Body area network

Last updated December 13, 2024

A body area network (BAN), also referred to as a wireless body area network (WBAN), a body sensor network (BSN) or a medical body area network (MBAN), is a wireless network of wearable computing devices.^[1]^[2]^[3]^[4]^[5] BAN devices may be embedded inside the body as implants or pills,^[6] may be surface-mounted on the body in a fixed position, or may be accompanied devices which humans can carry in different positions, such as in clothes pockets, by hand, or in various bags.^[7] Devices are becoming smaller, especially in body area networks. These networks include multiple small body sensor units (BSUs) and a single central unit (BCU).^[8] Despite this trend, decimeter (tab and pad) sized smart devices still play an important role. They act as data hubs or gateways and provide a user interface for viewing and managing BAN applications on the spot. The development of WBAN technology started around 1995 around the idea of using wireless personal area network (WPAN) technologies to implement communications on, near, and around the human body. About six years later, the term "BAN" came to refer to systems where communication is entirely within, on, and in the immediate proximity of a human body.^[9]^[10] A WBAN system can use WPAN wireless technologies as gateways to reach longer ranges. Through gateway devices, it is possible to connect the wearable devices on the human body to the internet. This way, medical professionals can access patient data online using the internet independent of the patient location.^[11]

Concept

The rapid growth in physiological sensors, low-power integrated circuits, and wireless communication has enabled a new generation of wireless sensor networks, now used for purposes such as monitoring traffic, crops, infrastructure, and health. The body area network field is an interdisciplinary area which could allow inexpensive and continuous health monitoring with real-time updates of medical records through the Internet. A number of intelligent physiological sensors can be integrated into a wearable wireless body area network, which can be used for computer-assisted rehabilitation or early detection of medical conditions. This area relies on the feasibility of implanting very small biosensors inside the human body that are comfortable and that don't impair normal activities. The implanted sensors in the human body will collect various physiological changes in order to monitor the patient's health status no matter their location. The information will be transmitted wirelessly to an external processing unit. This device will instantly transmit all information in real time to the doctors throughout the world. If an emergency is detected, the physicians will immediately inform the patient through the computer system by sending appropriate messages or alarms. Currently, the level of information provided and energy resources capable of powering the sensors are limiting. While the technology is still in its primitive stage it is being widely researched and once adopted, is expected to be a breakthrough invention in healthcare, leading to concepts like telemedicine and MHealth becoming real.

Applications

Initial applications of BANs are expected to appear primarily in the healthcare domain, especially for continuous monitoring and logging vital parameters of patients with chronic diseases such as diabetes, asthma and heart attacks.

A BAN in place on a patient can alert the hospital, even before they have a heart attack, through measuring changes in their vital signs.
A BAN on a patient with diabetes could auto inject insulin through a pump, as soon as their blood-sugar levels increase.
A BAN can be used, to learn the underlying health state transitions and dynamics of a disease ^[5]

Other applications of this technology include sports, military, or security. Extending the technology to new areas could also assist communication by seamless exchanges of information between individuals, or between individuals and machines.

Standards

The latest international standard for BANs is the IEEE 802.15.6 standard.^[12]

Components

A typical BAN or BSN requires vital sign monitoring sensors, motion detectors (through accelerometers) to help identify the location of the monitored individual and some form of communication, to transmit vital sign and motion readings to medical practitioners or care givers. A typical body area network kit will consist of sensors, a Processor, a transceiver and a battery. Physiological sensors, such as ECG and SpO2 sensors, have been developed. Other sensors such as a blood pressure sensor, EEG sensor and a PDA for BSN interface are under development.^[13]

Wireless communication in the U.S.

The FCC has approved the allocation of 40 MHz of spectrum bandwidth for medical BAN low-power, wide-area radio links at the 2360–2400 MHz band. This will allow off-loading MBAN communication from the already saturated standard Wi-Fi spectrum to a standard band.^[14]

The 2360–2390 MHz frequency range is available on a secondary basis. The FCC will expand the existing Medical Device Radiocommunication (MedRadio) Service in Part 95 of its rules. MBAN devices using the band will operate under a 'license-by-rule' basis which eliminates the need to apply for individual transmitter licenses. Usage of the 2360–2390 MHz frequencies are restricted to indoor operation at health-care facilities and are subject to registration and site approval by coordinators to protect aeronautical telemetry primary usage. Operation in the 2390–2400 MHz band is not subject to registration or coordination and may be used in all areas including residential.^[15]

Challenges

Problems with the use of this technology could include:

Data quality: Data generated and collected through BANs can play a key role in the patient care process. It is essential that the quality of this data is of a high standard to ensure that the decisions made are based on the best information possible
Data management: As BANs generate large volumes of data, the need to manage and maintain these datasets is of utmost importance.^[16]
Sensor validation: Pervasive sensing devices are subject to inherent communication and hardware constraints including unreliable wired/wireless network links, interference and limited power reserves. This may result in erroneous datasets being transmitted back to the end user. It is of the utmost importance especially within a healthcare domain that all sensor readings are validated. This helps to reduce false alarm generation and to identify possible weaknesses within the hardware and software design.
Data consistency: Data residing on multiple mobile devices and wireless patient notes need to be collected and analysed in a seamless fashion. Within body area networks, vital patient datasets may be fragmented over a number of nodes and across a number of networked PCs or Laptops. If a medical practitioner's mobile device does not contain all known information then the quality of patient care may degrade.
Security: Considerable effort would be required to make WBAN transmission secure and accurate. It would have to be made sure that the patient secure data is only derived from each patient's dedicated WBAN system and is not mixed up with other patient's data. Further, the data generated from WBAN should have secure and limited access. Although security is a high priority in most networks, little study has been done in this area for WBANs. As WBANs are resource-constrained in terms of power, memory, communication rate and computational capability, security solutions proposed for other networks may not be applicable to WBANs. Confidentiality, authentication, integrity, and freshness of data together with availability and secure management are the security requirements in WBAN. The IEEE 802.15.6 standard, which is latest standard for WBAN, tried to provide security in WBAN. However, it has several security problems.^[17]
Interoperability: WBAN systems would have to ensure seamless data transfer across standards such as Bluetooth, Zigbee etc. to promote information exchange, plug and play device interaction. Further, the systems would have to be scalable, ensure efficient migration across networks and offer uninterrupted connectivity.
System devices: The sensors used in WBAN would have to be low on complexity, small in form factor, light in weight, power efficient, easy to use and reconfigurable. Further, the storage devices need to facilitate remote storage and viewing of patient data as well as access to external processing and analysis tools via the Internet.
Energy vs. accuracy: Sensors' activation policy should be determined to optimizing the trade-off between the BAN's power consumption versus the probability of patient's health state mis-classification. High power consumption often results in more accurate observations on the patient's health state and vice versa.^[18]
Privacy: People might consider the WBAN technology as a potential threat to freedom if the applications go beyond "secure" medical usage. Social acceptance would be key to this technology finding a wider application.
Interference: The wireless link used for body sensors should reduce the interference and increase the coexistence of sensor node devices with other network devices available in the environment. This is especially important for large scale implementation of WBAN systems.^[9]^[19]
Cost: Today's consumers expect low cost health monitoring solutions which provide high functionality. WBAN implementations will need to be cost optimized to be appealing alternatives to health conscious consumers.
Constant monitoring: Users may require different levels of monitoring, for example those at risk of cardiac ischemia may want their WBANs to function constantly, while others at risk of falls may only need WBANs to monitor them while they are walking or moving. The level of monitoring influences the amount of energy required and the life cycle of the BAN before the energy source is depleted.^[5]^[18]
Constrained deployment: The WBAN needs to be wearable, lightweight and non intrusive. It should not alter or encumber the user's daily activities. The technology should ultimately be transparent to the user i.e., it should perform its monitoring tasks without the user realising it.
Consistent performance: The performance of the WBAN should be consistent. Sensor measurements should be accurate and calibrated, even when the WBAN is switched off and switched on again.^[20] The wireless links should be robust and work under various user environments.

Related Research Articles

Wireless communication is the transfer of information (telecommunication) between two or more points without the use of an electrical conductor, optical fiber or other continuous guided medium for the transfer. The most common wireless technologies use radio waves. With radio waves, intended distances can be short, such as a few meters for Bluetooth, or as far as millions of kilometers for deep-space radio communications. It encompasses various types of fixed, mobile, and portable applications, including two-way radios, cellular telephones, personal digital assistants (PDAs), and wireless networking. Other examples of applications of radio wireless technology include GPS units, garage door openers, wireless computer mouse, keyboards and headsets, headphones, radio receivers, satellite television, broadcast television and cordless telephones. Somewhat less common methods of achieving wireless communications involve other electromagnetic phenomena, such as light and magnetic or electric fields, or the use of sound.

Zigbee is an IEEE 802.15.4-based specification for a suite of high-level communication protocols used to create personal area networks with small, low-power digital radios, such as for home automation, medical device data collection, and other low-power low-bandwidth needs, designed for small scale projects which need wireless connection. Hence, Zigbee is a low-power, low-data-rate, and close proximity wireless ad hoc network.

Wireless sensor networks (WSNs) refer to networks of spatially dispersed and dedicated sensors that monitor and record the physical conditions of the environment and forward the collected data to a central location. WSNs can measure environmental conditions such as temperature, sound, pollution levels, humidity and wind.

eHealth describes healthcare services which are supported by digital processes, communication or technology such as electronic prescribing, Telehealth, or Electronic Health Records (EHRs). The term "eHealth" originated in the 1990s, initially conceived as "Internet medicine," but has since evolved to have a broader range of technologies and innovations aimed at enhancing healthcare delivery and accessibility. According to the World Health Organization (WHO), eHealth encompasses not only internet-based healthcare services but also modern advancements such as artificial intelligence, mHealth, and telehealth, which collectively aim to improve accessibility and efficiency in healthcare delivery. Usage of the term varies widely. A study in 2005 found 51 unique definitions of eHealth, reflecting its diverse applications and interpretations. While some argue that it is interchangeable with health informatics as a broad term covering electronic/digital processes in health, others use it in the narrower sense of healthcare practice specifically facilitated by the Internet. It also includes health applications and links on mobile phones, referred to as mHealth or m-Health.. Key components of eHealth include electronic health records (EHRs), telemedicine, health information exchange, mobile health applications, wearable devices, and online health information. For example, diabetes monitoring apps allow patients to track health metrics in real time, bridging the gap between home and clinical care. These technologies enable healthcare providers, patients, and other stakeholders to access, manage, and exchange health information more effectively, leading to improved communication, decision-making, and overall healthcare outcomes.

Mutual authentication or two-way authentication refers to two parties authenticating each other at the same time in an authentication protocol. It is a default mode of authentication in some protocols and optional in others (TLS).

A wireless ad hoc network (WANET) or mobile ad hoc network (MANET) is a decentralized type of wireless network. The network is ad hoc because it does not rely on a pre-existing infrastructure, such as routers or wireless access points. Instead, each node participates in routing by forwarding data for other nodes. The determination of which nodes forward data is made dynamically on the basis of network connectivity and the routing algorithm in use.

CEN ISO/IEEE 11073 Health informatics - Medical / health device communication standards enable communication between medical, health care and wellness devices and external computer systems. They provide automatic and detailed electronic data capture of client-related and vital signs information, and of device operational data.

Internet of things (IoT) describes devices with sensors, processing ability, software and other technologies that connect and exchange data with other devices and systems over the Internet or other communication networks. The Internet of things encompasses electronics, communication, and computer science engineering. "Internet of things" has been considered a misnomer because devices do not need to be connected to the public internet; they only need to be connected to a network and be individually addressable.

Daintree Networks, Inc. was a building automation company that provided wireless control systems for commercial and industrial buildings. Founded in 2003, Daintree was headquartered in Los Altos, California, with an R&D lab in Melbourne, Australia.

A sensor grid integrates wireless sensor networks with grid computing concepts to enable real-time data collection and the sharing of computational and storage resources for sensor data processing and management. It is an enabling technology for building large-scale infrastructures, integrating heterogeneous sensor, data and computational resources deployed over a wide area, to undertake complicated surveillance tasks such as environmental monitoring.

Cyber-Physical Systems (CPS) are mechanisms controlled and monitored by computer algorithms, tightly integrated with the internet and its users. In cyber-physical systems, physical and software components are deeply intertwined, able to operate on different spatial and temporal scales, exhibit multiple and distinct behavioral modalities, and interact with each other in ways that change with context. CPS involves transdisciplinary approaches, merging theory of cybernetics, mechatronics, design and process science. The process control is often referred to as embedded systems. In embedded systems, the emphasis tends to be more on the computational elements, and less on an intense link between the computational and physical elements. CPS is also similar to the Internet of Things (IoT), sharing the same basic architecture; nevertheless, CPS presents a higher combination and coordination between physical and computational elements.

mHealth is an abbreviation for mobile health, a term used for the practice of medicine and public health supported by mobile devices. The term is most commonly used in reference to using mobile communication devices, such as mobile phones, tablet computers and personal digital assistants (PDAs), and wearable devices such as smart watches, for health services, information, and data collection. The mHealth field has emerged as a sub-segment of eHealth, the use of information and communication technology (ICT), such as computers, mobile phones, communications satellite, patient monitors, etc., for health services and information. mHealth applications include the use of mobile devices in collecting community and clinical health data, delivery/sharing of healthcare information for practitioners, researchers and patients, real-time monitoring of patient vital signs, the direct provision of care as well as training and collaboration of health workers.

Wearable technology is any technology that is designed to be used while worn. Common types of wearable technology include smartwatches and smartglasses. Wearable electronic devices are often close to or on the surface of the skin, where they detect, analyze, and transmit information such as vital signs, and/or ambient data and which allow in some cases immediate biofeedback to the wearer.

In medicine, monitoring is the observation of a disease, condition or one or several medical parameters over time.

Remote patient monitoring (RPM) is a technology to enable monitoring of patients outside of conventional clinical settings, such as in the home or in a remote area, which may increase access to care and decrease healthcare delivery costs. RPM involves the constant remote care of patients by their physicians, often to track physical symptoms, chronic conditions, or post-hospitalization rehab.

The IEEE 802.15.6 standard is the latest international standard for Wireless Body Area Network (WBAN).

Medical device connectivity is the establishment and maintenance of a connection through which data is transferred between a medical device, such as a patient monitor, and an information system. The term is used interchangeably with biomedical device connectivity or biomedical device integration. By eliminating the need for manual data entry, potential benefits include faster and more frequent data updates, diminished human error, and improved workflow efficiency.

Subsea Internet of Things (SIoT) is a network of smart, wireless sensors and smart devices configured to provide actionable operational intelligence such as performance, condition and diagnostic information. It is coined from the term The Internet of Things (IoT). Unlike IoT, SIoT focuses on subsea communication through the water and the water-air boundary. SIoT systems are based around smart, wireless devices incorporating Seatooth radio and Seatooth Hybrid technologies. SIoT systems incorporate standard sensors including temperature, pressure, flow, vibration, corrosion and video. Processed information is shared among nearby wireless sensor nodes. SIoT systems are used for environmental monitoring, oil & gas production control and optimisation and subsea asset integrity management. Some features of IoT's share similar characteristics to cloud computing. There is also a recent increase of interest looking at the integration of IoT and cloud computing. Subsea cloud computing is an architecture design to provide an efficient means of SIoT systems to manage large data sets. It is an adaption of cloud computing frameworks to meet the needs of the underwater environment. Similarly to fog computing or edge computing, critical focus remains at the edge. Algorithms are used to interrogate the data set for information which is used to optimise production.

A pulse watch, also known as a pulsometer or pulsograph, is an individual monitoring and measuring device with the ability to measure heart or pulse rate. Detection can occur in real time or can be saved and stored for later review. The pulse watch measures electrocardiography data while the user is performing tasks, whether it be simple daily tasks or intense physical activity. The pulse watch functions without the use of wires and multiple sensors. This makes it useful in health and medical settings where wires and sensors may be an inconvenience. Use of the device is also common in sport and exercise environments where individuals are required to measure and monitor their biometric data.

Konstantina "Nantia" Nikita is a Greek electrical and computer engineer and a professor at the School of Electrical and Computer Engineering at the National Technical University of Athens (NTUA), Greece. She is director of the Mobile Radiocommunications Lab and founder and director of the Biomedical Simulations and Imaging Lab, NTUA. Since 2015, she has been an Irene McCulloch Distinguished Adjunct Professor of Biomedical Engineering and Medicine at Keck School of Medicine and Viterbi School of Engineering, University of Southern California.

References

↑ "IEEE 802.15 WPAN Task Group 6 Body Area Networks". Archived from the original on 2018-03-25. Retrieved 2011-02-03.
↑ Ullah, S.; Higgins, H.; Braem, B.; Latre, B.; Blondia, C.; Moerman, I.; Saleem, S.; Rahman, Z.; Kwak, K. S. (2012). "A Comprehensive Survey of Wireless Body Area Networks: On PHY, MAC, and Network Layers Solutions". Journal of Medical Systems. 36 (3): 1065–1094. doi:10.1007/s10916-010-9571-3. hdl: 1854/LU-3234782 . PMID 20721685. S2CID 7988320. Archived from the original on 2020-02-15. Retrieved 2019-12-13.
↑ Chen, Min; Gonzalez, Sergio; Vasilakos, Athanasios; Cao, Huasong; Leung, Victor (2010). "Body Area Networks: A Survey" (PDF). Mobile Networks and Applications. 16 (2): 1–23. CiteSeerX 10.1.1.329.7097 . doi:10.1007/s11036-010-0260-8. ISSN 1383-469X. S2CID 16514036. Archived (PDF) from the original on 2017-08-10. Retrieved 2010-09-05.
↑ Movassaghi, Samaneh; Abolhasan, Mehran; Lipman, Justin; Smith, David; Jamalipour, Abbas (2014). "Wireless Body Area Networks: A Survey". IEEE Communications Surveys and Tutorials. 16 (3): 1658–1686. doi:10.1109/SURV.2013.121313.00064. S2CID 3835757.
1 2 3 Geller, T., David, Y. B., Khmelnitsky, E., Ben-Gal, I., Ward, A., Miller, D., & Bambos, N. (2019, May). "Learning Health State Transition Probabilities via Wireless Body Area Networks" (PDF). In ICC 2019-2019 IEEE International Conference on Communications (ICC), pp. 1-6. IEEE. 2019. Archived from the original (PDF) on February 4, 2020.{{cite web}}: CS1 maint: multiple names: authors list (link) CS1 maint: numeric names: authors list (link)
↑ Lamanna, Leonardo; Cataldi, Pietro; Friuli, Marco; Demitri, Christian; Caironi, Mario (January 2023). "Monitoring of Drug Release via Intra Body Communication with an Edible Pill". Advanced Materials Technologies. 8 (1): 2200731. doi: 10.1002/admt.202200731 . ISSN 2365-709X. S2CID 253174336.
↑ Poslad, Stefan (2009). Ubiquitous Computing Smart Devices, Smart Environments and Smart Interaction. Wiley. ISBN 978-0-470-03560-3. Archived from the original on 2012-02-15. Retrieved 2014-06-23.
↑ Schmidt R, Norgall T, Mörsdorf J, Bernhard J, von der Grün T (2002). "Body Area Network BAN—a key infrastructure element for patient-centered medical applications". Biomed Tech. 47 (1): 365–8. doi:10.1515/bmte.2002.47.s1a.365. PMID 12451866. S2CID 37439434.
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↑ Vierhout, P. a. M.; Konstantas, D.; Bults, Richard G. A.; Jones, Valerie M. (2001-09-18). "Body Area Networks for Healthcare" (PDF). Archived from the original (PDF) on 2013-06-15. Retrieved 2011-02-03.{{cite journal}}: Cite journal requires |journal= (help)
↑ M. R. Yuce & J. Y. Khan (2011). Yuce, Mehmet R & Khan, Jamil (eds.). Wireless Body Area Networks: Technology, Implementation, and Applications. doi:10.1201/b11522. ISBN 9780429184932. Archived from the original on January 17, 2023. Retrieved April 28, 2017.{{cite book}}: |journal= ignored (help)
↑ "IEEE P802.15.6-2012 Standard for Wireless Body Area Networks". Archived from the original on 2018-01-19. Retrieved 2015-03-12.
↑ "Body Sensor Networks". Archived from the original on 2009-12-16. Retrieved 2010-08-12.
↑ "'Body Area Networks' should free hospital bandwidth, untether patients – Computerworld". 2012-06-04. Archived from the original on 2013-06-19. Retrieved 2012-06-06.
↑ "FCC Dedicates Spectrum Enabling Medical Body Area Networks | FCC.gov". Archived from the original on 2012-05-30. Retrieved 2012-06-06.
↑ Healthcare Sensor Networks Challenges Toward Practical Implementation. CRC Press. 19 April 2016. ISBN 9781000755701. Archived from the original on 17 January 2023. Retrieved 11 June 2021.
↑ Toorani, Mohsen (2015). "On Vulnerabilities of the Security Association in the IEEE 802.15.6 Standard". Financial Cryptography and Data Security. Lecture Notes in Computer Science. Vol. 8976. pp. 245–260. arXiv: 1501.02601 . doi:10.1007/978-3-662-48051-9_18. ISBN 978-3-662-48050-2.
1 2 Miller, Daniel; Zhou, Zhengyuan; Bambos, Nicholas; Ben-Gal, Irad (2018). "Sensing-Constrained Power Control in Digital Health". 2018 Annual American Control Conference (ACC). pp. 4213–4220. doi:10.23919/ACC.2018.8431675. ISBN 978-1-5386-5428-6. S2CID 52020398.
↑ Garcia, P. (December 2011). "A Methodology for the Deployment of Sensor Networks". IEEE Transactions on Knowledge and Data Engineering. 11 (4).
↑ O'Donovan, Tony; O'Donoghue, John; Sreenan, Cormac; Sammon, David; O'Reilly, Philip; O'Connor, Kieran A. (2009). "A Context Aware Wireless Body Area Network (BAN)" (PDF). Proceedings of the 3d International ICST Conference on Pervasive Computing Technologies for Healthcare. doi:10.4108/ICST.PERVASIVEHEALTH2009.5987. S2CID 14131365. Archived (PDF) from the original on 2016-10-09. Retrieved 2016-06-05.

Engineer Reza Khalilian (SCOPUS:57193996763) (ORCiD: 0000-0001-5936-8596) (WOS: ACO-0524-2022) PhD, MSc Engineer of ICT and Electronics, Author, Research As, Tour Guide, Technical College Teacher Verified email at jdeihe.ac.ir - Homepage Healthcare EcosystemsWBANTelemedicineAI IoTCancer Prevention Title Cited by Year An Efficient Method to Improve WBAN Security R Khalilian, A Rezai, E Abedini Advanced Science and Technology Letters (ASTL) 64 (No. 11; ISSN. 2287-1233 … 25 2014 Secure Wireless Body Area Network (WBAN) Communication Method Using New Random Key Management Scheme R Khalilian, A Rezai, F Mesrinejad International Journal of Security and Its Applications (IJSIA) Scopus 10 (11 … 12 2016 Wireless Body Area Network (WBAN) Applications Necessity in Real Time Healthcare R Khalilian, A Rezai 13th IEEE Princeton Integrated STEM (Science, Technology, Engineering … 10 2022 Cloud Computing R Kalilian, A Rezai, M Mahdavi 2024 A new Efficient Adjustable Current Pulse Power Supply (ACPS) in the Wireless Body Area Network (WBAN) Khalilian, Reza, Rezai, Abdalhossein, Gharavi, Arash, Zafari, Mehdi 1st International Conference of Ideas on Electrical Engineering (ICNIEE2024 … 2024 Breast Cancer Diagnosis by Phased Array RADAR (PAR) on Real Time Wireless Body Area Networks (WBANs) Platform Khalilian, Reza, Rezai, Abdalhossein 1st International Conference of Ideas on Electrical Engineering (ICNIEE2024 … 2024 Intelligent Transportation System (ITS) Using Internet of Things (IoT) Khalilian, Reza, Rezai, Abdalhossein, Talakesh, SM Reza 14th IEEE International Conference on Information and Knowledge Technology … 2023 A New Biomedical Signal Processor (BSP) Architecture for Energy Efficient in Wireless Body Area Networks (WBANs) R Khalilian, A Rezai International Conference on New Researches and Technologies in Electrical … 2023 An Eco-Friendly Cosmopolitan (EFC) by Recycling Scientific/Industrial Towns (RSITs) Khalilian, Reza, Rezai, Abdalhossein, Talakesh, SM Reza 14th IEEE International Conference on Information and Knowledge Technology … 2023 Human Brain Mapping by Electroencephalogram (EEG) in Wireless Body Area Network (WBAN) with Brain Computing Interface (BCI) on Metaverse via Artificial Intelligent … R Khalilian, A Rezai The 6th meeting of the interdisciplinary health research network with the … 2023 A New Platform of WBAN in Real Time Tele Medicine and Healthcare Ecosystems to Manage the Covid-19 R Khalilian, A Rezai Academic Journal, Journal of Biomedical Physics and Engineering, 5th Shiraz … 2023 X Band Exciter R Khalilian, H Emami, M Moradi ISBN: 978-622-94444-4-3, Gohar Gooya Publications 1, 163 2023 Elements of Information Theory (and Coding 1) R Khalilian, A Hatam, S Nasri https://ketab.ir/book/37011d8c-5536-4eb3-9a64-0a45fd0973fa Elements of … 2023 BAES Token in Wireless Body Area Network for Real Time Healthcare Ecosystem R Khalilian, A Rezai, F Mesrinejad The 9th International Conference on Health, Treatment and Health Promotion … 2022 An Overview on the Wireless Body Area Networks as a Mater Platform by Value Management for Real Time Telemedicine and Healthcare Monitoring Ecosystem R Khalilian, A Rezai, R Kelishadi 1st International Telemedicine Conference, Medical Sciences University of … 2022 RFID Smart Card (1) R Khalilian, V Amir, F Goli https://ketab.ir/book/fd1a72a8-6b69-47fb-9cb8-5982216fc05a Gohar Gooya … 2021 E-Commerce (1) R Khalilian, MR Moslehi, E Khalilian https://ketab.ir/book/396dbafc-22c3-4056-accd-074efe64c758 Gohar Gooya … 2021 Wireless Body Area Network (WBAN) (1) R Kalilian, A Rezai, F Mesrinejad https://ketab.ir/book/682938a3-7130-4ab7-8830-8437e1abeea0 Gohar Gooya … 2021 Investigation, Design and Improvement Security of Wireless Body Area Networks (WBANs) R Khalilian, A Rezai, F Mesrinejad Master Thesis, Islamic Azad University of Majlesi 2016 Security Assessment of Proposed Wireless Body Area Network (WBAN) R Khalilian, A Rezai, F Mesrinejad National Conference on Electrical Engineering of Majlesi (NCEEM), Isfahan … 2016 A New Method for Energy Efficient in Wireless Body Area Network (WBAN) R Khalilian, A Rezai, E Abedini Iran's Electrical Engineering Student Conference, International Sharif … 2014 WBAN Security Improvement in a Real Time Healthcare and Medical Ecosystem R Khalilian, A Rezai, F Mesrinejad, E Abedini Mechatronic Systems Engineering and Telecommunication Systems (MISMEC … 2013 E-Commerce Security Protocols as a Dynamic Code Tokens R Khalilian, MR Moslehi Science and Culture University (ACECR IUT) 2011 RFID Smart Card and Contactless Reader (Terminal) R Khalilian, V Amir Shahid Rajaee Technical and Engineering College 2008

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[1] "IEEE 802.15 WPAN Task Group 6 Body Area Networks". Archived from the original on 2018-03-25. Retrieved 2011-02-03.

[2] Ullah, S.; Higgins, H.; Braem, B.; Latre, B.; Blondia, C.; Moerman, I.; Saleem, S.; Rahman, Z.; Kwak, K. S. (2012). "A Comprehensive Survey of Wireless Body Area Networks: On PHY, MAC, and Network Layers Solutions". Journal of Medical Systems. 36 (3): 1065–1094. doi:10.1007/s10916-010-9571-3. hdl: 1854/LU-3234782 . PMID 20721685. S2CID 7988320. Archived from the original on 2020-02-15. Retrieved 2019-12-13.

[3] Chen, Min; Gonzalez, Sergio; Vasilakos, Athanasios; Cao, Huasong; Leung, Victor (2010). "Body Area Networks: A Survey" (PDF). Mobile Networks and Applications. 16 (2): 1–23. CiteSeerX 10.1.1.329.7097 . doi:10.1007/s11036-010-0260-8. ISSN 1383-469X. S2CID 16514036. Archived (PDF) from the original on 2017-08-10. Retrieved 2010-09-05.

[4] Movassaghi, Samaneh; Abolhasan, Mehran; Lipman, Justin; Smith, David; Jamalipour, Abbas (2014). "Wireless Body Area Networks: A Survey". IEEE Communications Surveys and Tutorials. 16 (3): 1658–1686. doi:10.1109/SURV.2013.121313.00064. S2CID 3835757.

[Geller-5] 1 2 3 Geller, T., David, Y. B., Khmelnitsky, E., Ben-Gal, I., Ward, A., Miller, D., & Bambos, N. (2019, May). "Learning Health State Transition Probabilities via Wireless Body Area Networks" (PDF). In ICC 2019-2019 IEEE International Conference on Communications (ICC), pp. 1-6. IEEE. 2019. Archived from the original (PDF) on February 4, 2020.{{cite web}}: CS1 maint: multiple names: authors list (link) CS1 maint: numeric names: authors list (link)

[6] Lamanna, Leonardo; Cataldi, Pietro; Friuli, Marco; Demitri, Christian; Caironi, Mario (January 2023). "Monitoring of Drug Release via Intra Body Communication with an Edible Pill". Advanced Materials Technologies. 8 (1): 2200731. doi: 10.1002/admt.202200731 . ISSN 2365-709X. S2CID 253174336.

[Poslad-7] Poslad, Stefan (2009). Ubiquitous Computing Smart Devices, Smart Environments and Smart Interaction. Wiley. ISBN 978-0-470-03560-3. Archived from the original on 2012-02-15. Retrieved 2014-06-23.

[8] Schmidt R, Norgall T, Mörsdorf J, Bernhard J, von der Grün T (2002). "Body Area Network BAN—a key infrastructure element for patient-centered medical applications". Biomed Tech. 47 (1): 365–8. doi:10.1515/bmte.2002.47.s1a.365. PMID 12451866. S2CID 37439434.

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