Real-time motorized electrical hospital bed control with eye-gaze tracking

Patients with motor neuron disease and most terminal patients cannot use their hands or arms, and so they need another person for their all needs. However, the mental functions and memories of such patients are generally sound, and they can control their eyes. Using an eye-gaze tracking technique, we have realized a real-time system for such patients. The system controls a motorized electrical hospital bed (EHB) by eye gaze with 4 degrees of freedom, using a low-cost webcam. Contactless systems that require calibration cannot be used for EHB control. The system developed in this work does not require any calibration process and it is contactless. These properties are the most innovative part of the proposed approach. To begin, the system detects the eye region and computes the iris centers. It then tracks the centers and moves a mouse pointer on a screen with the eye gaze. The specific movements of the mouse pointer are evaluated as position changing requests and the completed movements of the mouse pointer change the EHB position electrically. The communication between the computer and the EHB is provided by a relay control card driven by Arduino Mega. The system works under day/artificial lighting conditions successfully with or without eyeglasses. The system was tested with 30 volunteers on the EHB safely and was completed with 90% success (the exceptions being people with slanted eyes).

[1]  Ghazali Sulong,et al.  An Enhanced Iris Segmentation Algorithm Using Circle Hough Transform , 2012 .

[2]  M. Ross,et al.  Acquired motor neuron disorders. , 1997, Neurologic clinics.

[3]  F. Ungureanu,et al.  A SURVEY OF EYE TRACKING METHODS AND APPLICATIONS , 2014 .

[4]  Nesrin Aydin Atasoy,et al.  Detection of eye motion direction in real time video image , 2014, 2014 22nd Signal Processing and Communications Applications Conference (SIU).

[5]  John D. Fernandez,et al.  Facial feature detection using Haar classifiers , 2006 .

[6]  Paul A. Viola,et al.  Rapid object detection using a boosted cascade of simple features , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[7]  Cheng-Yi Yu,et al.  Modulated AIHT Image Contrast Enhancement Algorithm based on Contrast-Limited Adaptive Histogram Equalization , 2013 .

[8]  Yoav Freund,et al.  Experiments with a New Boosting Algorithm , 1996, ICML.

[9]  Guang-Zhong Yang,et al.  Eye tracking for skills assessment and training: a systematic review. , 2014, The Journal of surgical research.

[10]  Xing Chen,et al.  A new concentric circle detection method based on Hough transform , 2012, 2012 7th International Conference on Computer Science & Education (ICCSE).

[11]  Paul A. Viola,et al.  Robust Real-Time Face Detection , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[12]  Carlos Hitoshi Morimoto,et al.  Eye gaze tracking techniques for interactive applications , 2005, Comput. Vis. Image Underst..

[13]  D. Venkataraman,et al.  Eye movement based electronic wheel chair for physically challenged persons , 2014 .

[14]  Assit. Prof. Aree A. Mohammed,et al.  Efficient Eye Blink Detection Method for disabled- helping domain , 2014 .

[15]  Huchuan Lu,et al.  A novel method for gaze tracking by local pattern model and support vector regressor , 2010, Signal Process..

[16]  Hannes Fassold,et al.  Realtime KLT Feature Point Tracking for High Definition Video , 2009 .

[17]  Bart Wyns,et al.  Low cost eye tracking for human-machine interfacing , 2010 .

[18]  Leandro Schwarz,et al.  Pupil and iris detection in dynamic pupillometry using the OpenCV library , 2012, 2012 5th International Congress on Image and Signal Processing.

[19]  David Beymer,et al.  Eye gaze tracking using an active stereo head , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[20]  Ashok Kumar,et al.  Design of a Real Time System for Acquiring and Analyzing Iris Images in MATLAB , 2011 .

[21]  J. B. Brooke,et al.  SUS: A 'Quick and Dirty' Usability Scale , 1996 .

[22]  Ediz Polat,et al.  A video-based eye pupil detection system for diagnosing bipolar disorder , 2013 .

[23]  Carlos Hitoshi Morimoto,et al.  Pupil detection and tracking using multiple light sources , 2000, Image Vis. Comput..

[24]  Zhiwei Zhu,et al.  Novel Eye Gaze Tracking Techniques Under Natural Head Movement , 2007, IEEE Transactions on Biomedical Engineering.

[25]  Yakup Genc,et al.  GPU-based Video Feature Tracking And Matching , 2006 .

[26]  P. Beauseroy,et al.  Hough Transform and Active Contour for Enhanced Iris Segmentation , 2012 .

[27]  P. Jonathon Phillips,et al.  Improvements in Video-based Automated System for Iris Recognition (VASIR) , 2009, 2009 Workshop on Motion and Video Computing (WMVC).

[28]  ík,et al.  DETECTION OF DETERMINED EYE FEATURES IN DIGITAL IMAGE , 2011 .

[29]  Musa Mohd Mokji,et al.  Upper Body Tracking Using KLT and Kalman Filter , 2012, INNS-WC.

[30]  M. Yamada,et al.  Eye word processor (EWP) and peripheral controller for the ALS patient , 1987 .

[31]  Metin Yildiz.  A new coding technique for EOG based writing systems , 2011, 2011 IEEE 19th Signal Processing and Communications Applications Conference (SIU).