Challenges and Future Perspectives on Electroencephalogram-Based Biometrics in Person Recognition
The emergence of the digital world has greatly increased the number of accounts and passwords that users must remember. It has also increased the need for secure access to personal information in the cloud. Biometrics is one approach to person recognition, which can be used in identification as well...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2018-10-01
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| Series: | Frontiers in Neuroinformatics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fninf.2018.00066/full |
| _version_ | 1818320031004491776 |
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| author | Hui-Ling Chan Po-Chih Kuo Chia-Yi Cheng Yong-Sheng Chen Yong-Sheng Chen Yong-Sheng Chen |
| author_facet | Hui-Ling Chan Po-Chih Kuo Chia-Yi Cheng Yong-Sheng Chen Yong-Sheng Chen Yong-Sheng Chen |
| author_sort | Hui-Ling Chan |
| collection | DOAJ |
| description | The emergence of the digital world has greatly increased the number of accounts and passwords that users must remember. It has also increased the need for secure access to personal information in the cloud. Biometrics is one approach to person recognition, which can be used in identification as well as authentication. Among the various modalities that have been developed, electroencephalography (EEG)-based biometrics features unparalleled universality, distinctiveness and collectability, while minimizing the risk of circumvention. However, commercializing EEG-based person recognition poses a number of challenges. This article reviews the various systems proposed over the past few years with a focus on the shortcomings that have prevented wide-scale implementation, including issues pertaining to temporal stability, psychological and physiological changes, protocol design, equipment and performance evaluation. We also examine several directions for the further development of usable EEG-based recognition systems as well as the niche markets to which they could be applied. It is expected that rapid advancements in EEG instrumentation, on-device processing and machine learning techniques will lead to the emergence of commercialized person recognition systems in the near future. |
| first_indexed | 2024-12-13T10:18:32Z |
| format | Article |
| id | doaj.art-2654b11c6ad14143ab66a65f0ac748a1 |
| institution | Directory Open Access Journal |
| issn | 1662-5196 |
| language | English |
| last_indexed | 2024-12-13T10:18:32Z |
| publishDate | 2018-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroinformatics |
| spelling | doaj.art-2654b11c6ad14143ab66a65f0ac748a12022-12-21T23:51:15ZengFrontiers Media S.A.Frontiers in Neuroinformatics1662-51962018-10-011210.3389/fninf.2018.00066395359Challenges and Future Perspectives on Electroencephalogram-Based Biometrics in Person RecognitionHui-Ling Chan0Po-Chih Kuo1Chia-Yi Cheng2Yong-Sheng Chen3Yong-Sheng Chen4Yong-Sheng Chen5Department of Computer Science, National Chiao Tung University, Hsinchu, TaiwanDepartment of Computer Science, National Chiao Tung University, Hsinchu, TaiwanInstitute of Biomedical Engineering, National Chiao Tung University, Hsinchu, TaiwanDepartment of Computer Science, National Chiao Tung University, Hsinchu, TaiwanInstitute of Biomedical Engineering, National Chiao Tung University, Hsinchu, TaiwanCenter for Emergent Functional Matter Science, National Chiao Tung University, Hsinchu, TaiwanThe emergence of the digital world has greatly increased the number of accounts and passwords that users must remember. It has also increased the need for secure access to personal information in the cloud. Biometrics is one approach to person recognition, which can be used in identification as well as authentication. Among the various modalities that have been developed, electroencephalography (EEG)-based biometrics features unparalleled universality, distinctiveness and collectability, while minimizing the risk of circumvention. However, commercializing EEG-based person recognition poses a number of challenges. This article reviews the various systems proposed over the past few years with a focus on the shortcomings that have prevented wide-scale implementation, including issues pertaining to temporal stability, psychological and physiological changes, protocol design, equipment and performance evaluation. We also examine several directions for the further development of usable EEG-based recognition systems as well as the niche markets to which they could be applied. It is expected that rapid advancements in EEG instrumentation, on-device processing and machine learning techniques will lead to the emergence of commercialized person recognition systems in the near future.https://www.frontiersin.org/article/10.3389/fninf.2018.00066/fullelectroencephalography (EEG)biometricsperson recognitionperson authenticationperson identification |
| spellingShingle | Hui-Ling Chan Po-Chih Kuo Chia-Yi Cheng Yong-Sheng Chen Yong-Sheng Chen Yong-Sheng Chen Challenges and Future Perspectives on Electroencephalogram-Based Biometrics in Person Recognition Frontiers in Neuroinformatics electroencephalography (EEG) biometrics person recognition person authentication person identification |
| title | Challenges and Future Perspectives on Electroencephalogram-Based Biometrics in Person Recognition |
| title_full | Challenges and Future Perspectives on Electroencephalogram-Based Biometrics in Person Recognition |
| title_fullStr | Challenges and Future Perspectives on Electroencephalogram-Based Biometrics in Person Recognition |
| title_full_unstemmed | Challenges and Future Perspectives on Electroencephalogram-Based Biometrics in Person Recognition |
| title_short | Challenges and Future Perspectives on Electroencephalogram-Based Biometrics in Person Recognition |
| title_sort | challenges and future perspectives on electroencephalogram based biometrics in person recognition |
| topic | electroencephalography (EEG) biometrics person recognition person authentication person identification |
| url | https://www.frontiersin.org/article/10.3389/fninf.2018.00066/full |
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