Hand Gesture Controlled Wheelchair

The integration of advanced technologies into assistive devices has the potential to significantly enhance the quality of life for individuals with mobility impairments. This paper presents the design and implementation of an automatic gesture-controlled wheelchair, leveraging the MPU 6050 sensor and ESPvroom32 microcontroller. The system is intended to provide a more intuitive and accessible mode of wheelchair control through hand gestures, facilitated by a glove-mounted MPU 6050 sensor. The MPU 6050, a six-axis motion tracking device, is used to detect hand gestures, which are interpreted by an ESPvroom32 microcontroller. These gestures are then transmitted wirelessly to a second ESPvroom32 unit located on the wheelchair, which interprets the commands and drives the motors via an L298N motor driver. In addition to gesture control, the system incorporates obstacle detection using OpenCV, a computer vision library. A camera mounted on the wheelchair captures real-time video, which is processed to detect obstacles. The proposed system is designed to offer an affordable, user-friendly, and efficient solution for individuals with mobility impairments, enabling them to navigate their. environment more independently and safely

Authors

Publication Details

Published
2024-12-20
DOI
https://doi.org/10.1109/icaiqsa64000.2024.10882335
Citations
1
Primary Topic
Gaze Tracking and Assistive Technology
Type
article
Field-Weighted Citation Impact
0.37
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Hand Gesture Controlled Wheelchair

Neelam Chandolikar, Pradeep Borkar, Atharva Bondarde, Ninad Bodade et al.
1 citations
Gaze Tracking and Assistive Technology
0.37
article

Hand Gesture Controlled Wheelchair

Neelam Chandolikar, Pradeep Borkar, Atharva Bondarde, Ninad Bodade, Vaishnavi Bornar, Dhanashree Borkar, Shripad Borbande
article en
1 citations

Abstract

The integration of advanced technologies into assistive devices has the potential to significantly enhance the quality of life for individuals with mobility impairments. This paper presents the design and implementation of an automatic gesture-controlled wheelchair, leveraging the MPU 6050 sensor and ESPvroom32 microcontroller. The system is intended to provide a more intuitive and accessible mode of wheelchair control through hand gestures, facilitated by a glove-mounted MPU 6050 sensor. The MPU 6050, a six-axis motion tracking device, is used to detect hand gestures, which are interpreted by an ESPvroom32 microcontroller. These gestures are then transmitted wirelessly to a second ESPvroom32 unit located on the wheelchair, which interprets the commands and drives the motors via an L298N motor driver. In addition to gesture control, the system incorporates obstacle detection using OpenCV, a computer vision library. A camera mounted on the wheelchair captures real-time video, which is processed to detect obstacles. The proposed system is designed to offer an affordable, user-friendly, and efficient solution for individuals with mobility impairments, enabling them to navigate their. environment more independently and safely

Openalex Percentile: Top 34%
Gaze Tracking and Assistive Technology
0.37
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.