DNBP-CCA:A Novel Approach to Enhancing Heterogeneous Data Traffic and Reliable Data Transmission for Body Area Network

The increased adoption of Internet of Medical Things (IoMT) technologies has resulted in the widespread use ofBody Area Networks (BANs) in medical and non-medical domains. However, the performance of IEEE 802.15.4-based BANs is impacted by challenges related to heterogeneous data traffic requirements among nodes, includingcontention during finite backoff periods, association delays, and traffic channel access through clear channelassessment (CCA) algorithms. These challenges lead to increased packet collisions, queuing delays, retransmissions,and the neglect of critical traffic, thereby hindering performance indicators such as throughput, packet deliveryratio, packet drop rate, and packet delay. Therefore, we propose Dynamic Next Backoff Period and Clear ChannelAssessment (DNBP-CCA) schemes to address these issues. The DNBP-CCA schemes leverage a combination ofthe Dynamic Next Backoff Period (DNBP) scheme and the Dynamic Next Clear Channel Assessment (DNCCA)scheme. The DNBP scheme employs a fuzzy Takagi, Sugeno, and Kang (TSK) model’s inference system toquantitatively analyze backoff exponent, channel clearance, collision ratio, and data rate as input parameters. Onthe other hand, the DNCCA scheme dynamically adapts the CCA process based on requested data transmission tothe coordinator, considering input parameters such as buffer status ratio and acknowledgement ratio. As a result,simulations demonstrate that our proposed schemes are better than some existing representative approaches andenhance data transmission, reduce node collisions, improve average throughput, and packet delivery ratio, anddecrease average packet drop rate and packet delay.

Priority Based Energy Efficient MAC Protocol by Varying Data Ratefor Wireless Body Area Network

Wireless Body Area Network(WBAN)is a cutting-edge technology that is being used in healthcare applications to monitor critical events in the human body.WBAN is a collection of in-body and on-body sensors that monitor human physical parameters such as temperature,blood pressure,pulse rate,oxygen level,body motion,and so on.They sense the data and communicate it to the Body Area Network(BAN)Coordinator.The main challenge for the WBAN is energy consumption.These issues can be addressed by implementing an effective Medium Access Control(MAC)protocol that reduces energy consumption and increases network lifetime.The purpose of the study is to minimize the energy consumption and minimize the delay using IEEE 802.15.4 standard.In our proposed work,if any critical events have occurred the proposed work is to classify and prioritize the data.We gave priority to the highly critical data to get the Guarantee Tine Slots(GTS)in IEEE 802.15.4 standard superframe to achieve greater energy efficiency.The proposed MAC provides higher data rates for critical data based on the history and current condition and also provides the best reliable service to high critical data and critical data by predicting node similarity.As an outcome,we proposed a MAC protocol for Variable Data Rates(MVDR).When compared to existing MAC protocols,the MVDR performed very well with low energy intake,less interruption,and an enhanced packet-sharing ratio.

An Efficient Heterogeneous Ring Signcryption Scheme for Wireless Body Area Networks

Wireless body area networks(WBANs)are an emerging technology for the real-time monitoring of physiological signals.WBANs provide a mechanism for collecting,storing,and transmitting physiological data to healthcare providers.However,the open wireless channel and limited resources of sensors bring security challenges.To ensure physiological data security,this paper provides an efficient Certificateless Public Key Infrastructure Heterogeneous Ring Signcryption(CP-HRSC)scheme,in which sensors are in a certificateless cryptosystem(CLC)environment,and the server is in a public key infrastructure(PKI)environment.CLC could solve the limitations of key escrow in identity-based cryptography(IBC)and certificate management for public keys in PKI.While PKI is suited for the server because it is widely used on the Internet.Furthermore,this paper designs a ring signcryption method that allows the controller to anonymously encrypt physiological data on behalf of a set of sensors,but the server does not exactly know who the sensor is.The construction of this paper can achieve anonymity,confidentiality,authentication,non-repudiation,and integrity in a logically single step.Under the computational Diffie-Hellman(CDH)problem,the formal security proof is provided in the random oracle model(ROM).This paper demonstrates that this scheme has indistinguishability against adaptive chosen ciphertext attacks(IND-CCA2)and existential unforgeability against adaptive chosen message attacks(EUF-CMA).In terms of computational cost and energy usage,a comprehensive performance analysis demonstrates that the proposed scheme is the most effective.Compared to the three existing schemes,the computational cost of this paper’s scheme is reduced by about 49.5%,4.1%,and 8.4%,and the energy usage of our scheme is reduced by about 49.4%,3.7%,and 14.2%,respectively.

Research on intelligent search-and-secure technology in accelerator hazardous areas based on machine vision

Prompt radiation emitted during accelerator operation poses a significant health risk,necessitating a thorough search and securing of hazardous areas prior to initiation.Currently,manual sweep methods are employed.However,the limitations of manual sweeps have become increasingly evident with the implementation of large-scale accelerators.By leveraging advancements in machine vision technology,the automatic identification of stranded personnel in controlled areas through camera imagery presents a viable solution for efficient search and security.Given the criticality of personal safety for stranded individuals,search and security processes must be sufficiently reliable.To ensure comprehensive coverage,180°camera groups were strategically positioned on both sides of the accelerator tunnel to eliminate blind spots within the monitoring range.The YOLOV8 network model was modified to enable the detection of small targets,such as hands and feet,as well as larger targets formed by individuals near the cameras.Furthermore,the system incorporates a pedestrian recognition model that detects human body parts,and an information fusion strategy is used to integrate the detected head,hands,and feet with the identified pedestrians as a cohesive unit.This strategy enhanced the capability of the model to identify pedestrians obstructed by equipment,resulting in a notable improvement in the recall rate.Specifically,recall rates of 0.915 and 0.82were obtained for Datasets 1 and 2,respectively.Although there was a slight decrease in accuracy,it aligned with the intended purpose of the search-and-secure software design.Experimental tests conducted within an accelerator tunnel demonstrated the effectiveness of this approach in achieving reliable recognition outcomes.

A Human Body Posture Recognition Algorithm Based on BP Neural Network for Wireless Body Area Networks

Human body posture recognition has attracted considerable attention in recent years in wireless body area networks(WBAN). In order to precisely recognize human body posture,many recognition algorithms have been proposed.However, the recognition rate is relatively low. In this paper, we apply back propagation(BP) neural network as a classifier to recognizing human body posture, where signals are collected from VG350 acceleration sensor and a posture signal collection system based on WBAN is designed. Human body signal vector magnitude(SVM) and tri-axial acceleration sensor data are used to describe the human body postures. We are able to recognize 4postures: Walk, Run, Squat and Sit. Our posture recognition rate is up to 91.67%. Furthermore, we find an implied relationship between hidden layer neurons and the posture recognition rate. The proposed human body posture recognition algorithm lays the foundation for the subsequent applications.

A novel nest-based scheduling method for mobile wireless body area networks

Wireless Body Area Networks(WBANs)comprise various sensors to monitor and collect various vital signals,such as blood pressure,pulse,heartbeat,body temperature,and blood sugar.A dense and mobile WBAN often suffers from interference,which causes serious problems,such as wasting energy and degrading throughput.In reality,not all of the sensors in WBAN need to be active at the same time.Therefore,they can be divided into different groups so that each group works in turn to avoid interference.In this paper,a Nest-Based WBAN Scheduling(NBWS)algorithm is proposed to cluster sensors of the same types in a single or multiple WBANs into different groups to avoid interference.Particularly,we borrow the graph coloring theory to schedule all groups to work using a Time Division for Multimodal Sensor(TDMS)group scheduling model.Both theoretical analysis and experimental results demonstrate that the proposed NBWS algorithm performs better in terms of frequency of collisions,transmission delay,system throughput,and energy consumption compared to the counterpart methods.

A Review of Wireless Body Area Networks for Medical Applications

Recent advances in Micro-Electro-Mechanical Systems (MEMS) technology, integrated circuits, and wireless communication have allowed the realization of Wireless Body Area Networks (WBANs). WBANs promise unobtrusive ambulatory health monitoring for a long period of time, and provide real-time updates of the patient’s status to the physician. They are widely used for ubiquitous healthcare, entertainment, and military applications. This paper reviews the key aspects of WBANs for numerous applications. We present a WBAN infrastructure that provides solutions to on-demand, emergency, and normal traffic. We further discuss in-body antenna design and low-power MAC protocol for a WBAN. In addition, we briefly outline some of the WBAN applications with examples. Our discussion realizes a need for new power-efficient solu-tions towards in-body and on-body sensor networks.

Relationship between body surface area and ALT normalization after long-term lamivudine treatment

AIM： To further evaluate the relationship between BSA and the effects of lamivudine in a greater number of cases and over a longer period of observation than in our previous evaluation. METHODS： We evaluated 249 patients with chronic hepatitis B. The effects of treatment for one year （n = 249）, two years （n = 147）, and three years （n = 72） were evaluated from the levels of serum ALT and HBVoDNA, as biological and virological effects （undetectable levels by PCR）, respectively. Moreover, several variables that could influence the response to treatment, including ALT, albumin, bilirubin, platelet counts, BSA, HBVoDNA, and HBeAg were analyzed. RESULTS： For 1-year treatment, multivariate analysis revealed that BSA （P = 0.0002） was the only factor for the biological effect, and that ALT （P = 0.0017）, HBV- DNA （P = 0.0004）, and HBeAg （P = 0.0021） were independent factors for the virological effect. For 2-year treatment, multivariate analysis again showed that BSA （P = 0.0147） was the only factor for the biological effect, and that ALT （P = 0.0192） and HBeAg （P = 0.0428） were independent factors for the virological effect. For 3-year treatment, multivariate analysis, however, could not reveal BSA （P = 0.0730） as a factor for the normalization of ALT levels. CONCLUSION： BSA is a significant predictor for the normalizing the effect of lamivudine therapy on ALT for an initial 2-year period, suggesting that lamivudine dosage should be based on the individual BSA.

Distributed privacy protection strategy for MEC enhanced wireless body area networks

With the rapid development and widespread application of Wireless Body Area Networks(WBANs),the traditional centralized system architecture cannot handle the massive data generated by the edge devices.Meanwhile,in order to ensure the security of physiological privacy data and the identity privacy of patients,this paper presents a privacy protection strategy for Mobile Edge Computing(MEC)enhanced WBANs,which leverages the blockchain-based decentralized MEC paradigm to support efficient transmission of privacy information with low latency,high reliability within a high-demand data security scenario.On this basis,the Merkle tree optimization model is designed to authenticate nodes and to verify the source of physiological data.Furthermore,a hybrid signature algorithm is devised to guarantee the node anonymity with unforgeability,data integrity and reduced delay.The security performance analysis and simulation results show that our proposed strategy not only reduces the delay,but also secures the privacy and transmission of sensitive WBANs data.

Power Allocation for Energy Harvesting in Wireless Body Area Networks

Wireless Body Area Networks(WBANs) are expected to achieve high reliable communications among a large number of sensors.The outage probability can be used to measure the reliability of the WBAN.In this paper,we optimize the outage probability with the harvested energy as constraints.Firstly,the optimal transmit power of the sensor is obtained while considering a single link between an access point(AP) located on the waist and a sensor attached on the wrist over the Rayleigh fading channel.Secondly,an optimization problem is formed to minimize the outage probability.Finally,we convert the non-convex optimization problem into convex solved by the Lagrange multiplier method.Simulations show that the optimization problem is solvable.The outage probability is optimized by performing power allocation at the sensor.And our proposed algorithm achieves minimizing the outage probability when the sensor uses energy harvesting.We also demonstrate that the average outage probability is reduced with the increase of the harvested energy.

Remote Health Monitoring Using IoT-Based Smart Wireless Body Area Network

A wireless body area network(WBAN)consists of tiny healthmonitoring sensors implanted in or placed on the human body.These sensors are used to collect and communicate human medical and physiological data and represent a subset of the Internet of Things(IoT)systems.WBANs are connected to medical servers that monitor patients’health.This type of network can protect critical patients’lives due to the ability to monitor patients’health continuously and remotely.The inter-WBAN communication provides a dynamic environment for patients allowing them to move freely.However,during patient movement,the WBAN patient nodes may become out of range of a remote base station.Hence,to handle this problem,an efficient method for inter-WBAN communication is needed.In this study,a method using a cluster-based routing technique is proposed.In the proposed method,a cluster head(CH)acts as a gateway between the cluster members and the external network,which helps to reduce the network’s overhead.In clustering,the cluster’s lifetime is a vital parameter for network efficiency.Thus,to optimize the CH’s selection process,three evolutionary algorithms are employed,namely,the ant colony optimization(ACO),multi-objective particle swarm optimization(MOPSO),and the comprehensive learning particle swarm optimization(CLPSO).The performance of the proposed method is verified by extensive experiments by varying values of different parameters,including the transmission range,node number,node mobility,and grid size.A comprehensive comparative analysis of the three algorithms is conducted by extensive experiments.The results show that,compared with the other methods,the proposed ACO-based method can form clusters more efficiently and increase network lifetime,thus achieving remarkable network and energy efficiency.The proposed ACO-based technique can also be used in other types of ad-hoc networks as well.

Black Hole and Sink Hole Attack Detection in Wireless Body Area Networks

In Wireless Body Area Networks(WBANs)with respect to health care,sensors are positioned inside the body of an individual to transfer sensed data to a central station periodically.The great challenges posed to healthcare WBANs are the black hole and sink hole attacks.Data from deployed sensor nodes are attracted by sink hole or black hole nodes while grabbing the shortest path.Identifying this issue is quite a challenging task as a small variation in medicine intake may result in a severe illness.This work proposes a hybrid detection framework for attacks by applying a Proportional Coinciding Score(PCS)and an MK-Means algorithm,which is a well-known machine learning technique used to raise attack detection accuracy and decrease computational difficulties while giving treatments for heartache and respiratory issues.First,the gathered training data feature count is reduced through data pre-processing in the PCS.Second,the pre-processed features are sent to the MK-Means algorithm for training the data and promoting classification.Third,certain attack detection measures given by the intrusion detection system,such as the number of data packages trans-received,are identified by the MK-Means algorithm.This study demonstrates that the MK-Means framework yields a high detection accuracy with a low packet loss rate,low communication overhead,and reduced end-to-end delay in the network and improves the accuracy of biomedical data.

A Game Theoretic Approach for Inter-Network Interference Mitigation in Wireless Body Area Networks

Wireless Body Area Network(WBAN) is an emerging technology to provide real-time health monitoring and ubiquitous healthcare services. In many applications, multiple wireless body area networks have to coexist in a small area, resulting in serious inter-network interference. This not only reduces network reliability that is especially important in emergency medical applications, but also consumes more power of WBANs. In this paper, an inter-network interference mitigation approach based on a power control algorithm is proposed. Power control is modeled as a non-cooperative game, in which both inter-network interference and energy efficiency of WBANs are considered. The existence and uniqueness of Nash Equilibrium in the game are proved, and an optimal scheme based on best response is proposed to find its Nash Equilibrium. By coordinating the transmission power levels among networks under interference environment, the total system throughput can be increased with minimum power consumed. The effectiveness of the proposed method has been illustrated by simulation results, where the performance of the proposed approach is evaluated in terms of overall utility and power efficiency and convergence speed.

Priority-based adaptive transmission algorithm for medical devices in wireless body area networks(WBANs)

A wireless body area network offers cost-effective solutions for healthcare infrastructure. An adaptive transmission algorithm is designed to handle channel efficiency, which adjusts packet size according to the difference in feature-point values that indicate biomedical signal characteristics. Furthermore, we propose a priority-adjustment method that enhances quality of service while guaranteeing signal integrity. A large number of simulations were carried out for performance evaluation. We use electrocardiogram and electromyogram signals as reference biomedical signals for performance verification. From the simulation results, we find that the average packet latency of proposed scheme is enhanced by 30% compared to conventional method. The simulation results also demonstrate that the proposed algorithm achieves significant performance improvement in terms of drop rates of high-priority packets around 0.3%-0.9 %.

Body area communication based on quasi-electrostatic field and spread spectrum

Based on the electrical model of body area communication, the change tendency of chan nel gain in 100 kHz 10 MHz band was experimentally analyzed and verified. Results show that chan nel gain was flat and signal attenuation was approximately 43 dB in 1 MHz 10 MHz band. The char acteristics of the channel were taken into account in the design of body area spread spectrum com munication and its multiuser receiver issue. BER Eb/No curves of single user and multiuser were de rived by simulation. The characteristics of body area commutation channel were studied and the fea sibility of introducing spread spectrum theory to body area communication was verified.

Energy-Efficieng MAC Protocols for Wireless Body Area Networks: A Survey

In this paper, we provide a comprehensive survey of key energy-efficient Medium Access Control (MAC) protocols for Wireless Body Area Networks (WBANs). At the outset, we outline the crucial attributes of a good MAC protocol for WBAN. Several sources that contribute to the energy inefficiency of WBAN are identified, and features of the various MAC protocols qualitatively compared. Then, we further investigate some representative TDMA-based energy-efficient MAC protocols for WBAN by emphasizing their strengths and weaknesses. Finally, we conclude with a number of open research issues with regard to WBAN MAC layer.

A pilot study in relationship among changes in visceral fat area, waist circumference and body weight in Japanese freshmen students

We investigated the relationship among delta (delta represents changes in parameters) visceral fat area, waist circumference and body weight in Japanese freshmen students. Visceral fat was measured at the umbilical level using computerized tomography scanning at baseline study and 6 months later. Body weight and height, as well as waist circumference were also measured. We found that visceral fat area, waist circumference, and body weight significantly correlated with each other at baseline, and 6 months later, delta visceral fat area and changes in % visceral fat area significantly correlated with delta waist circumference and delta body weight in female and in total subjects. In addition, based on the predictive linear equations from the regression analysis, we found that 1kg of delta body weight corresponded to 0.83 cm of delta waist circumference, and 1kg of delta body weight and 1cm of delta waist circumference corresponded to 9.41% and 7.80% of changes in visceral fat area, respectively, in total subjects. The present results suggest that delta visceral fat area is closely related to delta body weight and delta waist circumference in Japanese freshmen students.

Design and Analysis of a Compact Band Notch UWB Antenna for Body Area Network

This paper presents the design of a small printed ultra wideband antenna with Band Notched characteristics. Both the free space and on-body performances of this antenna were investigated through simulation. The newly designed UWB antenna is more revised small form factor sized, with the ability to avoid interference caused by WLAN (5.15 - 5.825 GHz) and WiMAX (5.25 - 5.85 GHz) systems with a band notch. The return loss response, gain, radiation pattern on free space of the antenna were investigated. After that, the on-body performances were tested on 3-layer human body model with radiation pattern, gain, return loss, and efficiency at 3.5, 5.7, 8, 10 GHz and all the results were compared with free space results. As the on-body performance was very good, the proposed antenna will be suitable to be used for multi-purpose medical applications and sports performance monitoring.

Error Control Strategy in Ultrasonic Body Area Networks

Recently,ultrasonic waves had been introduced as the transmission medium in Body Area Networks(BANs) to reduce the incalculable damage caused by radio waves. However,the communications based on ultrasonic waves suffer from poor propagation of signals in air and consume too much energy. To address these limitations,firstly,we make the theoretical analysis to ensure ultrasonic waves could be used in BANs(UBANs). Then,we propose an error control strategy in UBANs to dynamically adjust the error control scheme and the Max-Retries based on the current channel state,which is called UECS. The UECS is based on IEEE 802.15.6 standards and considering the characteristics of ultrasonic waves in BANs. Simulation results show that UECS achieves better performance in terms of packet delivery ratio and energy consumption compared with the traditional strategies.

The Effect of the Hemofiltration-Body Surface Area on the Mortality and Morbidity during Cardiopulmonary Bypass

The aim of this study is to investigate the effect of the hemofiltration-body surface area on mortality and morbidity during cardiopulmonary bypass (CBP). A total of 226 patients were divided into two groups as hemofiltration (HF) performed or not performed. The patients to whom hemofiltration was performed were also divided into three subgroups after the distribution analysis which was done according to body surface area. All patients were compared according to the relationship of hemofiltration-body surface area during cardiopulmonary bypass in the interms of mortality and morbidity. There was no statistically significant relationship between the subgroups according to the amount of hemofiltration by square meters (p = 0.818). There was statistically significant difference in total perfusion times and total hospital stay (p = 0.025;p = 0.038) between the subgroups which were divided by the amount of hemofiltration in square meters. As a result, no effect was observed on the mortality of the relationship between the amount of hemofiltration applied during CBP and body surface area.