A Novel Encryption Algorithm Based on DWT and Multichaos Mapping

Wireless communications for body area network (BAN) applications require an adaptable, dynamic and flexible medium access control (MAC) to cope with a variety of application requirements. The key requirements in BAN applications are low power consumption, high reliability of intra-BAN communication and low latency. As body posture highly affects the performance of MAC protocols, we evaluate the relaying benefits to reinforce links. However, since radio links are not stationary, the scheduling of the relaying should quickly adapt to BAN changes. We instead propose a BAN Adaptive TDMA MAC (BATMAC) which automatically detects the shadowing effect and adjusts its communication protocols and the parameters of the IEEE 802.15.4 superframe. Finally, we evaluate BATMAC from latency outage and energy consumption points of view depending on the redundancy of the monitoring information.

Power efficient ultra-wideband based wireless communication for wireless body area network applications

A non-uniformly spaced digital FIR filter bank has been proposed for QRS detection in wearable biomedical devices in Body Area Network (BAN) applications. The proposed filter bank is constructed based on frequency-response masking technique and employs two half-band filters as prototype filters, which leads to significant savings in terms of arithmetic operations. The introduction of non-uniformly spaced filter bank further enhances the detection accuracy especially in the BAN applications where motion artifacts are a major concern. Simulations show that the proposed algorithm correctly detects the QRS of both resting and exercising ECG, even under the presence of severe motion artifacts, baseline drift and large P/T waves.

The main bottleneck to achieve energy autonomy in body area networks (BAN) is the design of an ultra low power yet reliable wireless system. In this paper, we first demonstrate the feasibility of an ultra low power receiver by presenting our implemented receiver chip that could operate on a total power of 479.5 uW, which is more than one order of magnitude lower than commercially available low power transceivers working at 2.4 GHz. We then show the reliability of this chip, which can achieve a receiver sensitivity of −72 dBm for a data rate of 1 Mbps. We further demonstrate that this receiver sensitivity is sufficient to guarantee reliability by evaluating this chip in different to-body communication in BAN environments. By using typical BAN channels, simulation results show that our system can provide a reliable link in both the standing and walking situations. With the measured data, we show that a transmit power of −15 dBm is sufficient for our receiver to achieve reliable communication link in different BAN environments. This transmit power requirement is 15 dB lower than the widely known low power Zigbee system. It could thus significantly facilitate the ultra low power transmitter design, and minimize the human exposure to radio frequency electromagnetic fields. The design and evaluation of our receiver presented in this paper therefore provides a way to move towards the energy autonomy of BAN, and opens access to many new applications in BAN.

Review on miniaturized flexible wearable antenna with SAR measurement for body area network

This paper describes a low complexity, low data rate ultra-wideband system suited for use in body area network (BAN) applications. The described system has lower complexity and power consumption compared to similar systems for BAN applications. System architecture is defined and expected results in BAN communication channel are presented. Main building blocks like analog RF front-end IC and small size antennas suitable for applications on the human body have been developed and produced. Some measurement results of the implementation are presented.

It is worth mentioning that the growing use of wireless sensor networks, evolution in Nano biosensors and micro medical equipment, remote health monitoring has affected treatment. Since people have tended to ubiquitous health monitoring, real time medical health care systems will have great significance. It is crystal clear that offering a new design of Wireless Body Area Network (WBAN) in real time healthcare's system is very important. To pave the way for the discussion, we would like to pay your attention to the previous studies in which we have improved energy efficiency and security in WBAN. To pave the way for further discussion now, we would like to review the third aspect of WBAN challenge in maximum efficiency and performance, with the approaching security and optimal energy in the real time health care system applications. In a word, in this paper urgency of using WBAN for real time telemedicine is to be discussed.

Protection to classified digital data becomes so important in avoiding data manipulation and alteration. The focus of this paper is in data and information protection of digital images form. Protection is provided in the form of encrypted digital image. The encryption process uses a new map, , which is called MS map. This paper will show: the results of digital image encryption using MS map and how the performance is regarding the average time needed for encryption/decryption process; randomness of key stream sequence with NIST test, histogram analysis and goodness of fit test, quality of the decrypted image by PSNR, initial value sensitivity level, and key space. The results show that the average time of the encryption process is relatively same as the decryption process and it depends to types and sizes of the image. Cipherimage (encrypted image) is uniformly distributed since: it passes the goodness of fit test and also the histogram of the cipherimage is flat; key stream, that are generated by MS map, passes frequency (monobit) test, and runs test, which means the key stream is a random sequence; the decrypted image has same quality as the original image; and initial value sensitivity reaches 10−17, and key space reaches 3.24 × 10634. So, that encryption algorithm generated by MS map is more resistant to brute-force attack and known plaintext attack.

In this article, compact slotted rectangular patch antenna for wireless body area network (WBAN) applications. The designed antenna radiates at the resonance frequency of 5810MHz in free space and with body phantom model. The intended WBAN antenna design is simulated in free space as well as with human body phantom. The simulated antenna resonate frequency at 5810MHz with impedance bandwidth of 90MHz and 60MHz in free space and human body phantom respectively. The volume of the proposed rectangular slotted patch antenna is 64mm×52mm×0.857mm (3.26λ <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</inf> ×2.65λ <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</inf> ×0.044λ <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</inf> ). The proposed antenna broad side gain is 7.93dBi in free space and 7.67dBi with human body phantom. The width of the slot is chosen to optimize the impedance matching in biomedical application frequency range. The parametric analysis of antenna has been done to achieve the best performance of antenna for biomedical applications. The proposed antenna has been modelled and simulated using CST microwave suite with appropriate boundary conditions. The efficiency of slotted planar antenna is 94.8% without body phantom and 89.4% with human body phantom. An attempt has been made to propose patch antenna for achieving the impedance bandwidth within Spectrum range of Wireless Body Area Network (WBAN).The maximum SAR value of the intended antenna is within the range, as specified by IEEE safety guidelines.

Artificial intelligence (AI) is becoming a mainstream for telecommunication industry. With the utilization of millimeter-wave in 5G network, it becomes feasible to use beamforming techniques for on-body sensors in Wireless Body Area Network (WBAN) applications. Thus, there is a need for developing beamforming algorithms that can optimize WBAN network performance and a realistic dataset that can be used for training, testing, and benchmarking of the algorithms. Thus, we propose a dataset generation method for mmWave WBAN that utilizes computer vision and an adaptive deep learning-based algorithm for performance optimization of mmWave WBAN beamforming. Two major ideas are proposed: First, collecting human poses from estimation of 3D human poses in videos and generating more realistic poses using generative adversarial nets (GAN) are adopted; second, a GAN aims to predict the next beamforming directions using the previous set of directions as inputs. With available labeled human pose videos, the WBAN dataset we generate provides a sufficient amount of samples for training, testing, and benchmarking of beamforming algorithms. Additionally, the proposed adaptive beamforming algorithm does not require any intrusive data gathering methods. Our numerical studies show the advantages of our proposed approaches.

This paper presents a compact and planar ultra‐wideband (UWB) antenna, designed and characterized for the wearable Internet of Things (IoT) devices and wireless body area network (WBAN) applications. Two different substrates, ie, FR4 (h = 1.6 mm) and denim textile substrate (h = 1 mm), are used in the process of design and fabrication of the proposed antenna. The dimensions of the proposed antenna are 31 mm × 42 mm for FR4 substrate and 70 mm × 56 mm for denim textile substrate. The antenna structure consists of a rectangular radiating patch with two symmetrical staircase‐shaped slits. A reduced ground plane technique is used for the purpose of improving impedance bandwidth, which is further enhanced by the insertion of a small notch in the reduced ground plane which has improved the overall impedance matching characteristics of the proposed UWB antenna. The measured impedance bandwidth for S11 &lt; −10 dB and gain of the FR4 and denim textile substrate UWB antennas are 7.71 GHz/5.12 dBi and 7.95 GHz/3.57 dBi, respectively. The ADS momentum simulator is used for antenna simulations, and the simulated and measured results are generally found in good agreements.

Proposed is a zeroth-order resonant antenna placed on a wrist for wireless body area network (WBAN) applications. The proposed antenna is insensitive to human body effects and its curvature shape, owing to a bottom ground plate and zero phase constant features. The antenna's performance is simulated and measured through body equivalent liquid and the human body. The radiation patterns and reflection coefficient are constant when the antenna is placed on the body equivalent liquid and the wrist.

Bluetooth Low Energy (BLE) has emerged as a technology of choice in many applications including body area networks (BAN). In this paper, we investigate the use of BLE in terms of throughput, power consumption and latency and evaluate its suitability for BAN applications. We compare the performance of different versions of the Bluetooth core specification using a theoretical model and an experimental setup based on nRF52840 chip by Nordic Semiconductor. We focus on Electrocardiography (EKG) and give the current consumption and battery lifetime estimation of an EKG BLE node for different BLE versions and configurations.

In recent years, interests in the application of Wireless Body Area Network (WBAN) have grown considerably. A WBAN can be used to develop a patient monitoring system which offers flexibility and mobility to patients. Use of a WBAN will also allow the flexibility of setting up a remote monitoring system via either the internet or an intranet. For such medical systems it is very important that a WBAN can collect and transmit data reliably, and in a timely manner to the monitoring entity. In this paper we examine the performance of an IEEE802.15.4/Zigbee MAC based WBAN operating in different patient monitoring environment. We study the performance of a remote patient monitoring system using an OPNET based simulation model.

ABSTRACTAutomatic face recognition is useful in a wide range of applications. The accuracy of a face recognition system is adversely affected due to illumination variations. This study presents an illumination pre-processing method, “Enhanced Energy Discrete Wavelet Transform”, to increase recognition accuracy of front view faces under varying illuminations. This method is implemented as follows. A two-dimensional Discrete Wavelet Transform (2D DWT) decomposes the original image into four frequency sub-bands, namely low-low, low-high, high-low and high-high. The energy of each sub-band is computed. A weighting scheme is employed to increase the energy. The weighting scheme computes weight of sub-band based on its energy and threshold. The new sub-bands are obtained by multiplying sub-band, weight and weighting factor. Then, the new four sub-bands are added to create enhanced energy DWT image. The face recognition is carried out using Gabor magnitude features. The experiments are conducted in facial images of Yale, Pose Illumination Expression (PIE) and Extended Yale B. The results proves that low-low sub-band has maximum weight. The performance analysis is carried out using different threshold and weighting factor values. The weighting factor increases energy of low-low sub-band. The analysis of energy enhancement shows increase in energy of 20.96% and 31.88% in CMU PIE and Extended Yale B, respectively. The increase of energy improves the brightness of image. The recognition accuracy in CMU PIE and Extended Yale B is 99.02% and 99.82%, respectively. The comparative analysis with the state-of-the-art methods proves that the proposed method is an effective illumination pre-processing method.