The Experts below are selected from a list of 3012 Experts worldwide ranked by ideXlab platform

Smitha Kavallur Pisharath Gopi - One of the best experts on this subject based on the ideXlab platform.

  • low cost wireless Electrooculography speller
    Systems Man and Cybernetics, 2018
    Co-Authors: Hoi Ka Hou, Smitha Kavallur Pisharath Gopi
    Abstract:

    While communication is an innate ability to most of us, individuals with severe motor disability such as amyotrophic lateral sclerosis (ALS) have difficulty in daily communication. Nowadays, with the help of human-computer interface (HCI), they can communicate using bio-signal which can be measured from the human body and monitored. Electrooculography (EOG) is one type of bio-signal, it can be measured as the electrical potential difference generated by eye movement. This project aims to develop a low-cost wireless EOG based speller. The EOG signal acquisition used 5 surface electrodes, which captures horizontal and vertical eye movement. A low cost wireless EOG signal acquisition circuit was designed and implemented. A real-time EOG classifying algorithm was developed on the Arduino to classify up to 10 different types of eye movement. This classified information is transmitted wirelessly to a virtual keyboard ona computer. A self-design keyboard was developed by placing the most frequently used alphabets closer initial point to increase the efficiency of the speller. A test was conducted on eight subjects to compare the accuracy and efficiency of the proposed low cost wireless EOG speller. The proposed system was able to outperform most of the spellers reported in literature by providing an average accuracy of 89 % and speed of 6.48 lpm.

  • SMC - Low-Cost Wireless Electrooculography Speller
    2018 IEEE International Conference on Systems Man and Cybernetics (SMC), 2018
    Co-Authors: Hoi Ka Hou, Smitha Kavallur Pisharath Gopi
    Abstract:

    While communication is an innate ability to most of us, individuals with severe motor disability such as amyotrophic lateral sclerosis (ALS) have difficulty in daily communication. Nowadays, with the help of human-computer interface (HCI), they can communicate using bio-signal which can be measured from the human body and monitored. Electrooculography (EOG) is one type of bio-signal, it can be measured as the electrical potential difference generated by eye movement. This project aims to develop a low-cost wireless EOG based speller. The EOG signal acquisition used 5 surface electrodes, which captures horizontal and vertical eye movement. A low cost wireless EOG signal acquisition circuit was designed and implemented. A real-time EOG classifying algorithm was developed on the Arduino to classify up to 10 different types of eye movement. This classified information is transmitted wirelessly to a virtual keyboard ona computer. A self-design keyboard was developed by placing the most frequently used alphabets closer initial point to increase the efficiency of the speller. A test was conducted on eight subjects to compare the accuracy and efficiency of the proposed low cost wireless EOG speller. The proposed system was able to outperform most of the spellers reported in literature by providing an average accuracy of 89 % and speed of 6.48 lpm.

W.s. Newman - One of the best experts on this subject based on the ideXlab platform.

  • A human-robot interface based on Electrooculography
    IEEE International Conference on Robotics and Automation 2004. Proceedings. ICRA '04. 2004, 2004
    Co-Authors: W.s. Newman
    Abstract:

    Design and implementation of an Electrooculography based gaze-controlled robotic system is presented. The robot system consists of signal acquisition, pattern recognition, control strategy and robot motion modules. The user's eye gaze movements are reconstructed from electrooculogram (EOG) signals, which are recorded from the face in real time. The eye movement patterns, e.g., saccades, fixation and blinks are detected from the raw eye gaze movement data by a pattern recognition module. The control strategy module interprets the user's intention from the eye movement patterns based on predefined protocols. A horizontally mounted robot, emulating the skeletomuscular configuration of the human arm, is controlled by the robot motion control module to execute the interpreted user intention. The performance results of two control strategies are discussed.

  • ICRA - A human-robot interface based on Electrooculography
    IEEE International Conference on Robotics and Automation 2004. Proceedings. ICRA '04. 2004, 2004
    Co-Authors: Yingxi Chen, W.s. Newman
    Abstract:

    Design and implementation of an Electrooculography based gaze-controlled robotic system is presented. The robot system consists of signal acquisition, pattern recognition, control strategy and robot motion modules. The user's eye gaze movements are reconstructed from electrooculogram (EOG) signals, which are recorded from the face in real time. The eye movement patterns, e.g., saccades, fixation and blinks are detected from the raw eye gaze movement data by a pattern recognition module. The control strategy module interprets the user's intention from the eye movement patterns based on predefined protocols. A horizontally mounted robot, emulating the skeletomuscular configuration of the human arm, is controlled by the robot motion control module to execute the interpreted user intention. The performance results of two control strategies are discussed.

Jiawun Siao - One of the best experts on this subject based on the ideXlab platform.

  • eyeglasses based Electrooculography human wheelchair interface
    Systems Man and Cybernetics, 2009
    Co-Authors: Chunghsien Kuo, Yichang Chan, Hungchyun Chou, Jiawun Siao
    Abstract:

    This paper describes an Electrooculography (EOG) based human-wheelchair interface for wheelchair users. A pair of electrodes which measures the eye-gaze direction of users is desired as wheelchair manipulation commands. In addition to EOG based wheelchair manipulations, this paper also introduces ultrasonic arrays for detecting distances to actively avoid collisions. In order to simplify setup procedures of using this system, two electrodes are mounted on two side arms of eyeglasses respectively that are possible to have tight contacts with skins around eyes. Therefore, wheelchair movements are capable of following eye-gaze directions. On the other hand, an analog biopotential signal amplifier and a laptop computer are used to develop the proposed EOG based human-wheelchair interface controller. Finally, experimental results demonstrate the operations of EOG based human-wheelchair interface.

  • SMC - Eyeglasses based Electrooculography human-wheelchair interface
    2009 IEEE International Conference on Systems Man and Cybernetics, 2009
    Co-Authors: Chunghsien Kuo, Yichang Chan, Hungchyun Chou, Jiawun Siao
    Abstract:

    This paper describes an Electrooculography (EOG) based human-wheelchair interface for wheelchair users. A pair of electrodes which measures the eye-gaze direction of users is desired as wheelchair manipulation commands. In addition to EOG based wheelchair manipulations, this paper also introduces ultrasonic arrays for detecting distances to actively avoid collisions. In order to simplify setup procedures of using this system, two electrodes are mounted on two side arms of eyeglasses respectively that are possible to have tight contacts with skins around eyes. Therefore, wheelchair movements are capable of following eye-gaze directions. On the other hand, an analog biopotential signal amplifier and a laptop computer are used to develop the proposed EOG based human-wheelchair interface controller. Finally, experimental results demonstrate the operations of EOG based human-wheelchair interface.

Zhengping Wei - One of the best experts on this subject based on the ideXlab platform.

  • online vigilance analysis based on Electrooculography
    International Joint Conference on Neural Network, 2012
    Co-Authors: Zhengping Wei
    Abstract:

    This study provides a highly efficient online method for vigilance analysis and verifies this theory in some experiments. Compared with electroencephalogram (EEG) signals, Electrooculography (EOG) signals are easier to collect and faster to process. Some research has proven relations between vigilance and EOG features like blink features and slow eye movement (SEM). This study uses 48 kind of features of eye blinks, SEM and rapid eye movement (REM) from horizontal and vertical channels of EOG signals. It is verified by experiments that the precision of this method is higher than other methods which uses single kind of features like eye blinks. This study also implements an online vigilance analysis method and its precision is close to the offline method after about one minute from the beginning of collecting signals. With the application of dry electrode amplifiers, this algorithm is useful in real-time vigilance estimation in practical environment. This method can be an important part of brain-machine interfaces.

  • IJCNN - Online vigilance analysis based on Electrooculography
    The 2012 International Joint Conference on Neural Networks (IJCNN), 2012
    Co-Authors: Zhengping Wei
    Abstract:

    This study provides a highly efficient online method for vigilance analysis and verifies this theory in some experiments. Compared with electroencephalogram (EEG) signals, Electrooculography (EOG) signals are easier to collect and faster to process. Some research has proven relations between vigilance and EOG features like blink features and slow eye movement (SEM). This study uses 48 kind of features of eye blinks, SEM and rapid eye movement (REM) from horizontal and vertical channels of EOG signals. It is verified by experiments that the precision of this method is higher than other methods which uses single kind of features like eye blinks. This study also implements an online vigilance analysis method and its precision is close to the offline method after about one minute from the beginning of collecting signals. With the application of dry electrode amplifiers, this algorithm is useful in real-time vigilance estimation in practical environment. This method can be an important part of brain-machine interfaces.

Hoi Ka Hou - One of the best experts on this subject based on the ideXlab platform.

  • low cost wireless Electrooculography speller
    Systems Man and Cybernetics, 2018
    Co-Authors: Hoi Ka Hou, Smitha Kavallur Pisharath Gopi
    Abstract:

    While communication is an innate ability to most of us, individuals with severe motor disability such as amyotrophic lateral sclerosis (ALS) have difficulty in daily communication. Nowadays, with the help of human-computer interface (HCI), they can communicate using bio-signal which can be measured from the human body and monitored. Electrooculography (EOG) is one type of bio-signal, it can be measured as the electrical potential difference generated by eye movement. This project aims to develop a low-cost wireless EOG based speller. The EOG signal acquisition used 5 surface electrodes, which captures horizontal and vertical eye movement. A low cost wireless EOG signal acquisition circuit was designed and implemented. A real-time EOG classifying algorithm was developed on the Arduino to classify up to 10 different types of eye movement. This classified information is transmitted wirelessly to a virtual keyboard ona computer. A self-design keyboard was developed by placing the most frequently used alphabets closer initial point to increase the efficiency of the speller. A test was conducted on eight subjects to compare the accuracy and efficiency of the proposed low cost wireless EOG speller. The proposed system was able to outperform most of the spellers reported in literature by providing an average accuracy of 89 % and speed of 6.48 lpm.

  • SMC - Low-Cost Wireless Electrooculography Speller
    2018 IEEE International Conference on Systems Man and Cybernetics (SMC), 2018
    Co-Authors: Hoi Ka Hou, Smitha Kavallur Pisharath Gopi
    Abstract:

    While communication is an innate ability to most of us, individuals with severe motor disability such as amyotrophic lateral sclerosis (ALS) have difficulty in daily communication. Nowadays, with the help of human-computer interface (HCI), they can communicate using bio-signal which can be measured from the human body and monitored. Electrooculography (EOG) is one type of bio-signal, it can be measured as the electrical potential difference generated by eye movement. This project aims to develop a low-cost wireless EOG based speller. The EOG signal acquisition used 5 surface electrodes, which captures horizontal and vertical eye movement. A low cost wireless EOG signal acquisition circuit was designed and implemented. A real-time EOG classifying algorithm was developed on the Arduino to classify up to 10 different types of eye movement. This classified information is transmitted wirelessly to a virtual keyboard ona computer. A self-design keyboard was developed by placing the most frequently used alphabets closer initial point to increase the efficiency of the speller. A test was conducted on eight subjects to compare the accuracy and efficiency of the proposed low cost wireless EOG speller. The proposed system was able to outperform most of the spellers reported in literature by providing an average accuracy of 89 % and speed of 6.48 lpm.