Body area network

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A body area network (BAN), also referred to as a wireless body area network (WBAN) or a body sensor network (BSN), is a wireless network of wearable computing devices.[1][2][3][4] BAN devices may be embedded inside the body, implants, may be surface-mounted on the body in a fixed position Wearable technology or may be accompanied devices which humans can carry in different positions, in clothes pockets, by hand or in various bags.[5] Whilst, there is a trend towards the minitiarisation of devices, in particular, networks consisting of several miniaturized body sensor units (BSUs) together with a single body central unit (BCU).[6][7] larger decimeter sized (tab and pad) sized smart devices, accompanied devices, still play an important role in terms of acting as a data hub, data gateway and providing a user interface to view and manage BAN applications, in-situ. 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 systems where communication is entirely within, on, and in the immediate proximity of a human body. [8][9] 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. [10]

Concept[edit]

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[edit]

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

  • A BAN network 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 network on a diabetic patient could auto inject insulin through a pump, as soon as their insulin level declines.

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 individual and machines.

Components[edit]

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.[11]

Wireless communication in the U.S.[edit]

The FCC has approved a 40 MHz spectrum allocation 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.[12]

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.[13]

Challenges[edit]

Problems with the use of this technology could include:

  • 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.
  • System and device-level security: Considerable effort would be required to make BAN transmission secure and accurate. It would have to be made sure that the patient ‘’secure‘’ data is only derived from each patient's dedicated BAN system and is not mixed up with other patient's data. Further, the data generated from WBAN should have secure and limited access.
  • Invasion of 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.
  • 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.[14]
  • 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.[15]
  • 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.[16][17]
  • Data Management: As BANs generate large volumes of data, the need to manage and maintain these datasets is of utmost importance. O’Donoghue, John, and John Herbert. "Data Management within mHealth Environments: Patient Sensors, Mobile Devices, and Databases." Journal of Data and Information Quality (JDIQ) 4.1 (2012): 5. [18]

Besides hardware-centric challenges, the following human-centric challenges should be addressed for practical BAN development. These include [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.
  • 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. The wireless links should be robust and work under various user environments.

See also[edit]

References[edit]

  1. ^ Developing wireless body area networks standard
  2. ^ Sana Ullah, Henry Higgins, Bart Braem, Benoit Latre, Chris Blondia, Ingrid Moerman, Shahnaz Saleem, Ziaur Rahman and Kyung Sup Kwak, A Comprehensive Survey of Wireless Body Area Networks: On PHY, MAC, and Network Layers Solutions, Journal of Medical Systems (Springer), 2010. doi:10.1007/s10916-010-9571-3.
  3. ^ Chen, Min; Gonzalez, Sergio and Vasilakos, Athanasios and Cao, Huasong and Leung, Victor (2010). "Body Area Networks: A Survey". Mobile Networks and Applications (MONET) (Springer Netherlands) 16 (2): 1–23. doi:10.1007/s11036-010-0260-8. ISSN 1383-469X. 
  4. ^ Movassaghi, Samaneh; Abolhasan, Mehran and Lipman, Justin and Smith, David and Jamalipour, Abbas (2014). "Wireless Body Area Networks: A Survey". IEEE Communications Surveys and Tutorials (IEEE). 
  5. ^ Poslad, Stefan (2009). Ubiquitous Computing Smart Devices, Smart Environments and Smart Interaction. Wiley. ISBN 978-0-470-03560-3. 
  6. ^ 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. 
  7. ^ O'Donovan, T., O'Donoghue, J., Sreenan, C., O'Reilly, P., Sammon, D. and O'Connor, K.: A Context Aware Wireless Body Area Network (BAN), In proceedings of the Pervasive Health Conference 2009,
  8. ^ M. R. Yuce (2010). "Implementation of wireless body area networks for healthcare systems". Sensors and Actuators A: Physical 162: 116–129. doi:10.1016/j.sna.2010.06.004. 
  9. ^ http://doc.utwente.nl/66761/1/WG1_Val_Jones_Richard_Bults.pdf
  10. ^ M. R. Yuce and J. Y. Khan (2011). "Wireless Body Area Networks: Technology, Implementation, and Applications". Pan Stanford Publishing. Retrieved December 2011. 
  11. ^ http://vip.doc.ic.ac.uk/bsn/m621.html
  12. ^ "'Body Area Networks' should free hospital bandwidth, untether patients - Computerworld". Retrieved 2012-06-06. 
  13. ^ "FCC Dedicates Spectrum Enabling Medical Body Area Networks | FCC.gov". Retrieved 2012-06-06. 
  14. ^ O?Donoghue, J. Herbert, J. and Fensli, R.: Sensor Validation within a Pervasive Medical Environment, In Proceedings of IEEE Sensors, South Korea, ISBN 1-4244-0376-6, 2006.
  15. ^ O?Donoghue, J., Herbert, J. and Kennedy, R.: Data Consistency within a Pervasive Medical Environment, In Proceedings of IEEE Sensors, South Korea, ISBN 1-4244-0376-6, 2006.
  16. ^ http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6THG-5093N36-3&_user=915767&_coverDate=07%2F31%2F2010&_rdoc=1&_fmt=high&_orig=search&_origin=search&_sort=d&_docanchor=&view=c&_acct=C000047922&_version=1&_urlVersion=0&_userid=915767&md5=bfcb3fbcaf1e3295f8a625a3cf5b75fc&searchtype=a
  17. ^ Garcia P., "A Methodology for the Deployment of Sensor Networks", IEEE Transactions On Knowledge And Data Engineering, vol. 11, no. 4, December 2011.
  18. ^ http://dl.acm.org/citation.cfm?id=2378021
  19. ^ Lai, D. , Begg, R.K. and Palaniswami, M. eds, Healthcare Sensor Networks: Challenges towards practical implementation, ISBN 978-1-4398-2181-7, 2011

External links[edit]