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Belkhiria C, Boudir A, Hurter C, Peysakhovich V. EOG-Based Human-Computer Interface: 2000-2020 Review. SENSORS (BASEL, SWITZERLAND) 2022; 22:4914. [PMID: 35808414 PMCID: PMC9269776 DOI: 10.3390/s22134914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 06/23/2022] [Accepted: 06/25/2022] [Indexed: 11/28/2022]
Abstract
Electro-oculography (EOG)-based brain-computer interface (BCI) is a relevant technology influencing physical medicine, daily life, gaming and even the aeronautics field. EOG-based BCI systems record activity related to users' intention, perception and motor decisions. It converts the bio-physiological signals into commands for external hardware, and it executes the operation expected by the user through the output device. EOG signal is used for identifying and classifying eye movements through active or passive interaction. Both types of interaction have the potential for controlling the output device by performing the user's communication with the environment. In the aeronautical field, investigations of EOG-BCI systems are being explored as a relevant tool to replace the manual command and as a communicative tool dedicated to accelerating the user's intention. This paper reviews the last two decades of EOG-based BCI studies and provides a structured design space with a large set of representative papers. Our purpose is to introduce the existing BCI systems based on EOG signals and to inspire the design of new ones. First, we highlight the basic components of EOG-based BCI studies, including EOG signal acquisition, EOG device particularity, extracted features, translation algorithms, and interaction commands. Second, we provide an overview of EOG-based BCI applications in the real and virtual environment along with the aeronautical application. We conclude with a discussion of the actual limits of EOG devices regarding existing systems. Finally, we provide suggestions to gain insight for future design inquiries.
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Affiliation(s)
- Chama Belkhiria
- ISAE-SUPAERO, Université de Toulouse, 31400 Toulouse, France;
| | - Atlal Boudir
- ENAC, Université de Toulouse, 31400 Toulouse, France; (A.B.); (C.H.)
| | - Christophe Hurter
- ENAC, Université de Toulouse, 31400 Toulouse, France; (A.B.); (C.H.)
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Jiménez E, Ordóñez F. A Pilot Study of the Psychosocial Impact of Low-Cost Assistive Technology for Sexual Functioning in People with Acquired Brain Injury. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:3765. [PMID: 33916565 PMCID: PMC8038503 DOI: 10.3390/ijerph18073765] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Revised: 04/01/2021] [Accepted: 04/02/2021] [Indexed: 11/17/2022]
Abstract
People with acquired brain injury (ABI) face limitations when performing activities of daily living, including sexuality. Despite the common use among this group of assistive technology to compensate for or neutralize the limitations deriving from their condition, there is very little literature on outcome measures in assistive technology for sexual functioning. The aim of this study was to explore the psychosocial impact of the use of low-cost assistive technology in people with ABI. The sample was made up of 18 users: 15 men and 3 women diagnosed with ABI. The PLISSIT model was used, as well as the Psychosocial Impact of Assistive Device Scale-PIADS as an assessment tool. Three types of low-cost assistive technology were developed: seat cushions, bed equipment, and back supports. All three types of AT obtained positive scores on the PIADS total scale and its three subscales: competence, adaptability, and self-esteem. Although the results of this study are positive, more research into outcome measures for products to improve sexual functioning in people with ABI is required.
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Affiliation(s)
- Estíbaliz Jiménez
- Facultad Padre Ossó, Universidad de Oviedo, 33003 Oviedo, Asturias, Spain;
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3
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Golparvar AJ, Yapici MK. Toward graphene textiles in wearable eye tracking systems for human-machine interaction. BEILSTEIN JOURNAL OF NANOTECHNOLOGY 2021; 12:180-189. [PMID: 33614384 PMCID: PMC7884882 DOI: 10.3762/bjnano.12.14] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Accepted: 01/20/2021] [Indexed: 05/05/2023]
Abstract
The study of eye movements and the measurement of the resulting biopotential, referred to as electrooculography (EOG), may find increasing use in applications within the domain of activity recognition, context awareness, mobile human-computer and human-machine interaction (HCI/HMI), and personal medical devices; provided that, seamless sensing of eye activity and processing thereof is achieved by a truly wearable, low-cost, and accessible technology. The present study demonstrates an alternative to the bulky and expensive camera-based eye tracking systems and reports the development of a graphene textile-based personal assistive device for the first time. This self-contained wearable prototype comprises a headband with soft graphene textile electrodes that overcome the limitations of conventional "wet" electrodes, along with miniaturized, portable readout electronics with real-time signal processing capability that can stream data to a remote device over Bluetooth. The potential of graphene textiles in wearable eye tracking and eye-operated remote object interaction is demonstrated by controlling a mouse cursor on screen for typing with a virtual keyboard and enabling navigation of a four-wheeled robot in a maze, all utilizing five different eye motions initiated with a single channel EOG acquisition. Typing speeds of up to six characters per minute without prediction algorithms and guidance of the robot in a maze with four 180° turns were successfully achieved with perfect pattern detection accuracies of 100% and 98%, respectively.
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Affiliation(s)
- Ata Jedari Golparvar
- Faculty of Engineering and Natural Sciences, Sabanci University, TR-34956 Istanbul, Turkey
| | - Murat Kaya Yapici
- Faculty of Engineering and Natural Sciences, Sabanci University, TR-34956 Istanbul, Turkey
- Sabanci University SUNUM Nanotechnology Research Center, TR-34956 Istanbul, Turkey
- Department of Electrical Engineering, University of Washington, Seattle, WA 98195, USA
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Hosni SM, Shedeed HA, Mabrouk MS, Tolba MF. EEG-EOG based Virtual Keyboard: Toward Hybrid Brain Computer Interface. Neuroinformatics 2020; 17:323-341. [PMID: 30368637 DOI: 10.1007/s12021-018-9402-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Abstract
The past twenty years have ignited a new spark in the research of Electroencephalogram (EEG), which was pursued to develop innovative Brain Computer Interfaces (BCIs) in order to help severely disabled people live a better life with a high degree of independence. Current BCIs are more theoretical than practical and are suffering from numerous challenges. New trends of research propose combining EEG to other simple and efficient bioelectric inputs such as Electro-oculography (EOG) resulting from eye movements, to produce more practical and robust Hybrid Brain Computer Interface systems (hBCI) or Brain/Neuronal Computer Interface (BNCI). Working towards this purpose, existing research in EOG based Human Computer Interaction (HCI) applications, must be organized and surveyed in order to develop a vision on the potential benefits of combining both input modalities and give rise to new designs that maximize these benefits. Our aim is to support and inspire the design of new hBCI systems based on both EEG and EOG signals, in doing so; first the current EOG based HCI systems were surveyed with a particular focus on EOG based systems for communication using virtual keyboard. Then, a survey of the current EEG-EOG virtual keyboard was performed highlighting the design protocols employed. We concluded with a discussion of the potential advantages of combining both systems with recommendations to give deep insight for future design issues for all EEG-EOG hBCI systems. Finally, a general architecture was proposed for a new EEG-EOG hBCI system. The proposed hybrid system completely alters the traditional view of the eye movement features present in EEG signal as artifacts that should be removed; instead EOG traces are extracted from EEG in our proposed hybrid architecture and are considered as an additional input modality sharing control according to the chosen design protocol.
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Affiliation(s)
- Sarah M Hosni
- Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt
| | - Howida A Shedeed
- Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt
| | - Mai S Mabrouk
- Biomedical Engineering Department, Misr University for Science and Technology, Giza, Egypt.
| | - Mohamed F Tolba
- Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt
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SITbench 1.0: A Novel Switch-Based Interaction Technique Benchmark. JOURNAL OF HEALTHCARE ENGINEERING 2019; 2019:5075163. [PMID: 31531218 PMCID: PMC6721442 DOI: 10.1155/2019/5075163] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 07/15/2019] [Indexed: 11/17/2022]
Abstract
Evaluation process of a switch-based interaction technique (SIT) requires an interdisciplinary team effort and takes a considerable amount of time. Collecting subjective evaluation data from the users is a very common approach, but the subjective evaluation data alone might be manipulated and unreliable for comparing performances in many cases. Thus, therapists generally cannot succeed in determining the optimum SIT setup (i.e., determining the most appropriate combination of setup variables such as the switch type or switch site) at first attempts since it is hard to evaluate the measurable performance by collecting subjective data instead of objective data. Inevitably, each unsuccessful attempt to reach the optimum SIT setup results in a loss of serious time and effort. On the contrary, a benchmark application is also required to make performance evaluation of SITs by using a number of standard tests and empirical attributes. It is obvious that a quicker and more accurate SIT evaluation process provides a better cost and schedule management considering the increasing number of SIT users in the world. Therefore, we propose a novel benchmark for performance evaluation called SITbench that provides a quicker and more accurate switch evaluation process by collecting and saving the objective data automatically. We conducted a user study with eight participants and demonstrated that the objective data collected via the SITbench helped to determine the optimum SIT setup accurately. Result of a questionnaire applied to evaluate the SITbench itself was also satisfactory. SITbench is expected to help researchers and therapists to make a better evaluation according to any change done in SIT setup variables (switch type, activation method, etc.) with the aim of reaching the optimum SIT setup, which leads to a better cost and schedule management. As the first benchmark application compatible with all SITs, which can emulate keyboard characters or mouse clicks, it can be utilized by assistive technology professionals to make comparisons and evaluations automatically via standardized tests.
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Choudhari AM, Porwal P, Jonnalagedda V, Mériaudeau F. An Electrooculography based Human Machine Interface for wheelchair control. Biocybern Biomed Eng 2019. [DOI: 10.1016/j.bbe.2019.04.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Chang WD. Electrooculograms for Human-Computer Interaction: A Review. SENSORS 2019; 19:s19122690. [PMID: 31207949 PMCID: PMC6630230 DOI: 10.3390/s19122690] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Revised: 06/10/2019] [Accepted: 06/12/2019] [Indexed: 12/14/2022]
Abstract
Eye movements generate electric signals, which a user can employ to control his/her environment and communicate with others. This paper presents a review of previous studies on such electric signals, that is, electrooculograms (EOGs), from the perspective of human–computer interaction (HCI). EOGs represent one of the easiest means to estimate eye movements by using a low-cost device, and have been often considered and utilized for HCI applications, such as to facilitate typing on a virtual keyboard, moving a mouse, or controlling a wheelchair. The objective of this study is to summarize the experimental procedures of previous studies and provide a guide for researchers interested in this field. In this work the basic characteristics of EOGs, associated measurements, and signal processing and pattern recognition algorithms are briefly reviewed, and various applications reported in the existing literature are listed. It is expected that EOGs will be a useful source of communication in virtual reality environments, and can act as a valuable communication tools for people with amyotrophic lateral sclerosis.
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Affiliation(s)
- Won-Du Chang
- School of Electronic and Biomedical Engineering, Tongmyong University, Busan 48520, Korea.
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Bio-potentials for smart control applications. HEALTH AND TECHNOLOGY 2019. [DOI: 10.1007/s12553-019-00314-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Usakli AB, Gurkan S, Gurkan G, Kaya A. A novel EOG-based wireless rapid communication device for people with motor neuron diseases. J Med Eng Technol 2018; 42:420-425. [PMID: 30465704 DOI: 10.1080/03091902.2018.1531947] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
In this study, a new electrooculography (EOG) based system that provides efficient communication for people suffered from motor neuron diseases is presented. The system consists of two distinct devices. The first device operates as a main unit that is activated by the subject's eye movements. This unit is capable of transmitting 10 different command/state messages. These messages enable subject to choose his/her situation such as "I'm fine", "I feel bad", "I'm hungry" and "I'm thirsty". Commands such as "Come", "Go". The number of messages can be increased. The main unit acquires the EOG signal from the subject. Newly developed analogue and digital signal conditioning interprets the eye movements as specific messages and transmits them to the second unit (receiver) using radio frequency transmitter. The messages related to the subject's demands and situation can be heard from both main and receiver unit speakers. The wireless receiver unit is capable of notifying the patient's command by auditory and visual indicators. The realised device was tested by 2 healthy and 2 ALS patients and confirmed to be successful with 100% performance for sending correct messages.
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Affiliation(s)
- Ali Bulent Usakli
- a Department of Mechatronics Engineering , KTO Karatay University , Konya , Turkey
| | - Serkan Gurkan
- b Department of Electrical and Electronics , The NCO Academy , Balikesir , Turkey
| | - Guray Gurkan
- c Department of Electronics Engineering , Istanbul Kültür University , Istanbul , Turkey
| | - Alper Kaya
- d Board member at ALS MNH Association , Izmir , Turkey
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Soltani S, Mahnam A. A practical efficient human computer interface based on saccadic eye movements for people with disabilities. Comput Biol Med 2016; 70:163-173. [PMID: 26848728 DOI: 10.1016/j.compbiomed.2016.01.012] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2015] [Revised: 12/15/2015] [Accepted: 01/16/2016] [Indexed: 11/19/2022]
Abstract
Human computer interfaces (HCI) provide new channels of communication for people with severe motor disabilities to state their needs, and control their environment. Some HCI systems are based on eye movements detected from the electrooculogram. In this study, a wearable HCI, which implements a novel adaptive algorithm for detection of saccadic eye movements in eight directions, was developed, considering the limitations that people with disabilities have. The adaptive algorithm eliminated the need for calibration of the system for different users and in different environments. A two-stage typing environment and a simple game for training people with disabilities to work with the system were also developed. Performance of the system was evaluated in experiments with the typing environment performed by six participants without disabilities. The average accuracy of the system in detecting eye movements and blinking was 82.9% at first tries with an average typing rate of 4.5cpm. However an experienced user could achieve 96% accuracy and 7.2cpm typing rate. Moreover, the functionality of the system for people with movement disabilities was evaluated by performing experiments with the game environment. Six people with tetraplegia and significant levels of speech impairment played with the computer game several times. The average success rate in performing the necessary eye movements was 61.5%, which increased significantly with practice up to 83% for one participant. The developed system is 2.6×4.5cm in size and weighs only 15g, assuring high level of comfort for the users.
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Affiliation(s)
- Sima Soltani
- Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Hezar Jirib Ave, Isfahan, Iran.
| | - Amin Mahnam
- Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Hezar Jirib Ave, Isfahan, Iran.
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Real-Time Control of a Video Game Using Eye Movements and Two Temporal EEG Sensors. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2015; 2015:653639. [PMID: 26690500 PMCID: PMC4672363 DOI: 10.1155/2015/653639] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/18/2015] [Revised: 07/09/2015] [Accepted: 07/30/2015] [Indexed: 11/18/2022]
Abstract
EEG-controlled gaming applications range widely from strictly medical to completely nonmedical applications. Games can provide not only entertainment but also strong motivation for practicing, thereby achieving better control with rehabilitation system. In this paper we present real-time control of video game with eye movements for asynchronous and noninvasive communication system using two temporal EEG sensors. We used wavelets to detect the instance of eye movement and time-series characteristics to distinguish between six classes of eye movement. A control interface was developed to test the proposed algorithm in real-time experiments with opened and closed eyes. Using visual feedback, a mean classification accuracy of 77.3% was obtained for control with six commands. And a mean classification accuracy of 80.2% was obtained using auditory feedback for control with five commands. The algorithm was then applied for controlling direction and speed of character movement in two-dimensional video game. Results showed that the proposed algorithm had an efficient response speed and timing with a bit rate of 30 bits/min, demonstrating its efficacy and robustness in real-time control.
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12
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Quadcopter flight control using a low-cost hybrid interface with EEG-based classification and eye tracking. Comput Biol Med 2014; 51:82-92. [DOI: 10.1016/j.compbiomed.2014.04.020] [Citation(s) in RCA: 77] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2014] [Revised: 04/27/2014] [Accepted: 04/29/2014] [Indexed: 11/20/2022]
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Affine transform to reform pixel coordinates of EOG signals for controlling robot manipulators using gaze motions. SENSORS 2014; 14:10107-23. [PMID: 24919013 PMCID: PMC4118336 DOI: 10.3390/s140610107] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2014] [Revised: 05/21/2014] [Accepted: 06/04/2014] [Indexed: 11/16/2022]
Abstract
Biosignals will play an important role in building communication between machines and humans. One of the types of biosignals that is widely used in neuroscience are electrooculography (EOG) signals. An EOG has a linear relationship with eye movement displacement. Experiments were performed to construct a gaze motion tracking method indicated by robot manipulator movements. Three operators looked at 24 target points displayed on a monitor that was 40 cm in front of them. Two channels (Ch1 and Ch2) produced EOG signals for every single eye movement. These signals were converted to pixel units by using the linear relationship between EOG signals and gaze motion distances. The conversion outcomes were actual pixel locations. An affine transform method is proposed to determine the shift of actual pixels to target pixels. This method consisted of sequences of five geometry processes, which are translation-1, rotation, translation-2, shear and dilatation. The accuracy was approximately 0.86° ± 0.67° in the horizontal direction and 0.54° ± 0.34° in the vertical. This system successfully tracked the gaze motions not only in direction, but also in distance. Using this system, three operators could operate a robot manipulator to point at some targets. This result shows that the method is reliable in building communication between humans and machines using EOGs.
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Wang H, Li Y, Long J, Yu T, Gu Z. An asynchronous wheelchair control by hybrid EEG-EOG brain-computer interface. Cogn Neurodyn 2014; 8:399-409. [PMID: 25206933 DOI: 10.1007/s11571-014-9296-y] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2013] [Revised: 04/22/2014] [Accepted: 05/02/2014] [Indexed: 10/25/2022] Open
Abstract
Wheelchair control requires multiple degrees of freedom and fast intention detection, which makes electroencephalography (EEG)-based wheelchair control a big challenge. In our previous study, we have achieved direction (turning left and right) and speed (acceleration and deceleration) control of a wheelchair using a hybrid brain-computer interface (BCI) combining motor imagery and P300 potentials. In this paper, we proposed hybrid EEG-EOG BCI, which combines motor imagery, P300 potentials, and eye blinking to implement forward, backward, and stop control of a wheelchair. By performing relevant activities, users (e.g., those with amyotrophic lateral sclerosis and locked-in syndrome) can navigate the wheelchair with seven steering behaviors. Experimental results on four healthy subjects not only demonstrate the efficiency and robustness of our brain-controlled wheelchair system but also indicate that all the four subjects could control the wheelchair spontaneously and efficiently without any other assistance (e.g., an automatic navigation system).
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Affiliation(s)
- Hongtao Wang
- School of Automation Science and Engineering, South China University of Technology, Guangzhou, 510640 China ; School of Information Engineering, Wuyi University, Jiangmen, 529020 China ; Engineering Research Center for Massive Biometric Information Processing, Jiangmen, Guangdong Province China
| | - Yuanqing Li
- School of Automation Science and Engineering, South China University of Technology, Guangzhou, 510640 China
| | - Jinyi Long
- School of Automation Science and Engineering, South China University of Technology, Guangzhou, 510640 China
| | - Tianyou Yu
- School of Automation Science and Engineering, South China University of Technology, Guangzhou, 510640 China
| | - Zhenghui Gu
- School of Automation Science and Engineering, South China University of Technology, Guangzhou, 510640 China
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16
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Hara K, Ohta K, Miyajima M, Hara M, Iino H, Matsuda A, Watanabe S, Matsushima E, Maehara T, Matsuura M. Mismatch negativity for speech sounds in temporal lobe epilepsy. Epilepsy Behav 2012; 23:335-41. [PMID: 22377331 DOI: 10.1016/j.yebeh.2012.01.019] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2011] [Revised: 01/15/2012] [Accepted: 01/17/2012] [Indexed: 11/18/2022]
Abstract
The mismatch negativity (MMN) is an electrophysiological trace of change detection, measured by electroencephalography (EEG), and is a reliable marker for pre-attentive auditory sensory memory. We used a phonetic oddball paradigm in patients with temporal lobe epilepsy (TLE) to elicit the MMN response at fronto-central sites and the mismatch positivity (MMP) response at mastoid sites. The MMN in 26 patients was compared with that of 26 age- and gender-matched healthy control participants. Electroencephalography responses were recorded during the presentation of speech sounds: the vowels 'a' and 'o' in alternation. Average waveforms were obtained for standard and deviant trials. We found that the MMP response at bilateral mastoid sites was reduced, whereas the MMN response at fronto-central sites did not change significantly. These results support the view that the MMN is generated by separable sources in the frontal and temporal lobes and that these sources are differentially affected by TLE.
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Affiliation(s)
- Keiko Hara
- Department of Life Sciences and Biofunctional Informatics, Graduate School of Health Care Sciences, Tokyo Medical and Dental University, Bunkyo-ku, Tokyo, Japan.
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Usakli AB, Susac A, Gurkan S. Fast face recognition: eye blink as a reliable behavioral response. Neurosci Lett 2011; 504:49-52. [PMID: 21911038 DOI: 10.1016/j.neulet.2011.08.055] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2011] [Revised: 08/24/2011] [Accepted: 08/25/2011] [Indexed: 11/17/2022]
Abstract
To investigate how quickly we can recognize faces, we used the onset of eye blinking as a behavioral response. The mean reaction time for the blink response was 188±38ms which was 80ms faster than the motor response. As expected, the subjects were more correct and faster to distinguish between faces and houses than when responding to particular face emotion and identity. Our results suggested that early visual processing before 150ms is very important in face processing. This corroborates previous reports from EEG/MEG studies and intracranial recordings on the face-related response around 100ms after stimulus onset. Our findings indicated that blinking can be used as a fast and reliable behavioral response.
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Affiliation(s)
- Ali Bulent Usakli
- Department of Technical Sciences, The NCO Academy, Balikesir, Turkey
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Pinheiro CG, Naves ELM, Pino P, Losson E, Andrade AO, Bourhis G. Alternative communication systems for people with severe motor disabilities: a survey. Biomed Eng Online 2011; 10:31. [PMID: 21507236 PMCID: PMC3103465 DOI: 10.1186/1475-925x-10-31] [Citation(s) in RCA: 52] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2010] [Accepted: 04/20/2011] [Indexed: 11/10/2022] Open
Abstract
We have now sufficient evidence that using electrical biosignals in the field of Alternative and Augmented Communication is feasible. Additionally, they are particularly suitable in the case of people with severe motor impairment, e.g. people with high-level spinal cord injury or with locked-up syndrome. Developing solutions for them implies that we find ways to use sensors that fit the user's needs and limitations, which in turn impacts the specifications of the system translating the user's intentions into commands. After devising solutions for a given user or profile, the system should be evaluated with an appropriate method, allowing a comparison with other solutions. This paper submits a review of the way three bioelectrical signals--electromyographic, electrooculographic and electroencephalographic--have been utilised in alternative communication with patients suffering severe motor restrictions. It also offers a comparative study of the various methods applied to measure the performance of AAC systems.
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Affiliation(s)
- Carlos G Pinheiro
- Laboratoire d'Automatique humaine et de Sciences Comportementales, Université de Metz, Bâtiment ISEA, 7 rue Marconi, 57070 METZ Technopôle, France.
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Lancioni GE, Singh NN, O'Reilly MF, Sigafoos J, Green V, Oliva D, Lang R. Microswitch and keyboard-emulator technology to facilitate the writing performance of persons with extensive motor disabilities. RESEARCH IN DEVELOPMENTAL DISABILITIES 2011; 32:576-582. [PMID: 21227637 DOI: 10.1016/j.ridd.2010.12.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2010] [Accepted: 12/14/2010] [Indexed: 05/30/2023]
Abstract
This study assessed the effectiveness of microswitches for simple responses (i.e., partial hand closure, vocalization, and hand stroking) and a keyboard emulator to facilitate the writing performance of three participants with extensive motor disabilities. The study was carried out according to an ABAB design. During the A phases, the participants (one child and two adults) were to write using the responses and technology available to them prior to this study. During the B phases, they used the new responses and technology. Data showed that two of the three participants had a faster writing performance during the B phases while the third participant had a slower writing performance. All three participants indicated a clear preference for the use of the new responses and technology, which were considered relatively easy and comfortable to manage and did not seem to cause any specific signs of tiredness. Implications of the findings are discussed.
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Affiliation(s)
- Giulio E Lancioni
- Department of Psychology, University of Bari, Via Quintino Sella 268, 70100 Bari, Italy.
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Itakura N, Sakamoto K. A new method for calculating eye movement displacement from AC coupled electro-oculographic signals in head mounted eye–gaze input interfaces. Biomed Signal Process Control 2010. [DOI: 10.1016/j.bspc.2009.12.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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