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Ambient Intelligence Fachbereich Informatik und Elektrotechnik AmI Ambient Intelligence Ambient Intelligence, Helmut Dispert Fachbereich Informatik und Elektrotechnik BAN – BSN - WBSN Ambient Intelligence • Body Area Network - BAN • Body Sensor Network – BSN • Wireless Body Sensor Network - WBSN Wireless body-area sensor networks (WBSNs) are key components of e-health solutions. Wearable wireless sensors can monitor and collect many different physiological parameters accurately, economically and efficiently. Ambient Intelligence, Helmut Dispert Fachbereich Informatik und Elektrotechnik BAN – BSN - WBSN Body sensing To address these issues, the concept of Body Sensor Networks (BSN) was first proposed in 2002 by Prof. Guang-Zhong Yang from Imperial College London. The aim of the BSN is to provide a truly personalised monitoring platform that is pervasive, intelligent, and invisible to the user. Example BSN system: represents a patient wearing a number of sensors on his body, each of which consists of a sensor connected to a small processor, wireless transmitter, and battery pack, forming a BSN node. The BSN node captures the sensor data, processes the data and then wirelessly transmits the information to a local processing unit, shown as a personal digital assistant (PDA) in the diagram. All this has been made possible by rapid advances in computing technology. Ambient Intelligence, Helmut Dispert Fachbereich Informatik und Elektrotechnik Literature Yang, Guang-Zhong (Ed.): Body Sensor Networks, Springer, 2006 ISBN: 978-1-84628-272-0 Ambient Intelligence, Helmut Dispert Fachbereich Informatik und Elektrotechnik BSN Ambient Intelligence, Helmut Dispert Fachbereich Informatik und Elektrotechnik BSN Wireless Body Sensor Network ? Fraunhofer Institute Ref.: www.golem.de Ambient Intelligence, Helmut Dispert Fachbereich Informatik und Elektrotechnik BSN A 'typical' architecture for a Body Sensor Network System Ambient Intelligence, Helmut Dispert Fachbereich Informatik und Elektrotechnik Braunschweig BSN Ref.: Technical University of Braunschweig Body Sensor Network Ambient Intelligence, Helmut Dispert Fachbereich Informatik und Elektrotechnik BAN – BSN - WBSN Body Area Networks – Average power consumption, sustained data rate 1 Gbit/s Wireless USB 100 Mbit/s 10 Mbit/s IEEE 802.11 a/b/g 1 Mbit/s Bluetooth 100 kbit/s ZigBee 10 kbit/s Body Area Network 1 kbit/s 2 mW 5 mW 10 mW 20 mW 50 mW 100 mW 200 mW 500 mW 1000 mW Ref.: Stefan Drude, Philips Ambient Intelligence, Helmut Dispert Fachbereich Informatik und Elektrotechnik BAN – BSN - WBSN Ambient Intelligence, Helmut Dispert Fachbereich Informatik und Elektrotechnik Ubiquitous Health Monitoring WBAN: Motivation • Goal: ubiquitous and affordable healthcare • Conditions: demographic and technology trends • Solution: 3-tier ubiquitous monitoring system – Tier 1: Wireless Body Area Network (WBAN) – Tier 2: Personal Server – Tier 3: Healthcare Provider Servers • Opportunities: – Ambulatory health monitoring – Computer-assisted rehabilitation – Augmented reality systems • Long-term benefits: – Promote healthy lifestyle – Seamless integration of data into personal medical records and research databases – Knowledge discovery through data mining Ref.: Emil Jovanov, Chris Ott, Aleksandar Milenkovic, Wireless Body Area Network for Health Monitoring Ambient Intelligence, Helmut Dispert Fachbereich Informatik und Elektrotechnik BAN – BSN - WBSN BAN Requirements - Draft • Distance 2 m std, 5 m special • Piconet density 2 - 4 nets / m2 • Devices per network max. 100 • Net network throughput 100 Mbit/s max. • Power consumption ~ 1mW / Mbps (@ 1 m distance) • Startup time < 100 us, or < 10% of TX slot • Latency (end to end) 10 ms • Network setup time < 1 sec (after initial setup, per device) Ref.: Stefan Drude, Philips Ambient Intelligence, Helmut Dispert Fachbereich Informatik und Elektrotechnik IEEE 802.15 IEEE 802.15 WPAN™ Task Group 6 (TG6) Body Area Networks The IEEE 802.15 Task Group 6 (BAN) is developing a communication standard optimized for low power devices and operation on, in or around the human body (but not limited to humans) to serve a variety of applications including medical, consumer electronics / personal entertainment and other. IEEE 802.15 definition: "a communication standard optimized for low power devices and operation on, in or around the human body (but not limited to humans) to serve a variety of applications including medical, consumer electronics / personal entertainment and other" Ambient Intelligence, Helmut Dispert Fachbereich Informatik und Elektrotechnik BAN – BSN - WBSN Applications 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 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). Ambient Intelligence, Helmut Dispert Fachbereich Informatik und Elektrotechnik BAN – BSN - WBSN Managed Body Sensor Networks - MBSN A managed body sensor network is defined as a system in which the third party makes decisions based on the data collected from one or many BSN. Background: increasing demand of resources placed on the medical community, the rising costs of in-patient care, and the relative lack of out- patient monitoring. Examples: • MobiHealth (2003, Telemedicine Group at the University of Twente) and • CodeBlue (Harvard University), two managed BSN that are approaching development of managed BSN from two different perspectives. MobiHealth approach: Continuous monitoring of vital constants for mobile users (Remote monitoring and treatment services). "Extra-BAN communication" (EBAN): Communication between a BAN and another network. Ambient Intelligence, Helmut Dispert Fachbereich Informatik und Elektrotechnik BAN – BSN - WBSN Managed Body Sensor Networks - MBSN MobiHealth: 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. Harvard University's Code Blue: represents another example of BSN currently in the trial stages. Like MobiHealth, 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. Two examples given by the MobiHealth team are emergency response and monitoring limb movement in stroke patient rehabilitation. Both scenarios have very different requirements both from a sensor perspective, and a timeliness perspective however the platform is able scale to accommodate both accordingly. Ambient Intelligence, Helmut Dispert Fachbereich Informatik und Elektrotechnik BAN – BSN - WBSN Autonomous Body Sensor Networks - ABSN Autonomous body sensor networks (ABSN) and MBSN share the same goals, but they accomplish them in different ways. While a MBSN relies on reading sensor information and delivering it to a third party for decision making and intervention, ABSN take a more proactive approach. 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. Human++ is a project developed in Belgium that aims to bring ABSN to the mainstream. The design of Human++ is relatively simple, any node in the mesh-network are able to talk to any other node in the network. There is a predefined "central" node that is designated for all EBAN communication. The central node also publishes information on any services that the ABSN provides external access to. Ambient Intelligence, Helmut Dispert Fachbereich Informatik und Elektrotechnik BAN – BSN - WBSN Example ABSN Diagram Ambient Intelligence, Helmut Dispert Fachbereich Informatik und Elektrotechnik BAN – BSN - WBSN Health BAN A health BAN is defined as a network of communicating devices worn on, around or in the body which provides mobile health services to the user. A BAN consists of a Mobile Base Unit (MBU) and a set of BAN devices (e.g. sensors, actuators or other ‘wearable devices’). The MBU acts as a processing platform and communications gateway and is currently realised as a software application running on a handheld device. BAN data may be processed locally within the BAN and/or remotely, the latter implying transmission of data to a remote location. Front-end supported sensors are powered by a sensor front end which also digitizes and filters the raw analogue signal before transmitting the data over a wireless link to the MBU. In general, a health BAN may act as a standalone device providing
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