Review of EEG-Based Biometrics in 5G-IoT: Current Trends and Future Prospects

被引:9
作者
Beyrouthy, Taha [1 ]
Mostafa, Nour [1 ]
Roshdy, Ahmed [2 ]
Karar, Abdullah S. [1 ]
Alkork, Samer [1 ]
Mourtzis, Dimitris
Niu, Qiang
Yang, Xu
机构
[1] Amer Univ Middle East, Coll Engn & Technol, Egaila 54200, Kuwait
[2] Univ Paris Est, LiSSi, F-94400 Vitry Sur Seine, Ile De France, France
来源
APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 02期
关键词
IoT; 5G; EEG signal; wearable IoT devices; Internet of Things; seamlessly IoT devices; sensors; EMOTION RECOGNITION; SMART HEALTH; IOT; ARCHITECTURE; INTERNET; SIGNALS; BCI; 5G; ACQUISITION; NETWORKS;
D O I
10.3390/app14020534
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The increasing integration of the Internet of Things (IoT) into daily life has led to significant changes in our social interactions. The advent of innovative IoT solutions, combined with the enhanced capabilities and expanded reach of 5G wireless networks, is altering the way humans interact with machines. Notably, the advancement of edge computing, underpinned by 5G networks within IoT frameworks, has markedly extended human sensory perception and interaction. A key biometric within these IoT applications is electroencephalography (EEG), recognized for its sensitivity, cost-effectiveness, and distinctiveness. Traditionally linked to brain-computer interface (BCI) applications, EEG is now finding applications in a wider array of fields, from neuroscience research to the emerging area of neuromarketing. The primary aim of this article is to offer a comprehensive review of the current challenges and future directions in EEG data acquisition, processing, and classification, with a particular focus on the increasing reliance on data-driven methods in the realm of 5G wireless network-supported EEG-enabled IoT solutions. Additionally, the article presents a case study on EEG-based emotion recognition, exemplifying EEG's role as a biometric tool in the IoT domain, propelled by 5G technology.
引用
收藏
页数:32
相关论文
共 147 条
[1]  
Adiga S, 2020, INT CONF SOFT COMP, P197, DOI [10.1109/ISCMI51676.2020.9311566, 10.1109/iscmi51676.2020.9311566]
[2]   Emotion Recognition by Correlating Facial Expressions and EEG Analysis [J].
Aguinaga, Adrian R. ;
Hernandez, Daniel E. ;
Quezada, Angeles ;
Tellez, Andres Calvillo .
APPLIED SCIENCES-BASEL, 2021, 11 (15)
[3]   A Comprehensive review on 5G-based Smart Healthcare Network Security: Taxonomy, Issues, Solutions and Future research directions [J].
Ahad, Abdul ;
Ali, Zahra ;
Mateen, Abdul ;
Tahir, Mohammad ;
Hannan, Abdul ;
Garcia, Nuno M. ;
Pires, Ivan Miguel .
ARRAY, 2023, 18
[4]   EEG-Brain Activity Monitoring and Predictive Analysis of Signals Using Artificial Neural Networks [J].
Aileni, Raluca Maria ;
Pasca, Sever ;
Florescu, Adriana .
SENSORS, 2020, 20 (12) :1-21
[5]   A Critical Survey of EEG-Based BCI Systems for Applications in Industrial Internet of Things [J].
Ajmeria, Rahul ;
Mondal, Mayukh ;
Banerjee, Reya ;
Halder, Tamesh ;
Deb, Pallav Kumar ;
Mishra, Debasish ;
Nayak, Pravanjan ;
Misra, Sudip ;
Pal, Surjya Kanta ;
Chakravarty, Debashish .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2023, 25 (01) :184-212
[6]   Explainable artificial intelligence to evaluate industrial internal security using EEG signals in IoT framework [J].
Al Hammadi, Ahmed Y. ;
Yeun, Chan Yeob ;
Damiani, Ernesto ;
Yoo, Paul D. ;
Hu, Jiankun ;
Yeun, Hyun Ku ;
Yim, Man-Sung .
AD HOC NETWORKS, 2021, 123
[7]   A Deep-Learning Model for Subject-Independent Human Emotion Recognition Using Electrodermal Activity Sensors [J].
Al Machot, Fadi ;
Elmachot, Ali ;
Ali, Mouhannad ;
Al Machot, Elyan ;
Kyamakya, Kyandoghere .
SENSORS, 2019, 19 (07)
[8]  
Al-masri Eyhab, 2022, 2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII ), P18, DOI 10.1109/ICKII55100.2022.9983557
[9]  
Alam F., 2014, P 2014 ACM MULT WORK, P15
[10]   Parkinson's Disease Detection from Resting-State EEG Signals Using Common Spatial Pattern, Entropy, and Machine Learning Techniques [J].
Aljalal, Majid ;
Aldosari, Saeed A. ;
AlSharabi, Khalil ;
Abdurraqeeb, Akram M. ;
Alturki, Fahd A. .
DIAGNOSTICS, 2022, 12 (05)