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Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)

Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs) Submission Title: Channel modeling for medical implanted communication systems by numerical simulation Date Submitted: [ xx Sep, 2008 ] Source: Jaehwan Kim[ETRI], HyungSoo Lee[ETRI], Jeong Ki Pack[CNU],

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Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)

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  1. Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs) Submission Title: Channel modeling for medical implanted communication systems by numerical simulation Date Submitted: [xx Sep, 2008] Source: Jaehwan Kim[ETRI], HyungSoo Lee[ETRI], Jeong Ki Pack[CNU], Tae Hong Kim[CNU] Contact: Jae Whan Kim, ETRI, Korea Voice: :+82-42-860-5338, E-mail:kimj@etri.re.kr Re: [n/a] Abstract: Provideneeds of channel modeling for medical implanted communication system Purpose: To provide basic channel characteristics for the manufacture of medical implantable communication system Notice: This document has been prepared to assist the IEEE P802.15. It is offered as a basis for discussion and is not binding on the contributing individual's or organization's. The material in this document is subject to change in form and content after further study. The contributor's reserves the right to add, amend or withdraw material contained herein. Release: The contributor acknowledges and accepts that this contribution becomes the property of IEEE and maybe made publicly available by P802.15.

  2. Contents • Channel models for BAN • Methods for channel modeling • Channel modeling 1 • Channel modeling 2 • Channel modeling 3 • Conclusions

  3. Channel models for WBAN

  4. Methods for channel modeling • Channel modeling • - Scenario 1(CM1), Scenario 2(CM2 ) • - FDTD method was used for channel modeling • using Remcom XFDTD 6.5 • - Frequency: 403.5 MHz • Human body model • - Korean male phantom model • (voxel size : 3 mm) • TX antenna • - Hertzian dipole • - Channel models must not be affected by the transmitting antenna • pattern. So the proper compensation for directive gain as well as • polarization are needed.

  5. Simulation scenario • Transmitter location : 17 positions • Near surface implants : 9 • Deep tissue implants : 8 16 15 1 2 14 3 11 12 4 7 13 6 5 8 10 9 • Receiver location : 138 points • Implants(in-body) : 78 • Body surface : 60 17

  6. Channel modeling 1 • Path loss model • - Path loss model used in IEEE P802.15-08-0033-05-0006 • - PL(d)=PL(d0)+10nlog10(d/d0)+S [dB] • d0 : reference distance, 50 mm • n : path loss exponent • S : random scatter around the regression line, N(0, σs) • Channel modeling • Grouping of the transmitter location • Deep tissue implant • Near surface implant • Grouping of the receiver location • In-body (implant) • Body surface : from the skin to 2 cm away from the skin

  7. Path Loss vs. Distance Scatter Plot(CM1) • Deep tissue implant to another • implant • (the maximum pathlength is about 180 cm) • Near surface implant to another • implant • (the maximum pathlength is about 180 cm) (n=3.65, PL(d0)=46.52, σs=8.84) ( n=4.33, PL(d0)=47.70, σs=5.77 )

  8. Path Loss vs. Distance Scatter Plot(CM2) • Deep tissue implant to body surface • (the maximum pathlength is about 180 cm) • Near surface implant to body • surface • (the maximum pathlength is about 180 cm) (n=5.22, PL(d0)=37.28, σs=5.76) (n=3.53, PL(d0)=45.37, σs=9.46)

  9. Path Loss vs. Distance Scatter Plot(CM1) • Deep tissue implant to another • implant (fitted up to 50 cm) • Near surface implant to another • implant (fitted up to 50 cm) (n=6.17, PL(d0)=34.89, σs=5.44) (n=5.34, PL(d0)=35.48, σs=8.42)

  10. Path Loss vs. Distance Scatter Plot(CM2) • Deep tissue implant to body surface • (fitted up to 50 cm) • Near surface implant to body • surface (fitted up to 50 cm) (n=6.06, PL(d0)=31.95, σs=5.75) (n=4.34, PL(d0)=40.17, σs=10.09)

  11. Summary of the channel modeling 1 • When we fit the path loss model for the whole receiver locations (the maximum pathlength is about 180 cm), the modeling parameters are slightly different from the results of IEEE 802.15-08-0519-00-0006. • However, the parameter values are well within the statistical error bound (one σs value). • <Implant to Implant CM1 (Scenario S1)> • <Implant to Body surface CM2 (Scenario S2)>

  12. When fitted up to 50 cm as shown in IEEE 802.15-08-0519-00-0006, we obtained similar results as in IEEE P802.15-08-0033-05-0006. • <Implant to Implant CM1 (Scenario S1)> • <Implant to Body surface CM2 (Scenario S2)>

  13. Channel modeling 2 • Path loss model • - Same as the model used in IEEE P802.15-08-0033-05-0006 • Channel modeling • - We tried channel modeling for different scenarios (different grouping of TX’s or RX’s). • - Modeling 2A • Path loss was modeled for total implant locations (i. e., the whole TX’s are grouped together for fitting) • - Modeling 2B • Path loss was modeled for the total implant locations with the RX points grouped differently. • Receiver groups: head, trunk, lower parts of the body, arms • - Modeling 2C • Path loss was modeled for the type of the transmitting implanted devices (Implant to Implant) • Type of devices : capsule endoscope, glucose-insulin, pacemaker, deep brain stimulator, healthcare shoes

  14. Path Loss vs. Distance Scatter Plot(2A) • Total implant(deep tissue and • near surface) to implant • Total implant(deep tissue and • near surface) to body surface (n=4.01,PL(d0)=43.97, σs=8.89) (n=3.83, PL(d0)=48.46, σs=8.53)

  15. Summary of the channel modeling 2A • Modeling parameters fitted for all transmitting • implanted devices

  16. Path Loss vs. Distance Scatter Plot(2B) • Implant to head • Implant to lower parts of the body (n=4.03, PL(d0)=47.11, σs=8.65 ) (n=3.75, PL(d0)=47.89, σs=9.78)

  17. Path Loss vs. Distance Scatter Plot(2B) • Implant to trunk • Implant to arms (n=4.26, PL(d0)=44.99, σs=8.21 ) (n=3.81, PL(d0)=48.02, σs=7.97)

  18. Summary of the channel modeling 2B • Modeling parameters for different RX locations • ( Implant to Implant)

  19. Path Loss vs. Distance Scatter Plot(2C) • Capsule endoscope • (gullet) • Glucose Insulin • (right hand) (n=4.48, PL(d0)=45.57, σs=6.42 ) (n=3.23, PL(d0)=43.52, σs=6.46)

  20. Path Loss vs. Distance Scatter Plot(2C) • Pacemaker • (heart) • Deep brain stimulator • (right throat) (n=4.29, PL(d0)=46.75, σs=6.55 ) (n=3.60, PL(d0)=47.96, σs=10.07)

  21. Path Loss vs. Distance Scatter Plot(2C) • Healthcare shoes (sole) (n=3.83, PL(d0)=36.72, σs=5.54 )

  22. Summary of the channel modeling 2C • Modeling parameters for different transmitting • implanted devices (Implant to Implant)

  23. Summaries of the channel modeling 2 • We have modeled WBAN channels for three • different modeling scenarios(2A, 2B, 2C). • The results of the modeling scenario 2A are similar to those of the channel modeling 1. Thus, it seems that the modeling scenario in IEEE 802.15-08-0519-00-0006could be simplified. • The results of the modeling scenario 2B show that there are no large difference in the model parameters for different body parts. So, the modeling scenario in IEEE 802.15-08-0519-00-0006 seems to be good.

  24. When we classify the transmitting implants in more detail(modeling scenario 2C), the parameter values are similar to the results of the modeling scenario 2A. • Thus, the detailed classification of the transmitting implants does not seem to be necessary.

  25. Channel modeling 3 • Path loss model • - PL(d)=PL(d0)+10nlog10(d/d0)+ a*d +S [dB] • d0 : reference distance, 50 mm • a : coefficient for absorption loss • n : path loss exponent, N(0, σs) • S : random scatter around the regression line • - The absorption loss of biological tissues is very large. Because the absorption loss is a linear term in a log scale, we tried a modified path loss model by adding the first order term to WBAN channel more accurately. • Channel modeling • - Same as in the channel modeling 1

  26. Path loss vs. Distance Scatter Plot(CM1) • Deep tissue implant to another • implant • Near surface implant to another • implant (n=5.87, PL(d0)=36.80, a=-19.70, σs=8.22) (n=7.39, PL(d0)=33.58, a=-28.00, σs=5.07)

  27. Path loss vs. Distance Scatter Plot(CM2) • Deep tissue implant to body surface • Near surface implant to body surface (n=4.89, pl=39.83, a=-13.44, σs=9.30) (n=7.38, PL(d0)=29.37, a=-24.96, σs=5.45)

  28. Summary of the channel modeling 3 • The comparison of the results of the channel modeling 3 shows that the modified pass loss model seems to be better, in terms of the modeling accuracy (i. e. standard deviation σs). • <Implant to Implant CM1 (Scenario S1)> • <Implant to Body surface CM2 (Scenario S2)>

  29. Conclusions • We have modeled WBAN channel by two path loss models. • We also tried different scenarios for channel modeling. • Extensive simulation to characterize the MICS path loss has been performed and statistical path loss models at 403.5 MHz are derived. • The models are based on 9 near surface implants and 8 deep tissue implants for the Korean male phantom model.

  30. The modeling results show that • Classification of the implants to two groups(deep tissue and near surface) might not be necessary. • The modified path loss model seems to work better. • The modeling parameters could be different depending on the path length for fitting, the location of TX’s or RX’s, but they are well within the statistical error bound (one σs value).

  31. References • Doc : 15-08-0519-00-0006 A statistical path loss model for MICS • Doc : 15-08-0033-05-0006 Channel model for body area network (BAN)

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