG commands and drives the motor unit through a motor driver circuit, while an integrated voice communication module allows the user to select pre-recorded or text-to-speech phrases to convey basic needs to caregivers without relying on manual speech or limb movement. The system is designed as a low-cost, non-invasive, and reproducible assistive device that combines mobility and communication support, offering improved independence compared with existing mobility-only assistive wheelchairs.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-03
DOI
https://doi.org/10.5281/zenodo.23908728
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Neuro-Controlled Wheelchair with Integrated Voice Communication Support

Prof. S. J. Pardeshi, Prof. Vivekanand Gund, Vaibhav Dantkale
Zenodo (CERN European Organization for Nuclear Research)
EEG and Brain-Computer Interfaces
article

Neuro-Controlled Wheelchair with Integrated Voice Communication Support

Prof. S. J. Pardeshi, Prof. Vivekanand Gund, Vaibhav Dantkale
article en

Abstract

Individuals suffering from quadriplegia, spinal cord injuries, Amyotrophic Lateral Sclerosis (ALS), or severe paralysis often retain full cognitive function but lose the ability to control their limbs, making conventional joystick-based wheelchairs unusable for them. This paper proposes a Neuro-Controlled Wheelchair with Integrated Voice Communication Support that uses a non-invasive EEG headset to capture the user's brain signals and translate them into wheelchair movement commands such as forward, backward, left, right, and stop. A microcontroller processes the classified EEG commands and drives the motor unit through a motor driver circuit, while an integrated voice communication module allows the user to select pre-recorded or text-to-speech phrases to convey basic needs to caregivers without relying on manual speech or limb movement. The system is designed as a low-cost, non-invasive, and reproducible assistive device that combines mobility and communication support, offering improved independence compared with existing mobility-only assistive wheelchairs.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 16%
EEG and Brain-Computer Interfaces
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon
Neuro-Controlled Wheelchair with Integrated Voice Communication Support — Prof. S. J. Pardeshi, Prof. Vivekanand Gund, et al. · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS