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Author

Anwar Al-Haddad

Bio: Anwar Al-Haddad is an academic researcher from Universiti Teknologi Malaysia. The author has contributed to research in topics: Wheelchair & Eye tracking. The author has an hindex of 5, co-authored 5 publications receiving 73 citations.

Papers
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Proceedings ArticleDOI
20 Sep 2011
TL;DR: This work proposes new method beside the classic method, to control the motorized wheelchair using EOG signals, which allows the user to look around freely while the wheelchair navigates automatically to the desired goal point.
Abstract: In this work, we propose new method beside the classic method, to control the motorized wheelchair using EOG signals The new method allows the user to look around freely while the wheelchair navigates automatically to the desired goal point Only EOG signals are used to control the wheelchair, eye gazing and blinking The user can still choose to control the wheelchair using the classic manual method in case the environment and obstacles structure does not help with the auto navigation method In the new auto navigation method the micro controller can know the goal point direction and distance by calculating the gaze angle that the user is gazing at Gaze angle and blinks are measured and used as inputs for the controlling method Tangent Bug algorithm is used to navigate the wheelchair in Auto controlling method

28 citations

Proceedings ArticleDOI
08 Feb 2012
TL;DR: A new method beside the classic method, to control the motorized wheelchair using EOG signals, which allows the user to look around freely while the wheelchair navigates automatically to the desired goal point.
Abstract: In this paper, we propose new method beside the classic method, to control the motorized wheelchair using EOG signals. The new method allows the user to look around freely while the wheelchair navigates automatically to the desired goal point. Only EOG signals are used to control the wheelchair; eye gazing and blinking. The user can still choose to control the wheelchair using the classic manual method in case the environment and obstacles structure does not help with the auto navigation method. In the new auto navigation method the microcontroller can know the goal point direction and distance by calculating the gaze angle that the user is gazing at. PoingBug algorithm is used to navigate the wheelchair in Auto controlling method. Simulated results are similar to Tangent Bug algorithm results, but experimental tests are slightly improved in some cases where the surroundings have sharp edges.

18 citations

Proceedings ArticleDOI
12 Dec 2011
TL;DR: This work proposes new method beside the classic method, to control the motorized wheelchair using EOG signals, which allows the user to look around freely while the wheelchair navigates automatically to the desired goal point.
Abstract: In this work, we propose new method beside the classic method, to control the motorized wheelchair using EOG signals The new method allows the user to look around freely while the wheelchair navigates automatically to the desired goal point Only EOG signals are used to control the wheelchair, eye gazing and blinking The user can still choose to control the wheelchair using the classic manual method in case the environment and obstacles structure does not help with the auto navigation method In the new auto navigation method the micro controller can know the goal point direction and distance by calculating the gaze angle that the user is gazing at Tangent Bug algorithm is used to navigate the wheelchair in Auto controlling method Experimental results are similar to simulated with minimum error, due to minimal positioning and sensing errors

15 citations

Proceedings ArticleDOI
26 Jun 2012
TL;DR: This work proposes a new approach alongside the typical method, to control the motorized wheelchair using EOG signals, which grants the user to look around without restraint, while the wheelchair navigates automatically to the desired goal point.
Abstract: In the present study, we put forward a new approach together with the classic method, to direct the powered wheelchair by means of eye movements. At the same time as the wheelchair automatically travels towards the location of the desired destination, the user is granted to look around without restraints. Only Electro-Oclography (EOG) signals are used to guide the wheelchair; eye gazes and blinks. Switching between guiding methods; typical manual method and developed automatic method, can be done any time by the user. In the proposed guiding approach; by scheming the gaze angle of the wheelchair user, the control unit is able to obtain the desired point location; distance and direction. Bug algorithms are employed to guide the wheelchair in the automatic guiding approach. Two different Bug algorithms are utilized to navigate the wheelchair in the auto controlling method. A comparison is discussed between Bug2 and Tangent-Bug, algorithms. Experimental tests show slightly different results than theory, because the bug algorithms cannot continuously update the robot's position data in experiments.

10 citations

Proceedings ArticleDOI
01 Dec 2012
TL;DR: It was showed that the characteristics of EEG signal (beta wave) differ with respect to the type of visual stimuli assessment, as normal children generally have beta (β) wave (14 - 32 Hz).
Abstract: This paper presents the characteristics of Electroencephalography (EEG) signal based on sensory modulation of visual stimuli assessments. The visual stimuli consisted of two assessments which are Phase 1 (the study phase) and Phase 2 (the working memory phase). The aim of this visual stimulus is to investigate the responses of the brain activity while remembering the sequence of the pictures. Based on this stimulus responses, EEG signal was recorded and captured from four channel locations at F8, F7, F4, and F3. This paper illustrates the extraction of EEG signals from normal children to determine the pattern of signal acquired. The data was analyzed using Wavelet Transform (WT) as normal children generally have beta (β) wave (14 – 32 Hz). This study showed that the characteristics of EEG signal (beta wave) differ with respect to the type of visual stimuli assessment. As a result, Phase 2 had higher Direct Current (DC) value for all channels and the average beta wavelength for ten children was approximately 23.14 Hz.

6 citations


Cited by
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Journal ArticleDOI
TL;DR: A novel system that enables a person with motor disability to control a wheelchair via eye-gaze and to provide a continuous, real-time navigation in unknown environments is proposed.
Abstract: Thanks to advances in electric wheelchair design, persons with motor impairments due to diseases, such as amyotrophic lateral sclerosis (ALS), have tools to become more independent and mobile. However, an electric wheelchair generally requires considerable skill to learn how to use and operate. Moreover, some persons with motor disabilities cannot drive an electric wheelchair manually (even with a joystick), because they lack the physical ability to control their hand movement (such is the case with people with ALS). In this paper, we propose a novel system that enables a person with motor disability to control a wheelchair via eye-gaze and to provide a continuous, real-time navigation in unknown environments. The system comprises a Permobile M400 wheelchair, eye tracking glasses, a depth camera to capture the geometry of the ambient space, a set of ultrasound and infrared sensors to detect obstacles with low proximity that are out of the field of view for the depth camera, a laptop placed on a flexible mount for maximized comfort, and a safety off switch to turn off the system whenever needed. First, a novel algorithm is proposed to support continuous, real-time target identification, path planning, and navigation in unknown environments. Second, the system utilizes a novel N-cell grid-based graphical user interface that adapts to input/output interfaces specifications. Third, a calibration method for the eye tracking system is implemented to minimize the calibration overheads. A case study with a person with ALS is presented, and interesting findings are discussed. The participant showed improved performance in terms of calibration time, task completion time, and navigation speed for a navigation trips between office, dining room, and bedroom. Furthermore, debriefing the caregiver has also shown promising results: the participant enjoyed higher level of confidence driving the wheelchair and experienced no collisions through all the experiment.

105 citations

Journal ArticleDOI
TL;DR: An asynchronous wheelchair navigation system using a hybrid of EEG signal and EOG artifacts embedded in EEG signals is demonstrated where each participant successfully completed all tasks without collision while showing improvement in maneuvering ability over attempts.
Abstract: Asynchronous wheelchair navigation system using EEG signals and EOG artifacts.Horizontal gazes are observed at C3, C4 and eyelid positions at O2.The system is modeled as a finite state machine with three states for each mode.Total of six different directions move in forward and backward.Actual navigation tasks are performed and registered an average accuracy of 97.5%. In this study, an asynchronous wheelchair navigation system using a hybrid of EEG signal and EOG artifacts embedded in EEG signals is demonstrated. The EEG signals are recorded at three different locations on the scalp in the occipital and motor cortex regions. First, an EEG signal related to eyelid position is analyzed and used to determine whether the eyes are closed or open. If the eyes are closed, no wheelchair movement is allowed. If the eyes are open, EOG traces (artifacts) from two other EEG signals are examined to infer the gaze direction of the eyes. A sliding window is utilized to position important cues in the trace signals at the center of the window for effective classification. The variance of the EEG signal is used to determine the eyelid position by thresholding. Then, features extracted from the EOG traces are used as inputs to a pair of minimum distance classifiers whose outputs reveal the gaze shift performed by the eyes. The wheelchair navigation system is designed to move forward and backward in a total of six different directions. However, the number of distinct gaze direction that can be used as commands to move the wheelchair is only three. Therefore, we model the system as a finite state machine with three modes, each containing three states to overcome this deficiency. The system is equipped with proximity sensor to avoid collision with obstacles. A stop command is also available for safety measures. In a real-time experiment involving 20 participants, the system performed well as it registered a high accuracy of 97.88% with an average of computational time less than 1s. The system was also tested by five participants in a navigation experiment where each participant successfully completed all tasks without collision while showing improvement in maneuvering ability over attempts.

37 citations

Proceedings ArticleDOI
15 May 2016
TL;DR: The aim of this study is to analyse which electrode configuration could be best for medical applications by comparison of different electrode placements while showing the particularities of each one.
Abstract: The eye acts as a dipole between the cornea (positive potential) and the retina (negative potential) which causes an electric field around the eyeball. Therefore, when humans make saccadic eye movements, they generate signals relative to this potential called electrooculography (EOG) signals. These signals can be measured by placing electrodes near the eye. Different electrode configurations can be employed to acquire the EOG signals. The properties of these signals change depending on the number and placement of the electrodes. Therefore, this paper presents a comparative study of electrode placement used to measure EOG signals. In order to support this study a low-cost signal acquisition hardware was developed. It enables the comparison of different electrode placements while showing the particularities of each one. The aim of this study is to analyse which electrode configuration could be best for medical applications.

31 citations

Proceedings ArticleDOI
06 Nov 2012
TL;DR: The proposed intelligent HCI system can run in real-time and offers a natural and efficient interface for people with disability in their limbs to communicate with robots.
Abstract: This paper presents a novel hand gesture system for intelligent human-computer interaction (HCI) and its applications in medical assistance, e.g. intelligent wheelchair control. The hand gesture vocabulary in the system consists of five key hand postures and three compound states, and its design strategy covers the minimal hand motions, distraction detection and user-friendly design. The experiment results show that the designed lexicon is intuitive, ergonomic, and easy to be remembered and performed. The system is tested in both of the indoor and outdoor environments and shows the robustness to lighting change and users' errors. The proposed intelligent HCI system can run in real-time and offers a natural and efficient interface for people with disability in their limbs to communicate with robots.

30 citations

Journal ArticleDOI
TL;DR: A robust system that generates control command using only one type of asynchronous eye activity (voluntary eye blink) to navigate the wheelchair without a need of graphical user interface to provide a user-friendly, cost-effective and reliable HMI.

29 citations