Body Sensor Nodes Research Articles

A Secured IoT Based Advanced Health Care System for Medical Field using Sensor Network

In day to day life health awareness and controlling system is important to monitor those patient’s physiological parameters frequently. In the recent health awareness environment those usage of IOT innovation organization acquires accommodation of professionals and also patients, since they are connected to different medical fields. A sensor node needs to be arranged on the apparent of the patient body will gather the entire signal from those wireless sensor and also send them of the body sensor node. Those connected sensor nodes on the patient’s body can make in the structure of a wireless body sensor network furthermore they have the capacity with sense those heart beat rate, temperature of surroundings. That basic focus to this system may be on transmitting the individuals’ patient’s health watching parameters through wireless communication in crucial conditions. We propose a secure IOT built health awareness monitoring and will check that saline level of the patient.

Wireless Body Area Networks MAC Protocol For Energy Efficiency and Extending Lifetime

Wireless body area networks (WBANs), as an important part of the Internet of things and sensor networks, are becoming more important in health monitoring and entertainment services. The sensor nodes in these applications need to transmit information data to personal station and receive control information from personal station to adjust working modes. However, unlike an easily rechargeable personal station, body sensor nodes suffer from energy shortages, which affect the nodes lifetimes. To solve this problem, we design a novel medium access control (MAC) layer protocol to enhance the energy efficiency and extend the lifetime of body sensor nodes in WBANs. The proposed protocol utilizes a hybrid scheme by taking advantage of carrier-sense multiple accesses with the collision avoidance and time division multiple access schemes. In addition, we allocate the main transmission overhead at the personal station side and design a novel awaiting order state for sensor nodes to improve energy efficiency. Also, the analysis and simulation results demonstrate that the proposed protocol can provide a 6 to 15 decrease in energy consumption from other protocols.

A Joint Transmission Power Control and Duty-Cycle Approach for Smart Healthcare System

Emerging revolution in the healthcare has caught the attention of both the industry and academia due to the rapid proliferation in the wearable devices and innovative techniques. In the mean-time, body sensor networks (BSNs) have become the potential candidate in transforming the entire landscape of the medical world. However, large battery lifetime and less power drain are very vital for these resource-constrained sensor devices while collecting the bio signals. Hence, minimizing their charge and energy depletions are still very challenging tasks. It is examined through large real-time data sets that due to the dynamic nature of the wireless channel, the traditional predictive transmission power control (TPC) and a constant transmission power techniques are no more supportive and potential candidates for BSNs. Thus, this paper first proposes a novel joint TPC and duty-cycle adaptation-based framework for pervasive healthcare. Second, an adaptive energy-efficient transmission power control algorithm is developed by adapting the temporal variation in the on-body wireless channel amid static (i.e., standing and walking at a constant speed) and dynamic (i.e., running) body postures. Third, a feedback control-based duty-cycle algorithm is proposed for adjusting the execution period of tasks (i.e., sensing and transmission). Fourth, system-level battery and energy harvesting models are proposed for body sensor nodes by examining the energy depletion of sensing and transmission tasks. It is validated through Monte Carlo experimental analysis that the proposed algorithm saves more energy of 11.5% with reasonable packet loss ratio by adjusting both the transmission power and the duty cycle unlike the conventional constant TPC and PTPC methods.

Ultra-low power m-sequence code generator for body sensor node applications

In this paper, a design of low power m-sequence code generator is proposed. The efficiency of producing the code sequence within the region of sub-threshold voltage is investigated using 90nm technology and verified using the auto-correlation and eye diagram characterizations. A further method of power saving in addition to voltage reduction is carried out by scaling the technology node from 90 to 65nm. A comparison of power consumption and maximum attainable frequency between both technologies is performed. The ratio of power saving while using 65nm technology is ranging from 45% to 55% for the three different code lengths investigated.

A Noise-Power-Area Optimized Biosensing Front End for Wireless Body Sensor Nodes and Medical Implantable Devices

In this paper, we present a noise, power, and area efficient biosensing front-end application specified integrated circuit (ASIC) for the next-generation wireless body sensor nodes and implantable devices. We identify the key design parameter tradeoffs in the biomedical recording systems and carry out a thorough analysis and optimization to maximize them. Based on our analysis and optimization of the front end, we propose a design methodology for the recording channel that is applicable to various biomedical applications. The ASIC is implemented in a 0.18- $\mu \text{m}$ CMOS process to validate our optimization methodology. The ASIC is reconfigurable to accommodate various biopotentials with the high-pass and low-pass cutoff frequencies being 0.5–300 Hz and 150 Hz–10 kHz, respectively. The low-pass cutoff is provided by an ultralow power $G_{m}$ - ${C}$ low-pass filter, which also acts as an antialiasing filter for the switching-optimized 10-b successive approximation register (SAR) analog-to-digital converter (ADC). The analog front end (AFE) gain is also programmable from 38 to 72 dB. A comprehensive power management unit provides the power supply, multiple reference voltages, and bias currents to the entire chip. The AFE and ADC dissipate only $5.74~\mu \text{W}$ and 306 nW from the on-chip regulators, respectively. The measured input-referred noise is $2.98~\mu \text{V}_{{\text {rms}}}$ , resulting in the noise efficiency factor and power efficiency factor equals 2.6 and 9.46, respectively. The active area of the AFE is 0.0228 mm2. We verify the chip functionality in a number of in vivo and ex vivo biological experiments.

HEAL-WEAR: An Ultra-Low Power Heterogeneous System for Bio-Signal Analysis

Personalized healthcare devices enable low-cost, unobtrusive and long-term acquisition of clinically relevant biosignals. These appliances, termed wireless body sensor nodes (WBSNs), are fostering a revolution in health monitoring for patients affected by chronic ailments. Nowadays, WBSNs often embed complex digital processing routines, which must be performed within an extremely tight energy budget. Addressing this challenge, in this paper, we introduce a novel computing architecture devoted to the ultra-low power analysis of biosignals. Its heterogeneous structure comprises multiple processors interfaced with a shared acceleration resource, implemented as a coarse-grained reconfigurable array (CGRA). The CGRA mesh effectively supports the execution of the intensive loops that characterize biosignal analysis applications, while requiring a low reconfiguration overhead. Moreover, both the processors and the reconfigurable fabric feature single-instruction/multiple data (SIMD) execution modes to increase efficiency when multiple data streams are concurrently processed. The run-time behavior on the system is orchestrated by a lightweight hardware mechanism, which concurrently synchronizes processors for SIMD execution and regulates access to the reconfigurable accelerator. By jointly leveraging run-time reconfiguration and SIMD execution, the illustrated heterogeneous system achieves, when executing complex biosignal analysis applications, speedups of up to $11.3\times $ on the considered kernels and up to 37.2% overall energy savings, with respect to an ultra-low power multi-core platform, which does not feature CGRA acceleration.

EHDC: An Energy Harvesting Modeling and Profiling Platform for Body Sensor Networks.

Energy harvesting is a promising solution to the limited battery lifetimes of body sensor nodes. Self-powered sensor systems capable of quasi-perpetual operation enable the possibility of truly continuous monitoring of patients beyond the clinic. However, the discontinuous and dynamic characteristics of harvesting in real-world scenarios-and their implications for the design and operation of self-powered systems-are not yet well understood. This paper presents a mobile energy harvesting and data collection (EHDC) platform designed to provide a deeper understanding of energy harvesting dynamics. The EHDC platform monitors and records the instantaneous usable power generated by body-worn harvesters, while also collecting human activity and environmental data to provide a comprehensive real-world evaluation of two energy harvesting modalities common to body sensor networks: solar and thermoelectric. The platform was initially validated with benchtop tests and later with real-world deployments on two subjects. 7-h-long multimodal energy harvesting profiles were generated, and the environmental and behavioral data were used to expand upon previously developed Kalman filter based mathematical models for energy harvesting prediction. Results confirm the validity of the EHDC platform and harvesting models, establishing the potential for longer term monitoring of energy harvesting characteristics; thus, informing the design and operation of self-powered body sensor networks.

Beta-Decrement of Contention Probability to Enhance Both Fairness and Throughput in IEEE 802.15.6 Slotted Aloha Algorithm

The IEEE 802.15.6 slotted Aloha based protocol for wireless body area network includes contention based medium access control to accommodate heterogeneous body sensor nodes. Current protocol has been designed to handle incoming packets from sensors having different priorities but per class throughput degrades as the number of competing nodes increases. An improved algorithm is suggested to handle not only the throughput issue but also the starvation issue in saturated conditions. Simulation results validates the suggested algorithm.

A Synchronization-Based Hybrid-Memory Multi-Core Architecture for Energy-Efficient Biomedical Signal Processing

In the last decade, improvements on technology scaling have enabled the design of a novel generation of wearable bio-sensing monitors. These smart Wireless Body Sensor Nodes (WBSNs) are able to acquire and process biological signals, such as electrocardiograms, for periods of time extending from hours to days. The energy required for the on-node digital signal processing (DSP) is a crucial limiting factor in the conception of these devices. To address this design challenge, we introduce a domain-specific ultra-low power (ULP) architecture dedicated to bio-signal processing. The platform features a light-weight strategy to support different operating modes and synchronization among cores. Our approach effectively reduces the power consumption, harnessing the intrinsic parallelism and the workload requirements characterizing the target domain. Operations at low voltage levels are supported by a heterogeneous memory subsystem comprising a standard-cell based ultra-low voltage reliable partition. Experimental results show that, when executing real-world bio-signal DSP applications, a state-of-the-art multi-core architecture can improve its energy efficiency in up to 50 percent by utilizing our proposed approach, outperforming traditional single-core alternatives.

Vertical Handover Algorithm for WBANs in Ubiquitous Healthcare with Quality of Service Guarantees

Recently, Wireless Body Area Networks (WBANs) have become an emerging technology in healthcare, where patients are equipped withwearable and implantable body sensor nodes to gather sensory information for remote monitoring. The increasing development of coordinator devices on patients enables the internetworking of WBANs in heterogeneous wireless networks to deliver physiological information that is collected at remote terminals in a timely fashion. However, in this type of network, providing a seamless handover with a guaranteed Quality of Service (QoS), especially emergency services, is a challenging task. In this paper, we proposed an effective Multi-Attribute Decision-Making (MADM) handover algorithm that guarantees seamless connectivity. A patient’s mobile devices automatically connect to the best network that fulfills the QoS requirements of different types of applications. Additionally, we integrated a Content-Centric Networking (CCN) processing module into different wireless networks to reduce packet loss, enhance QoS and avoid unnecessary handovers by leveraging in-network caching to achieve efficient content dissemination for ubiquitous healthcare. Simulation results proved that our proposed approach forthe model with CCN outperforms the model without CCN and Received Signal Strength Vertical Handoff (RSS-VHD) in terms of the number of handovers, enhancing QoS, packet loss, and energy efficiency.

An inductor-based converter with EMI reduction for low-voltage thermoelectric energy harvesting

ABSTRACTThis paper presents a self-powered inductor-based converter which harvests thermoelectric energy and boosts extremely low voltage to a typical voltage level for supplying body sensor nodes. Electromagnetic interference (EMI) of the converter is reduced by spreading spectrum of fundamental frequency and harmonics via pseudo-random modulation, which is obtained via combining the linear feedback shift register and digitally controlled oscillator. Besides, the methods, namely extracting energy near MPP and reducing the power dissipation, are employed to improve the power efficiency. The presented inductor-based converter is designed and verified in CSMC CMOS 0.18-µm 1P6M process. The results reveal that it achieves the high efficiency and EMI reduction at the same time.

High-Efficient Energy Harvester With Flexible Solar Panel for a Wearable Sensor Device

This paper proposes an optimal energy harvester (OEH) that uses a flexible photovoltaic (FPV) module to prolong battery life for a wearable body sensor node under indoor and outdoor conditions. The proposed sensor node uses a Bluetooth low-energy module, which consumes low power to wirelessly communicate with mobile devices for monitoring vital signals. A 19 cm $\times4$ cm FPV module that can easily conform to human body contours is used for generating a peak-power of up to 500 mW to charge the battery in outdoor environments. To optimize the power collected under various irradiances, the OEH is designed with a boost circuit for harvesting the low energy available indoors and a maximum power point tracker for collecting the high energy that is available outdoors. The booster can operate within a wide input voltage range of 0.65–3 V to generate a stable output voltage of 3.3 V, and it has a high conversion efficiency of ~95%. The MPPT uses fuzzy inference engine to find the MPP of the FPV that is required to power the system. The results of our experiment show that the proposed device can prolong the lifetime by up to 950% under an irradiance of only 2.9 mW/cm2, and the proposed node becomes an autonomous node under partial shading and sunlight conditions. Therefore, this paper can provide a useful solution for extending the lifetime of wearable sensor devices.

Guest Editorial

Guest Editorial

Secure anonymous mutual authentication for star two-tier wireless body area networks

Background and objectivesMutual authentication is a very important service that must be established between sensor nodes in wireless body area network (WBAN) to ensure the originality and integrity of the patient's data sent by sensors distributed on different parts of the body. However, mutual authentication service is not enough. An adversary can benefit from monitoring the traffic and knowing which sensor is in transmission of patient's data. Observing the traffic (even without disclosing the context) and knowing its origin, it can reveal to the adversary information about the patient's medical conditions. Therefore, anonymity of the communicating sensors is an important service as well. Few works have been conducted in the area of mutual authentication among sensor nodes in WBAN. However, none of them has considered anonymity among body sensor nodes. Up to our knowledge, our protocol is the first attempt to consider this service in a two-tier WBAN. We propose a new secure protocol to realize anonymous mutual authentication and confidential transmission for star two-tier WBAN topology. MethodsThe proposed protocol uses simple cryptographic primitives. We prove the security of the proposed protocol using the widely-accepted Burrows-Abadi-Needham (BAN) logic, and also through rigorous informal security analysis. In addition, to demonstrate the practicality of our protocol, we evaluate it using NS-2 simulator. ResultsBAN logic and informal security analysis prove that our proposed protocol achieves the necessary security requirements and goals of an authentication service. The simulation results show the impact on the various network parameters, such as end-to-end delay and throughput. The nodes in the network require to store few hundred bits. Nodes require to perform very few hash invocations, which are computationally very efficient. The communication cost of the proposed protocol is few hundred bits in one round of communication. Due to the low computation cost, the energy consumed by the nodes is also low. ConclusionsOur proposed protocol is a lightweight anonymous mutually authentication protocol to mutually authenticate the sensor nodes with the controller node (hub) in a star two-tier WBAN topology. Results show that our protocol proves efficiency over previously proposed protocols and at the same time, achieves the necessary security requirements for a secure anonymous mutual authentication scheme.

Efficient self‐powered convertor with digitally controlled oscillator‐based adaptive maximum power point tracking and RF kick‐start for ultralow‐voltage thermoelectric energy harvesting

A self-powered convertor for thermoelectric energy harvesting in body sensor nodes (BSNs) is designed to boost extremely low voltage to the typical supply voltage of BSNs. An adaptive maximum power point tracking (MPPT) based on digitally controlled oscillator (DCO) is achieved by adjusting the switching frequency according to the relation between the half open-circuit voltage of thermoelectric generator and the equivalent voltage. DCO exhibits small line sensitivity and temperature coefficient (TC). Radio frequency (RF) kick-start based on a self-synchronous rectifier is introduced to achieve the no-battery effect. A modified zero current switching based on the common-gate comparator is utilised to decrease the power dissipation of power metal–oxide–semiconductor field-effect transistors. In addition, the power dissipation of the main blocks is reduced by discontinuing the clocked and common-gate comparators after comparison in each cycle, and by making most transistors of DCO and the complementary metal-oxide-semiconductor (CMOS) voltage reference work in the weak inversion or linear region. The zero TC principle of the CMOS voltage reference is extended to all process. The novel convertor is designed and verified in Central Semiconductor Manufacturing Corporation CMOS 0.18 µm process. The results reveal that it achieves adaptive MPPT without battery and exhibits a peak end-to-end efficiency of about 63%.

An Implementation of Wireless Body Area Networks for Improving Priority Data Transmission Delay.

The rapid growth of wireless sensor networks has enabled the human health monitoring of patients using body sensor nodes that gather and evaluate human body parameters and movements. This study describes both simulation model and implementation of a new traffic sensitive wireless body area network by using non-preemptive priority queue discipline. A wireless body area network implementation employing TDMA is designed with three different priorities of data traffics. Besides, a coordinator node having the non-preemptive priority queue is performed in this study. We have also developed, modeled and simulated example network scenarios by using the Riverbed Modeler simulation software with the purpose of verifying the implementation results. The simulation results obtained under various network load conditions are consistent with the implementation results.

QoS-Aware Energy Management in Body Sensor Nodes Powered by Human Energy Harvesting

Harvesting energy in the human environment has been identified as an effective way to charge the body sensor nodes in wireless body area networks (WBANs). In such networks, the capability of the nodes to detect events is of vital importance and complements the stringent quality of service (QoS) demands in terms of delay, throughput, and packet loss. However, the scarce energy collected by human motions, along with the strict requirements of vital health signals in terms of QoS, raises important challenges for WBANs and stresses the need for new integrated QoS-aware energy management schemes. In this paper, we propose a joint power-QoS (PEH-QoS) control scheme, composed of three modules that interact in order to make optimal use of energy and achieve the best possible QoS. The proposed scheme ensures that a sensor node is able to detect the medical events and transmit the respective data packets efficiently. Extensive simulations, conducted for different human activities (i.e., relaxing, walking, running, and cycling), have shown that the application of PEH-QoS in a medical node increases the detection efficiency, the throughput, and the energy efficiency of the system.

Performance Analysis of the Physical and Medium Access Control Layer Parameters with Effect of Varying Transmission Power Using IEEE 802.15.4 Standard for Wireless Body Sensor Networks

Wireless Body Area Network (WBAN) consists of miniaturized, tiny, low power body sensor nodes communicating with a BAN (Body Area Node) Coordinator through Radio Frequency (RF) interface link. Recent advancements in the field of Information, Communication and microelectronics have led to the realization of WBAN, which will help in hazardous, long term health monitoring especially for elderly people. Most of the present day's Body Area Network node's MAC/PHY protocols are built using IEEE 802.15.4 and ZigBee standard. This standard will surely make an impact through its improvisation especially in MAC/PHY layers in the days to come. Already researchers have been working on the new WBAN standard. This paper emphasizes the basic structure of IEEE 802.15.5 MAC/PHY layers through experimentation on 7 specific, static body sensor nodes placed at appropriate points on the human body transmitting heterogeneous data using Time division multiple access and Contention access period of CSMA/CA protocol. The body area channels are considered with temporal and fixed path loss values. Physical layer parameters such as latency and fade depth distribution, MAC packets received and breakdown packets of MAC layer are presented. Packet with respect to the unique and useful parameters, packet received from Media Access Control layer of each node under various conditions of the channel and with Carrier Sense Multiple Access/Collision Avoidance comparing with Time Division Multiple Access techniques. Experimental results show that a transmitting-12dBm to -15dBm was found to be suitable for energy efficient WBAN system. For TDMA scheme, the algorithm may be fine-tuned to reduce the number of packet failure which improves the energy efficiency for any kind of channel.

From Micro to Nano: The Evolution of Wireless Sensor-Based Health Care.

Over the past decade, embedded systems and microelectromechanical systems have evolved in a radical way, redefining our standard of living and enhancing the quality of life. Health care, among various other fields, has benefited vastly from this technological development. The concept of using sensors for health care purposes originated in the late 1980s when sensors were developed to measure certain physiological parameters associated with the human body. In traditional sensor nodes, the signal sources are mostly different environmental phenomena (such as temperature, vibration, and luminosity) or man-made events (such as intrusion and mobile target tracking), whereas in case of the physiological sensors, the signal source is living human tissue. These sensor nodes, as their primary sensing element, have a diaphragm that converts pressure into displacement. This displacement, in turn, is subsequently transformed into an electrical signal. The concept of wireless physiological sensor nodes, however, gained popularity in the mid-2000s, with the sensed data from the nodes transmitted to the hub via a wireless medium. The network formed by this heterogeneous set of wireless body sensor nodes is termed a wireless body-area network (WBAN). Each WBAN is essentially a composition of multiple wireless body sensor nodes and a single hub. The hub is primarily responsible for acquisition of the raw sensed data from all the component sensor nodes and first-level aggregation of the data before transmitting the aggregated data for further analysis to a remote data acquisition center. Here, we outline the evolution of WBANs in the context of modern health care and its convergence with nanotechnology.

A $24\,\mu \text{W}$, Batteryless, Crystal-free, Multinode Synchronized SoC “Bionode” for Wireless Prosthesis Control

We present a batteryless, crystal-free, time division multiple access (TDMA) synchronized multinode wireless body sensor node (WBSN) system-on-chip (SoC), referred to as a Bionode, for continuous and real-time telemetry of electromyograms (EMGs), enabling intuitive upper limb prosthesis control by an amputee. The SoC utilizes state of the art in supercapacitive RF energy harvesting, biosensing analog-front-end, switching-optimized SAR ADC, ultra-low-power RF transceiver, and clock circuits. The sensor node SoCs are time synchronized with a base station, mounted on the prosthetic arm, by using the ultra-low-power TDMA controller and receiver, and the digital core circuits. A 915 MHz broadcast RF signal is utilized to synthesize the carrier frequency of the transmitter. This along with the process and voltage compensated on-chip clock obviates the need for a bulky crystal oscillator, thus providing a low-cost and highly integrated solution to the WBSNs. The SoC is verified by capturing the EMG data from a healthy human body and consumes only $24\;{\upmu}\text{W}$ , while operating exclusively from the harvested RF energy. Implemented in a $0.18\;{\upmu}\text{m}$ CMOS process, the SoC occupies $2.025\;{\text {mm}}^{2}$ silicon area. The sensor node has an extremely low weight and physical dimensions, thanks to the flexible carbon nanotube (CNT) supercapacitor, electrically small antenna (ESA), and crystal-free operation of the SoC.