Visualization of Body Area Networks
The term Body Area Network (BAN) refers to a network intended to be used in or around the human body. While this is an emerging field, networks of medical sensors are anticipated to be a primary application. Such sensors would either be attached to or implanted in the human body and would communicate wirelessly both within the body and to devices outside the body.
For this technology to develop, greater understanding of radio frequency (RF) propagation through the human body is needed. In this project, we seek to provide such insight. This work is assisting the IEEE standards committees to develop communications standards and will help RF engineers to design effective communication devices for BANs.
Additional Technical Details:
Modeling and Visualization of BANs
Because experimentation on human subjects is currently not feasible, RF propagation through the human body is being modeled in software with a 3D full-wave electromagnetic field simulator. The 3D human body model includes frequency dependent dielectric properties of 300+ parts in a male human body. The data produced by this simulation software is then brought into a 3D immersive visualization system, which enables researchers to study the modeled RF propagation through direct interactions with the data.
The simulations are being performed by members of the Advanced Network Technologies Division of ITL and the visualization work is being done by members of the High Performance Computing and Visualization Group of the Applied and Computational Mathematics Division of ITL.
The Immersive Visualization System
The immersive system includes several important components: three orthogonal screens that provide the visual display, the motion tracked stereoscopic glasses, and a hand-held motion tracked input device. The screens are large projection video displays that are placed edge-to-edge in a corner configuration. These three screens are used to display a single 3D stereo scene. The scene is updated based on the position of the user as determined by the motion tracker. This allows the system to present to the user a 3D virtual world within which the user can move and interact with the virtual objects. The main interaction device is a hand-held three button motion-tracked wand with a joystick.
This virtual environment allows for more natural interaction between experts with different backgrounds such as engineering and medical sciences. The researchers can look at data representations at any scale and position, move through data, change orientation, and control the elements of the virtual world using a variety of interaction techniques including measurement and analysis.
For example, we have implemented interactive tools for probing the 3D data fields. One tool enables the researcher to move the motion-tracked wand through the virtual scene, yielding a continuously updated display of the value of the data field at the position of the wand. Another tool enables the user to interactively stretch a line segment through virtual body, and to generate graphs of the 3D data fields along that path. We have found these to be effective tools in getting quantitative information from the 3D scene and in gaining insight into RF propagation through the human body.
W.-B. Yang, K. Sayrafian-Pour, J. Hagedorn, J. Terrill, K. Y. Yazdandoost, A. Taparugssanagorn, M. Hamalainen, J. Iinatti, Impact of an Aortic Valve Implant on Body Surface UWB Propagation: A Preliminary Study, The Fifth International Symposium on Medical Information and Communication Technology (ISMICT), March 27-31, 2011.
K. Sayrafian-Pour, W. B. Yang, J. Hagedorn, J. Terrill, K. Y. Yazdandoost, K. Hamaguchi, Channel Models for Medical Implant Communication, International Journal of Wireless Information Networks, 17(3-4), December 2010, pp. 105-112.
K. Sayrafian-Pour, W. Yang, J. Hagedorn, J. Terrill and K. Y. Yazdandoost, A Statistical Path Loss Model for Medical Implant Communication Channels, IEEE 2009 Personal, Indoor, and Mobile Radio Communications Symposium, September 2009.
Note: Received Best Paper Award.
K. Y. Yazdandoost and K. Sayrafian-Pour, Channel Model for Body Area Network (BAN), Report to the IEEE, April 2009, P802.15. ID: IEEE 802.15-08-0780-02-0006.
Note: J. Hagedorn, J. Terrill, and W. Yang listed as contributors.
J. Hagedorn, J. Terrill, W. Yang, K. Sayrafian-Pour, K. Y. Yazdandoost and R. Kohno, A Statistical Path Loss Model for MICS, September 2008, Report to the IEEE P802.15. ID: IEEE 802.15-08-0519-01-0006.
J. Hagedorn, J. Terrill, W. Yang, K. Sayrafian-Pour, K. Y. Yazdandoost and R. Kohno, MICS Channel Characteristic: Preliminary Results, May 2008, Report to the IEEE P802.15. ID: IEEE 802.15-08-0351-00-0006.
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