Head mouse control system for people with disabilities. Issue 1 (3rd April 2019)

• Record Type: Journal Article
• Authors: Abiyev, Rahib H.; Arslan, Murat
• Other Names: Elçi Atilla guestEditor.; Çelik Ertuğrul Duygu guestEditor.
• Is Part Of: Expert systems. Volume 37:Issue 1(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-04-03
• Subjects: computer vision -- convolutional neural network -- deep learning -- disabled people; Expert systems (Computer science); 006.33
• DOI: 10.1111/exsy.12398
• Languages: English
• ISSNs: 0266-4720

Abstract

Abstract: In this paper, a human–machine interface for disabled people with spinal cord injuries is proposed. The designed human–machine interface is an assistive system that uses head movements and blinking for mouse control. In the proposed system, by moving one's head, the user moves the mouse pointer to the required coordinates and then blinks to send commands. The considered head mouse control is based on image processing including facial recognition, in particular, the recognition of the eyes, mouth, and nose. The proposed recognition system is based on the convolutional neural network, which uses the low‐quality images that are captured by a computer's camera. The convolutional neural network (CNN) includes convolutional layers, a pooling layer, and a fully connected network. The CNN transforms the head movements to the actual coordinates of the mouse. The designed system allows people with disabilities to control a mouse pointer with head movements and to control mouse buttons with blinks. The results of the experiments demonstrate that this system is robust and accurate. This invention allows people with disabilities to freely control mouse cursors and mouse buttons without wearing any equipment.