BODY AREA NETWORK

Presentation by :Muhammed Nigil K AS8 CSE

INTRODUCTIONBAN, a base technology, consisting of a set of mobile and compact intercommunicating sensors, either wearable or implanted into the human body, which monitor vital body parameters and movements. These devices, communicating through wireless technologies, transmit data from the body to a home base station, from where the data can be forwarded to a hospital, clinic or elsewhere, real-time.

A BAN topology consists of several nodes deployed in such a way in order to create an on-body communication network. Such a network is supposed to be autonomous and is expected to incorporate a central portable unit, the Personal Base Station (PBS). The PBS will receive and preprocess any medical sensor measured data and then will retransmit it to the medical service via a public network. The aim of this scheme is to improve the quality of life and control the patient’s medical costs.IEEE 802.15.6 is the task group for BAN.

HISTORY & DEVELOPMENT OF BAN -> BAN technology is still an emerging technology, and as such it has a very short history. -> BAN technology emerges as the natural byproduct of existing sensor network technology and biomedical engineering. -> Professor Guang-Zhong Yang was the first person to formally define the phrase "Body Sensor Network" (BSN) -> BSN technology represents the lower bound of power and bandwidth from the BAN use case scenarios.-> Some of the more common use cases for BAN technology are:

- Body Sensor Networks (BSN) - Sports and Fitness Monitoring - Wireless Audio - Mobile Device Integration - Personal Video Devices

-> Operates in global, license-exempt band.

-> Effective sleep mode(s) and concept for effective, remote wake-up.

-> High privacy and security.

-> Peer to peer communication, point to multi-point communication.

-> Omni-directional antennas: small, flexible

-> Support for several power management / consumption schemes.

-> Quality of service, guaranteed bandwidth

-> Graceful degradation of services

-> Concurrent availability of asynchronous and isochronous channels

-> Very low duty cycle applications (sensors)

CHARACTERSITICS

DATA RATE VS POWER

TECHNICAL REQUIREMENTS-> Distance 2 m std, 5 m special

-> Piconet density 2 - 4 nets / m2

-> Devices per network max. 100

-> Net network throughput 100 Mbps max.

-> Power consumption ~ 1mW / Mbps (@ 1 m distance)

-> Startup time < 100 us

-> Latency (end to end) 10 ms

-> Network setup time < 1 sec (after initial setup, per device)

-> Antenna pattern Omni directional

UBIQUITOUS HEALTH MONITORING

A ubiquitous health monitoring system for multiple users was developed based on a ZigBee and wireless local area network (WLAN) dual-network. A compact biosignal monitoring unit (BMU) for measuring electrocardiogram (ECG), photoplethysmogram (PPG), and temperature was also developed.

SYSTEM ARCHITECTURE

-> Three- tier architecture : WBAN , Personal Server, Medical Server

-> Sensor nodes are strategically placed on user’s body

-> Network Implemented using ZigBee (802.15.4) or Bluetooth

(802.15.1)

-> Network configuration tasks: sensor node registration & setup of

secure communication

-> Personal Server implemented on PDA (Personal Digital Assistant)

-> Medical Server records medical details and provide services

-> Data transfers require encryption of all sensitive information

SYSTEM ARCHITECTURE

SENSOR NODES

Personal Server with Network Coordinator, ECG sensor and motion sensor

Telos wireless platform with daughtercard ISPM

ActiS as motion sensor

Body Media Monitor

DATA FLOW

APPLICATION IN HEALTHCARE-> BANs have grown as a refinement of BSN. As such, BSN remain the most thought out applications of BAN.-> BSN devices refine the general requirements by restricting themselves to a much smaller range (< 0.01 - 2.00 m). This limited range allows developers to take advantage of several aspects of the human body.-> First, the human body itself can become a channel for short range

communication, thus removing the need for a traditional antenna->By removing the requirement of an additional antenna, the power

consumption of BSN devices shrinks to 0.1 - 1.0 mW. At this low of power, the human body is actually capable of generating enough excess energy that the devices could "scavenge" the required energy directly from the host's body, removing the restriction on traditional power sources (like batteries)

MANAGED BODY SENSOR NETWORKS -> A managed body sensor network (MBSN) is defined as a system where the third party makes decisions based the data collected from one or many BSN.-> MobiHealh and CodeBlue, two managed BSN that are are approaching

development of managed BSN from two different perspectives. -> Continuous monitoring of vital constants for mobile users: the MobiHealth approach. a BSN with EBAN connectivity to a 2.5/3G networks to provide out- patient monitoring of patients vital signs. Through this infrastructure the MobiHealth designers were able to provide sensor information to qualified medical professionals, where multiple patients data could be monitored in an aggregate form.-> CodeBlue provides an infrastructure for multiple patient monitoring through EBAN communication. However, CodeBlue takes a more middleware approach to BSN instead of the packaged solution that MobiHealth provides. By providing a middleware layer, the CodeBlue project allows developers to specify the modules to use. In this way, CodeBlue is rather flexible at runtime.

AUTONOMOUS BODY SENSOR NETWORKS

-> ABSN introduce actuators in addition to the sensors to allow the BSN to effect change on the users body. In addition to the actuators, ABSN contain more intelligent sensors that contain enough intelligence to complete their own tasks independently.

CHALLENGES-> Signal & Path Performance - the signal and path loss inside the human body is drastically different than the rules in plain space. That said the rules governing signal and path loss remain the same. Researchers have been able to model signal loss throughout the human body, however the more interesting research involves using the human body as a transmission medium for electrical signals.-> 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. -> 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. -> 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’s data is only derived from each patient’s dedicated BAN system and is not mixed up with other patient’s data.

FUTURE APPLICATIONS-> A WBAN network in place on a patient can alert the hospital, even before

he has a heart attack, through measuring changes in his vital signs.

-> A WBAN network on a diabetic patient could auto inject insulin though a

pump, as soon as his insulin level declines, thus making the patient

‘doctor-free’ and virtually healthy.

-> BAN is expected to be used for supporting speech-impaired person.

-> 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.

CONCLUSION-> A wearable WBAN of physiological sensors integrated into a telemedical

system holds the promise to become key Infrastructure element in remotely

supervised, home- based patient rehabilitation.

-> It has the potential to provide a better and less expensive alternative for

rehabilitation healthcare and may provide benefit to patients, physicians,

and society through continuous monitoring in the ambulatory setting.

-> It also provides continuous Monitoring with early detection.

-> The coin-sized intelligent sensors will be applied as skin patches,

integrated into a personal monitoring system, and worn for extended

periods of time.

REFERENCES-> Emil Jovanov, Aleksandar Milenkovic, Chris Otto and Piet C de Groen, “A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation“ in Journal of Neuro Engineering and Rehabilitation 2005, 2:6-> Angelos A. Goulianos and Stavros Stavrou “UWB Path Arrival Times in Body Area Networks” in IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS, VOL. 6, 2007-> Chris Otto, Aleksandar Milenkovic, Corey Sanders, Emil Jovanov “System Architecture of a Wireless Body Area Sensor Network for Ubiquitous Health monitoring” in Journal of Mobile Multimedia, Vol. 1, No.4(2006) 307-326-> Huan-Bang Li, Ken-ichi Takizawa, Bin Zhen, Ryuji Kohno "Body Area Network and Its Standardization at IEEE 802.15.MBAN”-> Chris A. Otto “Wireless body area networks for ambulatory health monitoring”

Steve Warren, Jeffrey Lebak, Jianchu Yao, Jonathan Creekmore, Aleksandar Milenkovic, and Emil Jovanov “Interoperability and Security in Wireless Body Area Network Infrastructures”-> Thomas Zasowski, Gabriel Meyer, Frank Althaus, and Armin Wittneben “Propagation Effects in UWB Body Area Networks”