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Liu Q, Zhou J, Zeng Q, Sun D, Yu B, Yang L, Zhang Z, Wu J, Zhang Y. Flexible Dry Epidermal Electrophysiological Electrodes Based on One-Dimensional Platinum-Coated Silver Nanowires. ACS APPLIED NANO MATERIALS 2024; 7:18226-18236. [DOI: 10.1021/acsanm.3c03457] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/28/2024]
Affiliation(s)
- Qing Liu
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Jie Zhou
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- College of Optoelectronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China
| | - Qi Zeng
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518061, China
| | - Dexin Sun
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Bin Yu
- College of Materials Science and Engineering, Donghua University, Shanghai 201620, China
| | - Liangtao Yang
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Zhilin Zhang
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Jinglong Wu
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Yi Zhang
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
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Manoharan AK, Batcha MIK, Mahalingam S, Raj B, Kim J. Recent Advances in Two-Dimensional Nanomaterials for Healthcare Monitoring. ACS Sens 2024; 9:1706-1734. [PMID: 38563358 DOI: 10.1021/acssensors.4c00015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
The development of advanced technologies for the fabrication of functional nanomaterials, nanostructures, and devices has facilitated the development of biosensors for analyses. Two-dimensional (2D) nanomaterials, with unique hierarchical structures, a high surface area, and the ability to be functionalized for target detection at the surface, exhibit high potential for biosensing applications. The electronic properties, mechanical flexibility, and optical, electrochemical, and physical properties of 2D nanomaterials can be easily modulated, enabling the construction of biosensing platforms for the detection of various analytes with targeted recognition, sensitivity, and selectivity. This review provides an overview of the recent advances in 2D nanomaterials and nanostructures used for biosensor and wearable-sensor development for healthcare and health-monitoring applications. Finally, the advantages of 2D-nanomaterial-based devices and several challenges in their optimal operation have been discussed to facilitate the development of smart high-performance biosensors in the future.
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Affiliation(s)
- Arun Kumar Manoharan
- Department of Electrical, Electronics and Communication Engineering, School of Technology, Gandhi Institute of Technology and Management (GITAM), Bengaluru 561203, Karnataka, India
| | - Mohamed Ismail Kamal Batcha
- Department of Electronics and Communication Engineering, Agni College of Technology, Chennai 600130, Tamil Nadu, India
| | - Shanmugam Mahalingam
- Department of Materials System Engineering, Pukyong National University, Busan 48513, Republic of Korea
| | - Balwinder Raj
- Department of Electronics and Communication Engineering, Dr B R Ambedkar National Institute of Technology Jalandhar, Punjab 144011, India
| | - Junghwan Kim
- Department of Materials System Engineering, Pukyong National University, Busan 48513, Republic of Korea
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Maiseli B, Abdalla AT, Massawe LV, Mbise M, Mkocha K, Nassor NA, Ismail M, Michael J, Kimambo S. Brain-computer interface: trend, challenges, and threats. Brain Inform 2023; 10:20. [PMID: 37540385 PMCID: PMC10403483 DOI: 10.1186/s40708-023-00199-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 07/01/2023] [Indexed: 08/05/2023] Open
Abstract
Brain-computer interface (BCI), an emerging technology that facilitates communication between brain and computer, has attracted a great deal of research in recent years. Researchers provide experimental results demonstrating that BCI can restore the capabilities of physically challenged people, hence improving the quality of their lives. BCI has revolutionized and positively impacted several industries, including entertainment and gaming, automation and control, education, neuromarketing, and neuroergonomics. Notwithstanding its broad range of applications, the global trend of BCI remains lightly discussed in the literature. Understanding the trend may inform researchers and practitioners on the direction of the field, and on where they should invest their efforts more. Noting this significance, we have analyzed 25,336 metadata of BCI publications from Scopus to determine advancement of the field. The analysis shows an exponential growth of BCI publications in China from 2019 onwards, exceeding those from the United States that started to decline during the same period. Implications and reasons for this trend are discussed. Furthermore, we have extensively discussed challenges and threats limiting exploitation of BCI capabilities. A typical BCI architecture is hypothesized to address two prominent BCI threats, privacy and security, as an attempt to make the technology commercially viable to the society.
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Affiliation(s)
- Baraka Maiseli
- Department of Electronics and Telecommunications Engineering, College of Information and Communication Technologies, University of Dar es Salaam, 14113, Dar es Salaam, Tanzania.
| | - Abdi T Abdalla
- Department of Electronics and Telecommunications Engineering, College of Information and Communication Technologies, University of Dar es Salaam, 14113, Dar es Salaam, Tanzania
| | - Libe V Massawe
- Department of Electronics and Telecommunications Engineering, College of Information and Communication Technologies, University of Dar es Salaam, 14113, Dar es Salaam, Tanzania
| | - Mercy Mbise
- Department of Computer Science and Engineering, College of Information and Communication Technologies, University of Dar es Salaam, 14113, Dar es Salaam, Tanzania
| | - Khadija Mkocha
- Department of Electronics and Telecommunications Engineering, College of Information and Communication Technologies, University of Dar es Salaam, 14113, Dar es Salaam, Tanzania
| | - Nassor Ally Nassor
- Department of Electronics and Telecommunications Engineering, College of Information and Communication Technologies, University of Dar es Salaam, 14113, Dar es Salaam, Tanzania
| | - Moses Ismail
- Department of Electronics and Telecommunications Engineering, College of Information and Communication Technologies, University of Dar es Salaam, 14113, Dar es Salaam, Tanzania
| | - James Michael
- Department of Electronics and Telecommunications Engineering, College of Information and Communication Technologies, University of Dar es Salaam, 14113, Dar es Salaam, Tanzania
| | - Samwel Kimambo
- Department of Electronics and Telecommunications Engineering, College of Information and Communication Technologies, University of Dar es Salaam, 14113, Dar es Salaam, Tanzania
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Functional Two-Dimensional Materials for Bioelectronic Neural Interfacing. J Funct Biomater 2023; 14:jfb14010035. [PMID: 36662082 PMCID: PMC9863167 DOI: 10.3390/jfb14010035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 12/26/2022] [Accepted: 01/03/2023] [Indexed: 01/11/2023] Open
Abstract
Realizing the neurological information processing by analyzing the complex data transferring behavior of populations and individual neurons is one of the fast-growing fields of neuroscience and bioelectronic technologies. This field is anticipated to cover a wide range of advanced applications, including neural dynamic monitoring, understanding the neurological disorders, human brain-machine communications and even ambitious mind-controlled prosthetic implant systems. To fulfill the requirements of high spatial and temporal resolution recording of neural activities, electrical, optical and biosensing technologies are combined to develop multifunctional bioelectronic and neuro-signal probes. Advanced two-dimensional (2D) layered materials such as graphene, graphene oxide, transition metal dichalcogenides and MXenes with their atomic-layer thickness and multifunctional capabilities show bio-stimulation and multiple sensing properties. These characteristics are beneficial factors for development of ultrathin-film electrodes for flexible neural interfacing with minimum invasive chronic interfaces to the brain cells and cortex. The combination of incredible properties of 2D nanostructure places them in a unique position, as the main materials of choice, for multifunctional reception of neural activities. The current review highlights the recent achievements in 2D-based bioelectronic systems for monitoring of biophysiological indicators and biosignals at neural interfaces.
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Signal Quality Investigation of a New Wearable Frontal Lobe EEG Device. SENSORS 2022; 22:s22051898. [PMID: 35271044 PMCID: PMC8914983 DOI: 10.3390/s22051898] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 02/24/2022] [Accepted: 02/26/2022] [Indexed: 02/04/2023]
Abstract
The demand for non-laboratory and long-term EEG acquisition in scientific and clinical applications has put forward new requirements for wearable EEG devices. In this paper, a new wearable frontal EEG device called Mindeep was proposed. A signal quality study was then conducted, which included simulated signal tests and signal quality comparison experiments. Simulated signals with different frequencies and amplitudes were used to test the stability of Mindeep’s circuit, and the high correlation coefficients (>0.9) proved that Mindeep has a stable and reliable hardware circuit. The signal quality comparison experiment, between Mindeep and the gold standard device, Neuroscan, included three tasks: (1) resting; (2) auditory oddball; and (3) attention. In the resting state, the average normalized cross-correlation coefficients between EEG signals recorded by the two devices was around 0.72 ± 0.02, Berger effect was observed (p < 0.01), and the comparison results in the time and frequency domain illustrated the ability of Mindeep to record high-quality EEG signals. The significant differences between high tone and low tone in auditory event-related potential collected by Mindeep was observed in N2 and P2. The attention recognition accuracy of Mindeep achieved 71.12% and 74.76% based on EEG features and the XGBoost model in the two attention tasks, respectively, which were higher than that of Neuroscan (70.19% and 72.80%). The results validated the performance of Mindeep as a prefrontal EEG recording device, which has a wide range of potential applications in audiology, cognitive neuroscience, and daily requirements.
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