A Review on UWB Antenna Sensor for Wireless Body Area Networks

Alani, Sameer; Zakaria, Zahriladha; Saiedi, Tale; Ahmad, Ahmad K.; Mahmood, Sarmad Nozad; Saad, Mohammed Ayad; Rashid, Shah Samiur; Hamdi, Mustafa Maad; Albeyar, Ma'ath Abdulla A. Arabi

doi:10.1109/ismsit50672.2020.9254219

Cited by 10 publications

(5 citation statements)

References 70 publications

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“…The master unit's placement (6) was found to be less error prone, with a low packet-loss ratio in both cases, for the subject walking in the public hall and on the treadmill. Placement (6) avoids the limitations of UWB-WBAN, as revealed in the literature [39].…”

Section: Discussionmentioning

confidence: 99%

“…The literature identifies the limitations in reliable data transmission for a patient's freedom of movement and the avoidance of interference from other bands [39]. Data transmission in the presence of other microwave signals, as shown in Figure 7, was not expected to affect the WSA data transmission over UWB.…”

Section: Discussionmentioning

confidence: 99%

“…According to the studies discussed in [39], a WBAN based on IEEE802.15.4-2011, such as the WSA presented in this paper, can be used as a communication network for personal health applications. The technology behind this standard is now mature enough to be available in the market, making it a potential solution for dedicated low-cost WBAN systems, as shown here.…”

Section: Discussionmentioning

confidence: 99%

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Wearable Sensory Apparatus for Real-Time Feedback in Wearable Robotics

Munih¹,

Ivanić²,

Kamnik³

2021

Applied Sciences

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We describe the Wearable Sensory Apparatus (WSA) System, which has been implemented and verified in accordance with the relevant standards. It comprises the Inertial Measurement Units (IMUs), real-time wireless data transmission over Ultrawideband (UWB), a Master Unit and several IMU dongles forming the Wireless Body Area Network (WBAN). The WSA is designed for, but is not restricted to, wearable robots. The paper focuses on the topology of the communication network, the WSA hardware, and the organization of the WSA firmware. The experimental evaluation of the WSA incorporates the confirmation of the timing using the supply current WSA profile, measurements related to determining the less error prone position of the master device on the backpack, measurements of the quality of the data transfer in a real environment scenario, measurements in the presence of other microwave signals, and an example of raw IMU signals during human walking. Placement of the master device on the top of the backpack was found to be less error prone, with less than 0.02% packet loss for all the IMU devices placed on different body segments. The packet loss did not change significantly in public buildings or on the street. There was no impact of Wi-Fi bands on the WSA data transfer. The WSA hardware and firmware passed conformance testing in a certified lab. Most importantly, the WSA performed reliably in the laboratory and in clinical tests with exoskeletons and prostheses.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Wearable Sensory Apparatus for Real-Time Feedback in Wearable Robotics

Munih¹,

Ivanić²,

Kamnik³

2021

Applied Sciences

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“…The rapid advancement of the IoT has revolutionized various industries, including healthcare. holds tremendous potential for improving patient care, enabling remote monitoring, and enhancing healthcare delivery [3]. However, with this increased connectivity comes a pressing concern: the security of the IOMT environment.…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Analysis of Security Challenges and Countermeasures in Wireless Sensor Networks Enhanced by Machine Learning and Deep Learning Technologies

Saleh,

Marouane,

Fakhfakh

2024

IJSSE

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Wireless sensor networks (WSNs) play a crucial role in monitoring and capturing information in various domains, including the Internet of Medical Things (IOMT). However, WSNs face significant security challenges, such as intrusion and potential malicious activities, due to their distributed and resource-constrained nature. This research provides a comprehensive analysis of the security challenges in WSNs enhanced by machine learning and deep learning technologies within the context of the IOMT. The research addresses these challenges by proposing practical countermeasures to mitigate security concerns in WSNs. It discusses the complexities, critical security issues, and vulnerabilities within WSNs, offering insights into potential fixes based on various approaches and theories. Furthermore, the integration of machine learning and deep learning in WSNs enables efficient communication, data analysis, and control, supporting areas like the IOMT, which includes monitoring prescription orders, tracking patients' movements, and remotely managing patients with chronic illnesses. By addressing the security challenges specific to WSNs in the IOMT environment, this research contributes to the advancement of secure and reliable wireless sensing systems in critical domains. The utilization of machine learning and deep learning technologies facilitates the development of robust methods for detecting and mitigating network attacks. The practical implications of the research findings are demonstrated through tangible examples within the IOMT context, emphasizing the potential impact on improving the security and reliability of wireless sensing systems.

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“…A high transmission rate can be achieved by combining a large bandwidth covering the majority of the radio spectrum with an appropriate modulation (such as Pulse Position Modulation (PPM), Pulse Amplitude Modulation (PAM), Bi-Phase Modulation (BPSK), Code Division Multiple Access (CDMA), or Orthogonal Frequency Division Multiplexing (OFDM)) [ 2 ]. UWB technology has a wide range of applications, including data transmission and sensor data collecting in modern networks, such as WPAN (Wireless Personal Area Networks) for interconnecting electronic devices [ 2 ] and WBAN (Wireless Body Area Networks) for continuous health monitoring [ 3 ]. Additionally, it can be utilized to locate or detect moving objects, such as in collision avoidance systems or human sensing.…”

Section: Introductionmentioning

confidence: 99%

Influence of Various Technologies on the Quality of Ultra-Wideband Antenna on a Polymeric Substrate

et al. 2022

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The design, simulation, realization, and measurement of an ultra-wideband (UWB) antenna on a polymeric substrate have been realized. The UWB antenna was prepared using conventional technology, such as copper etching; inkjet printing, which is regarded as a modern and progressive nano-technology; and polymer thick-film technology in the context of screen-printing technology. The thick-film technology-based UWB antenna has a bandwidth of 3.8 GHz, with a central frequency of 9 GHz, and a frequency range of 6.6 to 10.4 GHz. In addition to a comparison of the technologies described, the results show that the mesh of the screens has a significant impact on the quality of the UWB antenna when utilizing polymeric screen-printing pastes. Last but not least, the eco-friendly combination of polyimide substrate and graphene-based screen-printing paste is thoroughly detailed. From 5 to 9.42 GHz, the graphene-based UWB antenna achieved a bandwidth of 4.42 GHz. The designed and realized UWB antenna well exceeds the Federal Communications Commission’s (FCC) standards for UWB antenna definition. The modification of the energy surface of the polyimide substrate by plasma treatment is also explained in this paper, in addition to the many types of screen-printing pastes and technologies. According to the findings, plasma treatment improved the bandwidth of UWB antennas to 5.45 GHz, and the combination of plasma treatment with graphene provides a suitable replacement for traditional etching technologies. The characteristics of graphene-based pastes can also be altered by plasma treatment in terms of their usability on flexible substrates.

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A Review on UWB Antenna Sensor for Wireless Body Area Networks

Cited by 10 publications

References 70 publications

Wearable Sensory Apparatus for Real-Time Feedback in Wearable Robotics

Wearable Sensory Apparatus for Real-Time Feedback in Wearable Robotics

A Comprehensive Analysis of Security Challenges and Countermeasures in Wireless Sensor Networks Enhanced by Machine Learning and Deep Learning Technologies

Influence of Various Technologies on the Quality of Ultra-Wideband Antenna on a Polymeric Substrate

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