TY - GEN
T1 - An Application of Head Gesture For Controlling Electric Wheelchair Movement
AU - Somawirata, I. Komang
AU - Utaminingrum, Fitri
AU - Tibyani, Tibyani
AU - Adinugroho, Sigit
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/11/9
Y1 - 2023/11/9
N2 - Technology is being utilized by everyone in the age of globalization to perform or complete routine tasks that are vital for survival. However, some parts of the human population are unable to carry out daily activities due to a lack or inability to move the body's locomotors, such as the hands and feet. Smart wheelchairs that can accept input using only eye movements combined with facial landmark methods have been the focus of previous research. Regrettably, it did no longer produce the predicted level of accuracy considering previous research only focused on the eye area, which does no longer take into consideration the opportunity of disabled humans having abnormalities in the eye area as well. As a result, this lookup used to be carried out by making use of head movement whilst nonetheless being integrated with facial landmarks, and based totally on the distance of the head and camera on the wheelchair to be able to direct and manipulate the clever wheelchair in order for it to be used properly. The focal point of this find out about was on managing head actions as inputs to direct the wheelchair closer to four directions, such as Turn left, turn right, straight forward, and stopping, with the integration of minimum (30 cm), fantastic (30-40 Cm), and maximum (50-60) distances in the experiment. This study generates a fairly exceptional stage of accuracy at a distance of 30-40 cm, ensuing in an increasingly extraordinary accuracy rate of 98%.
AB - Technology is being utilized by everyone in the age of globalization to perform or complete routine tasks that are vital for survival. However, some parts of the human population are unable to carry out daily activities due to a lack or inability to move the body's locomotors, such as the hands and feet. Smart wheelchairs that can accept input using only eye movements combined with facial landmark methods have been the focus of previous research. Regrettably, it did no longer produce the predicted level of accuracy considering previous research only focused on the eye area, which does no longer take into consideration the opportunity of disabled humans having abnormalities in the eye area as well. As a result, this lookup used to be carried out by making use of head movement whilst nonetheless being integrated with facial landmarks, and based totally on the distance of the head and camera on the wheelchair to be able to direct and manipulate the clever wheelchair in order for it to be used properly. The focal point of this find out about was on managing head actions as inputs to direct the wheelchair closer to four directions, such as Turn left, turn right, straight forward, and stopping, with the integration of minimum (30 cm), fantastic (30-40 Cm), and maximum (50-60) distances in the experiment. This study generates a fairly exceptional stage of accuracy at a distance of 30-40 cm, ensuing in an increasingly extraordinary accuracy rate of 98%.
KW - face detection
KW - face landmark
KW - smart wheelchair
UR - https://www.scopus.com/pages/publications/85192793637
U2 - 10.1145/3637684.3637686
DO - 10.1145/3637684.3637686
M3 - Conference contribution
AN - SCOPUS:85192793637
T3 - ACM International Conference Proceeding Series
SP - 7
EP - 11
BT - DMIP 2023 - Proceedings of the 2023 6th International Conference on Digital Medicine and Image Processing
PB - Association for Computing Machinery
T2 - 6th International Conference on Digital Medicine and Image Processing, DMIP 2023
Y2 - 9 November 2023 through 12 November 2023
ER -