TY  - CONF
AV  - none
SP  - 567
TI  - Application of Gesture Data Recognition in a Human-Interactive Leap Motion Sensor Chair
ID  - scholars15438
KW  - Bridge circuits; Controllers; Gesture recognition; Human computer interaction; Motion control; Wheels
KW  -  Activities of Daily Living; Activity of daily living; Adaptive manipulation; Arduino; Gestural interfaces; H-bridges; Leap motion controller; Motion controller; Motion sensors; Wheel chairs
KW  -  Wheelchairs
N1  - cited By 5; Conference of 2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021 ; Conference Date: 25 October 2021 Through 26 October 2021; Conference Code:176070
N2  - Gestural interface has been the subject of research for more than 40 years. The implementation of a novel intuitive and adaptive manipulation scheme is proposed by developing a human-machine communication interface between the Leap Motion controller and the wheel chair. In addition, an algorithm is developed to allow an optimum mapping between the user hand movement, tracked by the Leap Motion controller, and the wheel chair. The system should allow for a more natural human-computer interaction and a smooth manipulation of the wheel chair, by constantly adapting to the user hand tremor or shake. The sensor detects motions and moves the wheelchair accordingly. It will track the movement of the fingers and hands in order to identify the gesture, and then the motors will perform the required action using Arduino. The implementation would specially enhance the quality of living, especially for people with lower limb problems, and would support them in performing some of the essential Activities of Daily Living 'ADLs'. © 2021 IEEE.
PB  - Institute of Electrical and Electronics Engineers Inc.
SN  - 9781665416566
Y1  - 2021///
EP  - 571
A1  - Rasheed, K.
A1  - Saad, S.
A1  - Shahzad, L.
A1  - Ammad, S.
A1  - Ali, A.
A1  - Badshah, I.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124660406&doi=10.1109%2fICDABI53623.2021.9655819&partnerID=40&md5=9f41467ce9c18a6c622871e4ce5e9265
ER  -