Intelligent Wheelchair Control System based on Finger Pose Recognition
Abstract
In the old day, wheelchairs are moved manually
by using hand or with the assistance of someone else. Users of
this wheelchair get tired quickly if they have to walk long
distances. The electric wheelchair emerged as a form of
innovation and development for the manual wheelchair. This
paper presented the control system of the electric wheelchair
based on finger poses using the Convolutional Neural Network
(CNN). The camera is used to take pictures of five-finger poses.
Images are selected only in certain sections using Region of
Interest (ROI). The five-finger poses represent the movement of
the electric wheelchair to stop, right, left, forward, and
backward. The experimental results indicated that the accuracy
of the finger pose detection is about 93.6%. Therefore, the
control system using CNN can be a potential solution for an
electric wheelchair.
Collections
- LSP-Conference Proceeding [1876]