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EOG-Based Human–Computer Interface: 2000–2020 Review. SENSORS 2022; 22:s22134914. [PMID: 35808414 PMCID: PMC9269776 DOI: 10.3390/s22134914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [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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Design of a Wearable Eye-Movement Detection System Based on Electrooculography Signals and Its Experimental Validation. BIOSENSORS-BASEL 2021; 11:bios11090343. [PMID: 34562933 PMCID: PMC8471050 DOI: 10.3390/bios11090343] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 09/10/2021] [Accepted: 09/14/2021] [Indexed: 11/16/2022]
Abstract
In the assistive research area, human-computer interface (HCI) technology is used to help people with disabilities by conveying their intentions and thoughts to the outside world. Many HCI systems based on eye movement have been proposed to assist people with disabilities. However, due to the complexity of the necessary algorithms and the difficulty of hardware implementation, there are few general-purpose designs that consider practicality and stability in real life. Therefore, to solve these limitations and problems, an HCI system based on electrooculography (EOG) is proposed in this study. The proposed classification algorithm provides eye-state detection, including the fixation, saccade, and blinking states. Moreover, this algorithm can distinguish among ten kinds of saccade movements (i.e., up, down, left, right, farther left, farther right, up-left, down-left, up-right, and down-right). In addition, we developed an HCI system based on an eye-movement classification algorithm. This system provides an eye-dialing interface that can be used to improve the lives of people with disabilities. The results illustrate the good performance of the proposed classification algorithm. Moreover, the EOG-based system, which can detect ten different eye-movement features, can be utilized in real-life applications.
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Tang Z, Kong N, Zhang X, Liu Y, Hu P, Mou S, Liljeström P, Shi J, Tan W, Kim JS, Cao Y, Langer R, Leong KW, Farokhzad OC, Tao W. A materials-science perspective on tackling COVID-19. NATURE REVIEWS. MATERIALS 2020; 5:847-860. [PMID: 33078077 PMCID: PMC7556605 DOI: 10.1038/s41578-020-00247-y] [Citation(s) in RCA: 191] [Impact Index Per Article: 47.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 09/14/2020] [Indexed: 05/08/2023]
Abstract
The ongoing SARS-CoV-2 pandemic highlights the importance of materials science in providing tools and technologies for antiviral research and treatment development. In this Review, we discuss previous efforts in materials science in developing imaging systems and microfluidic devices for the in-depth and real-time investigation of viral structures and transmission, as well as material platforms for the detection of viruses and the delivery of antiviral drugs and vaccines. We highlight the contribution of materials science to the manufacturing of personal protective equipment and to the design of simple, accurate and low-cost virus-detection devices. We then investigate future possibilities of materials science in antiviral research and treatment development, examining the role of materials in antiviral-drug design, including the importance of synthetic material platforms for organoids and organs-on-a-chip, in drug delivery and vaccination, and for the production of medical equipment. Materials-science-based technologies not only contribute to the ongoing SARS-CoV-2 research efforts but can also provide platforms and tools for the understanding, protection, detection and treatment of future viral diseases.
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Affiliation(s)
- Zhongmin Tang
- Center for Nanomedicine and Department of Anesthesiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Na Kong
- Center for Nanomedicine and Department of Anesthesiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Xingcai Zhang
- School of Engineering and Applied Sciences, Harvard University, Cambridge, MA USA
| | - Yuan Liu
- Center for Nanomedicine and Department of Anesthesiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Ping Hu
- State Key Laboratory of High Performance Ceramics and Superfine Microstructure, Shanghai Institute of Ceramics, Chinese Academy of Sciences, Shanghai, China
| | - Shan Mou
- Institute of Molecular Medicine (IMM), Renji Hospital, State Key Laboratory of Oncogenes and Related Genes, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Peter Liljeström
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden
| | - Jianlin Shi
- State Key Laboratory of High Performance Ceramics and Superfine Microstructure, Shanghai Institute of Ceramics, Chinese Academy of Sciences, Shanghai, China
| | - Weihong Tan
- Institute of Molecular Medicine (IMM), Renji Hospital, State Key Laboratory of Oncogenes and Related Genes, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Molecular Science and Biomedicine Laboratory (MBL), State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, College of Biology, Aptamer Engineering Center of Hunan Province, Hunan University, Changsha, China
- The Cancer Hospital of the University of Chinese Academy of Sciences, Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, China
| | | | - Yihai Cao
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden
| | - Robert Langer
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA USA
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA USA
| | - Kam W. Leong
- Department of Biomedical Engineering, Columbia University, New York, NY USA
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY USA
| | - Omid C. Farokhzad
- Center for Nanomedicine and Department of Anesthesiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Wei Tao
- Center for Nanomedicine and Department of Anesthesiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
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Borghetti D, Bruni A, Fabbrini M, Murri L, Sartucci F. A low-cost interface for control of computer functions by means of eye movements. Comput Biol Med 2007; 37:1765-70. [PMID: 17601527 DOI: 10.1016/j.compbiomed.2007.05.003] [Citation(s) in RCA: 31] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2006] [Revised: 05/21/2007] [Accepted: 05/23/2007] [Indexed: 10/23/2022]
Abstract
Human-computer interactions (HCI) have become an important area of research and development in computer science and psychology. Appropriate use of computers could be of primary importance for communication and education of those subjects which could not move, speak, see or hear properly. The aim of our study was to develop a reliable, low-cost and easy-to-use HCI based on electrooculography signal analysis, to allow physically impaired patients to control a computer as assisted communication. Twenty healthy subjects served as volunteers: eye movements were captured by means of four electrodes and a two-channel amplifier. The output signal was then transmitted to an "Analog to Digital" (AD) converter, which digitized the signal of the amplifier at a rate of 500 Hz, before being sent to a laptop. We designed and coded a specific software, which analyzed the input signal to give an interpretation of eye movements. By means of a single ocular movement (up, down, left and right) the subjects were then able to move a cursor over a screen keyboard, passing from one letter to another; a double eye blink was then necessary to select and write the active letter. After a brief training session, all the subjects were able to confidently control the cursor and write words using only ocular movements and blinking. For each subject we presented three series of randomized words: mean time required to enter a single character was about 8.5s, while input errors were very limited (less than 1 per 250 characters). Our results confirm those obtained in previous studies: eye-movement interface can be used to properly control computer functions and to assist communication of movement-impaired patients.
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Affiliation(s)
- D Borghetti
- Department of Neuroscience, Clinical Neurology, Pisa University School of Medicine, Pisa, Italy.
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