A comprehensive review of wireless body area network

Hasan, Khalid; Biswas, Kamanashis; Ahmed, Khandakar; Nafi, Nazmus Shaker; Islam, Saiful

doi:10.1016/j.jnca.2019.06.016

Cited by 152 publications

(112 citation statements)

References 101 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Due to the limitation of energy resources, the power management has become a critical issue in designing a WBAN. Since wireless communication consumes a considerable portion of the energy 30 , numerous studies have proposed and investigated low-power solutions [31][32][33][34] . The conventional state-of-the-art wireless sensor networks working in the vicinity of the human body adopt radio-wave propagation for signal transmission.…”

mentioning

confidence: 99%

Human activity recognition using magnetic induction-based motion signals and deep recurrent neural networks

Golestani

Moghaddam

2020

Nat Commun

View full text Add to dashboard Cite

Recognizing human physical activities using wireless sensor networks has attracted significant research interest due to its broad range of applications, such as healthcare, rehabilitation, athletics, and senior monitoring. There are critical challenges inherent in designing a sensor-based activity recognition system operating in and around a lossy medium such as the human body to gain a trade-off among power consumption, cost, computational complexity, and accuracy. We introduce an innovative wireless system based on magnetic induction for human activity recognition to tackle these challenges and constraints. The magnetic induction system is integrated with machine learning techniques to detect a wide range of human motions. This approach is successfully evaluated using synthesized datasets, laboratory measurements, and deep recurrent neural networks.

show abstract

mentioning

confidence: 99%

Human activity recognition using magnetic induction-based motion signals and deep recurrent neural networks

Golestani

Moghaddam

2020

Nat Commun

View full text Add to dashboard Cite

show abstract

“…ETx-elec = ERx-elec = Eelec = 50 nJ / bit, (4) ε amp = 100 pJ / bit / m², (5) εamp is the energy used by the transmit amplifier. It is the most critical component in transmitter subsystem, that is, a major source of energy drainage.…”

Section: Energy Consumption Analysismentioning

confidence: 99%

“…The Wireless Body Area Network (WBAN) [3][4][5] is a particular type of wireless sensor network (WSN). WBAN is used in several fields [6] notably in the health field.…”

Section: Introductionmentioning

confidence: 99%

High Throughput and Thermal Aware Routing Protocol (HTTRP) for Wireless Body Area Networks

Bouldjadj¹,

Aliouat²

2020

ISI

View full text Add to dashboard Cite

One of the major applications of sensor networks in the near future will be in the area of biomedical research. Wireless Body Area Networks (WBANs) are composed of implanted biosensors for health monitoring and diagnostic purposes. The communication between these sensors is made in a wireless way at the base of the radio waves. The sensors' activity produces heat causing a temperature rise. The high-temperature rise of the sensors for a prolonged period might damage the surrounding tissues. Various routing protocols have been proposed in the literature to remedy this problem. These protocols tried to perform routing based on the SHR algorithm while avoiding hot-spots nodes. However, the energy of sensor nodes located in this shorter path is quickly exhausted and by the way, the whole network lifetime is influenced. In this work, we propose HTTRP, a new routing protocol for WBANs introducing a new route selection mechanism that aims to reduce the overheating of sensors and balance their energy consumption. This mechanism is based on a function that considers the residual energy of sensor nodes and their temperature when choosing the next relay node. The carried out simulation results show that our HTTRP protocol has better performance in terms of network lifetime, charge balancing, temperature rise, and throughput compared to a representative of TARP that is TARA protocol.

show abstract

“…Given this variety of applications , the actual wireless short range technologies do not fully comply with the specific requirements and technical challenges of WBANs [16]. For this reason, IEEE 802.15.6 was created in November 2007 to deliver an international standard for highly reliable, short-range, and bodywide communications, while providing a broad range of data rates going from 75.9 Kbps (narrowband) to 15.6 Mbps (ultrabroadband); to cover a variety of applications.…”

Section: Introductionmentioning

confidence: 99%

The Effects of Transmission Power and Modulation Schemes on the Performance of WBANs in on-Body Medical Applications

Boumaiz¹,

Ghazi²,

Fattah³

et al. 2020

Adv. sci. technol. eng. syst. j.

View full text Add to dashboard Cite

Wireless Body Area Networks support the operation within multiple frequency bands. Thus, they can be integrated in several applications, one of which is on-body medical monitoring applications, as concerned in this paper. Therefore, the purpose of this study is to present the impact of transmission power and both of Differential Binary Phase Shift Keying and Differential Quadrature Phase Shift Keying modulation schemes, on the performance of a WBAN model based on the IEEE 802.15.6 2.4 GHz narrow-band, dedicated to on-body medical applications. This involves identifying the modulation scheme(s) and transmission power level(s) to be adopted for these applications, that can be classified into three types depending on their data rate (low, medium and high data rate medical applications), in order to meet Packet Loss Rate and latency requirements. The numerical study has confirmed that the adoption of DBPSK modulation and low transmission powers provides good performance for low data rate monitoring applications. At medium data rates, a relatively increased transmit power was required. However, at high data rates, DQPSK modulation with a 0 dBm transmission power seemed to be the right choice to be made in terms of the mentioned performance indicators.

show abstract

A comprehensive review of wireless body area network

Cited by 152 publications

References 101 publications

Human activity recognition using magnetic induction-based motion signals and deep recurrent neural networks

Human activity recognition using magnetic induction-based motion signals and deep recurrent neural networks

High Throughput and Thermal Aware Routing Protocol (HTTRP) for Wireless Body Area Networks

The Effects of Transmission Power and Modulation Schemes on the Performance of WBANs in on-Body Medical Applications

Contact Info

Product

Resources

About