Biomedical Wireless Sensor Networks Research Articles

Efficient Biomedical Signal Security Algorithm for Smart Internet of Medical Things (IoMTs) Applications

Due to the rapid development of information and emerging communication technologies, developing and implementing solutions in the Internet of Medical Things (IoMTs) field have become relevant. This work developed a novel data security algorithm for deployment in emerging wireless biomedical sensor network (WBSN) and IoMTs applications while exchanging electronic patient folders (EPFs) over unsecured communication channels. These EPF data are collected using wireless biomedical sensors implemented in WBSN and IoMTs applications. Our algorithm is designed to ensure a high level of security for confidential patient information and verify the copyrights of bio-signal records included in the EPFs. The proposed scheme involves the use of Hahn’s discrete orthogonal moments for bio-signal feature vector extraction. Next, confidential patient information with the extracted feature vectors is converted into a QR code. The latter is then encrypted based on a proposed two-dimensional version of the modified chaotic logistic map. To demonstrate the feasibility of our scheme in IoMTs, it was implemented on a low-cost hardware board, namely Raspberry Pi, where the quad-core processors of this board are exploited using parallel computing. The conducted numerical experiments showed, on the one hand, that our scheme is highly secure and provides excellent robustness against common signal-processing attacks (noise, filtering, geometric transformations, compression, etc.). On the other hand, the obtained results demonstrated the fast running of our scheme when it is implemented on the Raspberry Pi board based on parallel computing. Furthermore, the results of the conducted comparisons reflect the superiority of our algorithm in terms of robustness when compared to recent bio-signal copyright protection schemes.

SeizeIT: SEIZURE victims are no longer leashed

Seizure considered to be one of the severe and most common type of neurological disorders. Despite the availability of numerous anti-seizure drugs, it is often difficult to control the disease completely and effectively. Lack of close supervision and failure in providing urgent medical care during and after seizure episodes, leads to serious injuries or even death. On the other hand, Use of wireless sensor networks in everyday applications have rapidly increased due to decreased technology costs and improved product reliability. Therefore developing a wearable device to monitor seizure may complete the anamnesis, help medical staff in diagnosing and acute treatment while preventing seizure related accidents. There are number of seizure detection systems available in the market. Still their performance is far from perfect. This paper explores an application of biomedical wireless sensor networks, which attempts to monitor patients in a completely non-invasive and non-intrusive manner. It describes a wearable device together with seizure prediction and alerting system, which is designed to address some issues with seizure detection systems in the market. Its functional block diagram and operating modes are detailed. Possible application areas of the device are also discussed

Smart Health Care Monitoring System using Light Fidelity and Wireless Biomedical Sensor Network

This paper presents smart health care monitoring using Light Fidelity (Li-Fi) technology and Wireless Biomedical Sensor Networks (WBSNs). The node of each WBSN poised of health care sensors and patient’s health information are transmitted and received using Li-Fi technology. The breathing rate, pulse rate, body temperature and other patient’s body parameters are regularly monitored using WBSNs and Li-Fi based patients monitoring system. The health of the patients cannot be monitored 24X7. Sometimes the health of the patients becomes abnormal in the absence of care taker. For those critical conditions we have proposed a smart health care monitoring system to transfer patient’s records to the observer.

Towards Genetic Cryptography for Biomedical Wireless Sensor Networks Gateways.

The integration of wireless sensor networks into Internet of things, led to a new generation of sensor nodes, directly connected to remote servers, for signal processing and decision making. The migration of data processing from the local node, achieved by decoupling the node hardware from the required processing capabilities, is only possible through implementation of network virtualization. The virtualization which brings new services that are executed remotely has led to security challenges, yet to be resolved, due to the increasing amount of data being continually exchanged between the sensor node hub and remote servers. In this regard, we introduce a novel genetic algorithm for data security with a powerful security architecture that performs one-time key, single block enciphering instead of a block chaining or weak stream enciphering. The algorithm architecture produces variable (stealthy) keys and data that adopt the white noise statistical behavior, therefore, having high immunity to cryptanalysis. The algorithm combines gene fusion and horizontal gene transfer inspired from the spread of antibiotic resistance in bacteria. A salt extracted from the data block hash value adds the stealthy-key feature to the cipher. In fact, the avalanche effect for a block of encrypted sensors data of 16×16B achieves an average of 98% with a single bit flipped in the data. An application in biomedical WSN/IoT with simulation and experimental results is presented.

Wireless Biomedical Sensor Networks: A technology review

Wireless Biomedical Sensor Networks: A technology review

Smart context-aware QoS-based admission control for biomedical wireless sensor networks

Wireless sensor networks are being used as the enabling technology that helps to support the development of new applications and services targeting the domain of healthcare, in particular, regarding data collection for continuous health monitoring of patients or to help physicians in their diagnosis and further treatment assessment. Therefore, due to the critical nature of both medical data and medical applications, such networks have to satisfy demanding quality of service requirements. Despite the efforts made in the last few years to develop quality of service mechanisms targeting wireless sensor networks and its wide range of applications, the network deployment scenario can severely restrict the network's ability to provide the required performance. Furthermore, the impact of such environments on the network performance is hard to predict and manage due to its random nature. In this way, network planning and management, in complex environments like general or step-down hospital units, is a problem still looking for a solution. In such context, this paper presents a smart context-aware quality of service based admission control method to help engineers, network administrators, and healthcare professionals managing and supervising the admission of new patients to biomedical wireless sensor networks. The proposed method was tested in a small sized hospital. In view of the results achieved during the experiments, the proposed admission control method demonstrated its ability, not only to control the admission of new patients to the biomedical wireless sensor network, but also to find the best location to admit the new patients within the network. By placing the new sensor nodes on the most favourable locations, this method is able to select the network topology in view of mitigating the quality of service provided by the network.

Low Voltage Charge Pump for RF Energy Harvesting Applications

Objective: As the need for energy increases, new technologies should replace the conventional energy resources. Energy harvesting is one of these technologies and finds applications in many areas such as wireless sensor networks, biomedical applications. Findings: This paper presents a low-voltage charge pump which works at input voltage as small as 100 mV and is suitable for wireless energy harvesting applications. With 100 mV input, the proposed charge pump provides an output of 1.05 V. This output voltage is adequate for charging low power devices for biomedical applications and wireless sensor networks. Novelty/Improvement: The proposed charge pump has the voltage conversion ratio (M) greater than 10 and the circuit does not need any start-up voltage mechanisms for the operations. Method/Analysis: The result presented in this work is based on extensive simulation on SPICE and are experimentally validated CNFET model of Stanford University.

Q-Learning-Based Optimized Routing in Biomedical Wireless Sensor Networks

ABSTRACTThe information regarding any abnormal behaviour in the physiological parameters of a patient should reach the remote healthcare personal immediately in real time, so as to take corrective action promptly and save the life. Biomedical wireless sensor network (BWSN) plays a vital role in this connection because it can be attached to the patient without causing any inconvenience to him/her and can communicate to any remote healthcare office without any delay. BWSN consists of individual nodes to collect the patient's information and communicate it to the remote health centre if the value of sensed signal is beyond normal range. The nodes deployed within the patients form a BWSN, and the network has to send the information from the source to the remote sink in an efficient way. The network should choose an optimized path for this communication, so that the node’s lifetime is increased. This paper presents a Q-learning-algorithm-based routing concept to route the sensed information if required from the individual node to the remote healthcare station. Simulations are made with a set of mobile biomedical wireless sensor nodes within an area of 100 m × 100 m flat space operating for 600 seconds of simulation time. Results show that the Q-learning-based approach requires less time to route the packet from the source node to the destination remote station.

Extending Lifetime of Biomedical Wireless Sensor Networks using Energy-Aware Routing and Relay Nodes

Biomedical wireless sensor networks are a key technology to enable the development of new healthcare services and/or applications, reducing costs and improving the citizen's quality of life. However, since they deal with health data, such networks should implement mechanisms to enforce high levels of quality of service. In most cases, the sensor nodes that form such networks are small and battery powered, and these extra quality of service mechanisms mean significant lifetime reduction due to the extra energy consumption. The network lifetime is thus a relevant feature to ensure the necessary quality of service requirements. In order to maximise the network lifetime, and its ability to offer the required quality of service, new strategies are needed to increase the energy efficiency, and balance in the network. The focus of this work goes to the effective use of the available energy in each node, combined with information about the reliability of the wireless links, as a metric to form reliable and energy-aware routes throughout the network. This paper present and discusses two different deployment strategies using energy-aware routing and relay nodes, assessed for different logical topologies. The authors' conclusion is that the use of energy-aware routing combined with strategic placed relay nodes my increase the network lifetime as high as 45%.

Designing a WSN Data Format for WLAN and Cellular Network Compatibility in an E-healthcare Framework

The emergence of wireless sensor networks (WSNs) has powerful results on various areas of applications such as medicine and healthcare, air pollution detection, fire detection, water quality monitoring etc. Wireless biomedical sensor networks can supply non-obstructive , long-time, and real-time medical convoy for the chronic patients. The use of wireless medical sensor networks on a large scale can successfully minimize the maximum workloads for the technically growing society and prolonged health service for the chronically ill patients. It also reduces the possibility of errors caused by human. For this there is a need for a variety of types of data to be collected and sent to the sink for processing and diagnosis. In addition there may be heterogeneity in the types of devices which are participating in the network. Here author presents a Zigbee based Ehealthcare framework which will provide seamless support to patients from far off or rural areas. Here also proposed a data format to be captured in WSNs that will be compatible in WLANs as well as in the cellular networks which will collect data from the patients. General Terms Sensor Network, Clustering Technique, E-healthcare System.

QoS-based management of biomedical wireless sensor networks for patient monitoring

Biomedical wireless sensor networks are a key technology to support the development of new applications and services targeting patient monitoring, in particular, regarding data collection for medical diagnosis and continuous health assessment. However, due to the critical nature of medical applications, such networks have to satisfy demanding quality of service requirements, while guaranteeing high levels of confidence and reliability. Such goals are influenced by several factors, where the network topology, the limited throughput, and the characteristics and dynamics of the surrounding environment are of major importance. Harsh environments, as hospital facilities, can compromise the radio frequency communications and, consequently, the network’s ability to provide the quality of service required by medical applications. Furthermore, the impact of such environments on the network’s performance is hard to manage due to its random and unpredictable nature. Consequently, network planning and management, in general or step-down hospital units, is a very hard task. In such context, this work presents a quality of service based management tool to help healthcare professionals supervising the network’s performance and to assist them managing the admission of new sensor nodes (i.e., patients to be monitored) to the biomedical wireless sensor network. The proposed solution proves to be a valuable tool both, to detect and classify potential harmful variations in the quality of service provided by the network, avoiding its degradation to levels where the biomedical signs would be useless; and to manage the admission of new patients to the network.

Energy-aware routing for biomedical wireless sensor networks

Available wireless sensor networks targeting the domain of healthcare enables the development of new applications and services in the context of E-Health. Such networks play an important role in several scenarios of patient monitoring, particularly those where data collection is vital for diagnosis and/or research purposes. However, despite emerging solutions, wearable sensors still depend on users' acceptance. One proposed solution to improve wearability relies on the use of smaller sensing nodes, requiring more energy-efficient networks, due to smaller room available for energy sources. In such context, smaller wireless sensor network nodes are required to work long time periods without human intervention and, at the same time, to provide appropriate levels of reliability and quality of service. Satisfaction of these two goals depends on several key factors, such as the routing protocol, the network topology, and energy efficiency. This paper offers a solution to increase the network lifetime based on a new Energy-Aware Objective Function used to design a Routing Protocol for Low-Power and Lossy Networks. The proposed Objective Function uses the Expected Transmission Count Metric and the Remaining Energy on each sensor node to compute the best paths to route data packets across the network. When compared with state of the art solutions, the proposed method increases the network lifetime by 21% and reduces the peaks of energy consumption by 12%. In this way, wireless sensor network nodes wearability can be improved, making them smaller and lighter, while maintaining the required performance.

A Prioritization Based Congestion Control Protocol for Healthcare Monitoring Application in Wireless Sensor Networks

Recent developments in biosensor and wireless technology have led to a rapid progress in wearable real time health monitoring. Unlike wired networks, wireless networks are subject to more packet loss and congestion. In this paper, we propose a congestion control and service prioritization protocol for real time monitoring of patients' vital signs using wireless biomedical sensor networks. The proposed system is able to discriminate between physiological signals and assign them different priorities. Thus, it would be possible to provide a better quality of service for transmitting highly important vital signs. Congestion control is performed by considering both the congestion situation in the parent node and the priority of the child nodes in assigning network bandwidth to signals from different patients. Given the dynamic nature of patients' health conditions, the proposed system can detect an anomaly in the received vital signs from a patient and hence assign more priority to patients in need. Simulation results confirm the superior performance of the proposed protocol. To our knowledge, this is the first attempt at a special-purpose congestion control protocol specifically designed for wireless biosensor networks.

Optimised priority assignment mechanism for biomedical wireless sensor networks

Biomedical wireless sensor networks (BWSNs) need to guarantee reliable and timely transfer of crucial data in emergency and time critical situations. Current schemes use static/fixed priority assignment mechanism based on source of data and not on the urgency of the data in different situations. This study presents a novel data transmission scheme, called optimised priority assignment mechanism (OPAM) for BWSNs. The proposed work dynamically schedule different types of data flows based on their time critical nature. It smartly assigns priority to individual data packets rather to particular service or flow by continuously monitoring queuing delay providing guaranteed end-to-end quality of service (QoS) without invoking any congestion control and avoidance mechanism. Experimental results show that OPAM performs better in terms of average throughput and end-to-end delay 55 and 20.5%, respectively, than routing service framework for standard BWSNs.

Energy-Efficiency Analysis of a Distributed Queuing Medium Access Control Protocol for Biomedical Wireless Sensor Networks in Saturation Conditions

The aging population and the high quality of life expectations in our society lead to the need of more efficient and affordable healthcare solutions. For this reason, this paper aims for the optimization of Medium Access Control (MAC) protocols for biomedical wireless sensor networks or wireless Body Sensor Networks (BSNs). The hereby presented schemes always have in mind the efficient management of channel resources and the overall minimization of sensors’ energy consumption in order to prolong sensors’ battery life. The fact that the IEEE 802.15.4 MAC does not fully satisfy BSN requirements highlights the need for the design of new scalable MAC solutions, which guarantee low-power consumption to the maximum number of body sensors in high density areas (i.e., in saturation conditions). In order to emphasize IEEE 802.15.4 MAC limitations, this article presents a detailed overview of this de facto standard for Wireless Sensor Networks (WSNs), which serves as a link for the introduction and initial description of our here proposed Distributed Queuing (DQ) MAC protocol for BSN scenarios. Within this framework, an extensive DQ MAC energy-consumption analysis in saturation conditions is presented to be able to evaluate its performance in relation to IEEE 802.5.4 MAC in highly dense BSNs. The obtained results show that the proposed scheme outperforms IEEE 802.15.4 MAC in average energy consumption per information bit, thus providing a better overall performance that scales appropriately to BSNs under high traffic conditions. These benefits are obtained by eliminating back-off periods and collisions in data packet transmissions, while minimizing the control overhead.

Multi-purpose healthcare telemedicine system with ISM band communication link support

Rapid advances in information technology and telecommunications, and more specifically wireless and mobile communications are leading to the emergence of a new type of information infrastructure that has the potential of supporting an array of advanced services for healthcare. This paper developed a wireless biomedical sensor network prototype system based on Industrial, Scientific and Medical (ISM) band for healthcare. It offers flexibility and mobility to save cost and energy spent on wiring. The framework hardware and software structure, related programming, the accuracy of the system and an optimisation of power consumption are also discussed in this paper.