research-article

Platypus: Indoor Localization and Identification through Sensing of Electric Potential Changes in Human Bodies

Authors:

Tobias Grosse-Puppendahl,

Xavier Dellangnol,

Christian Hatzfeld,

Matthias R. Hastall,

Marco GruteserAuthors Info & Claims

MobiSys '16: Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services

Pages 17 - 30

https://doi.org/10.1145/2906388.2906402

Published: 20 June 2016 Publication History

Abstract

Platypus is the first system to localize and identify people by remotely and passively sensing changes in their body electric potential which occur naturally during walking. While it uses three or more electric potential sensors with a maximum range of 2 m, as a tag-free system it does not require the user to carry any special hardware. We describe the physical principles behind body electric potential changes, and a predictive mathematical model of how this affects a passive electric field sensor. By inverting this model and combining data from sensors, we infer a method for localizing people and experimentally demonstrate a median localization error of 0.16 m. We also use the model to remotely infer the change in body electric potential with a mean error of 8.8 % compared to direct contact-based measurements. We show how the reconstructed body electric potential differs from person to person and thereby how to perform identification. Based on short walking sequences of 5 s, we identify four users with an accuracy of 94 %, and 30 users with an accuracy of 75 %. We demonstrate that identification features are valid over multiple days, though change with footwear.

References

[1]

F. Adib, Z. Kabelac, D. Katabi, and R.C. Miller. 3D tracking via body radio reflections. In Proceedings of the 11th USENIX Conference on Networked Systems Design and Implementation, NSDI'14, pages 317--329, Berkeley, CA, USA, 2014. USENIX Association.

Digital Library

[2]

H. Aly and M. Youssef. An analysis of device-free and device-based wifi-localization systems. Int. J. Ambient Comput. Intell., 6(1):1--19, 2014.

Digital Library

[3]

A.D. Aronoff, W.H. Boghosian, and H.A. Jenkinson. Electrostatic means for intrusion detection and ranging. Technical report, DTIC Document, 1965.

[4]

A. Aydin, P.B. Stiffell, R.J. Prance, and H. Prance. A high sensitivity calibrated electric field meter based on the electric potential sensor. Meas. Sci. Technol., 21, 2010.

[5]

S.T. Beardsmore-Rust. Remote applications of electric potential sensors in electrically unshielded environments. PhD thesis, University of Sussex, 2010.

[6]

C. BenAbdelkader, R. Cutler, and L. Davis. Person identification using automatic height and stride estimation. In Pattern Recognition, 2002. Proceedings. 16th International Conference on, volume 4, pages 377--380 vol.4, 2002.

Digital Library

[7]

M.S. Brandstein and H.F. Silverman. A practical methodology for speech source localization with microphone arrays. Computer Speech and Language, 11(2):91--126, 1997.

[8]

A. Branzel, C. Holz, D. Hoffmann, D. Schmidt, M. Knaust, P. Lühne, R. Meusel, S. Richter, and P. Baudisch. Gravityspace: Tracking users and their poses in a smart room using a pressure-sensing floor. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI'13, pages 725--734, New York, NY, USA, 2013. ACM.

Digital Library

[9]

A. Braun, H. Heggen, and R. Wichert. Capfloor - a flexible capacitive indoor localization system. In S. Chessa and S. Knauth, editors, Evaluating AAL Systems Through Competitive Benchmarking. Indoor Localization and Tracking, volume 309 of Communications in Computer and Information Science, pages 26--35. Springer Berlin Heidelberg, 2012.

[10]

G.S.P. Castle. Contact charging between insulators. Journal of Electrostatics, 40/41:13--20, 1997.

[11]

J. Chang, A.J. Kelly, and J.M. Crowley. Handbook of Electrostatic Processes. Marcel Dekker, Inc., 1995.

[12]

K. Chintalapudi, A. Padmanabha Iyer, and V.N. Padmanabhan. Indoor localization without the pain. In Proceedings of the Sixteenth Annual International Conference on Mobile Computing and Networking, MobiCom'10, pages 173--184, New York, NY, USA, 2010. ACM.

Digital Library

[13]

A.J. Clippingdale. The sensing of spatial electrical potential. PhD thesis, University of Sussex, 1993.

[14]

G. Cohn, S. Gupta, T. Lee, D. Morris, J.R. Smith, M.S. Reynolds, D.S. Tan, and S.N. Patel. An ultra-low-power human body motion sensor using static electric field sensing. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing, UbiComp'12, pages 99--102, New York, NY, USA, 2012. ACM.

Digital Library

[15]

Gabe Cohn, Daniel Morris, Shwetak Patel, and Desney Tan. Humantenna: using the body as an antenna for real-time whole-body interaction. In CHI '12, pages 1901--1910, 2012.

Digital Library

[16]

N. U. Czech-Damal, G. Dehnhardt, P. Manger, and W. Hanke. Passive electroreception in aquatic mammals. Journal of Comparative Physiology A, 199(6):555--563, 2013.

[17]

T. Ficker. Electrification of human body by walking. Journal of Electrostatics, 64:10--16, 2006.

[18]

S. Gabriel, R.W. Lau, and C. Gabriel. The dielectric properties of biological tissues: II. Measurements in the frequency range 10 Hz to 20 GHz. Physics in Medicine and Biology, 41(11):2251--2269, 1996.

[19]

W. Gebrial, R. J. Prance, C.J. Harland, and T.D. Clark. Noninvasive imaging using an array of electric potential sensors. Review of Scientific Instruments, 77(6), 2006.

[20]

T. Grosse-Puppendahl, Y. Berghoefer, A Braun, R. Wimmer, and A Kuijper. Opencapsense: A rapid prototyping toolkit for pervasive interaction using capacitive sensing. In Pervasive Computing and Communications (PerCom), 2013 IEEE International Conference on, pages 152--159, March 2013.

[21]

T. Grosse-Puppendahl, A. Braun, F. Kamieth, and A. Kuijper. Swiss-Cheese Extended: An Object Recognition Method for Ubiquitous Interfaces based on Capacitive Proximity Sensing. In CHI'13, pages 1401--1410, 2013.

Digital Library

[22]

Y. Guo and M. Hazas. Localising speech, footsteps and other sounds using resource-constrained devices. In 10th International Conference on Information Processing in Sensor Networks (IPSN), pages 330--341, 2011.

[23]

Marian Haescher, Denys J. C. Matthies, Gerald Bieber, and Bodo Urban. Capwalk: A capacitive recognition of walking-based activities as a wearable assistive technology. In Proceedings of the 8th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA'15, pages 35:1--35:8, New York, NY, USA, 2015. ACM.

Digital Library

[24]

M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I.H. Witten. The weka data mining software: An update. SIGKDD Explorations, 11(1), 2009.

Digital Library

[25]

C.J. Harland, T.D. Clark, and R.J. Prance. Electric potential probes - new directions in the remote sensing of the human body. Measurement Science and Technology, 13(2):163--169, 2002.

[26]

D. Hauschildt and N. Kirchhof. Advances in thermal infrared localization: Challenges and solutions. In 2010 International Conference on Indoor Positioning and Indoor Navigation, pages 1--8, 2010.

[27]

K. Hidaka. Electric field and voltage measurement by using electro-optic sensor. In Eleventh International Symposium on High Voltage Engineering, volume 2, pages 1--14, 1999.

[28]

T.W. Hnat, E. Griffiths, R. Dawson, and K. Whitehouse. Doorjamb: Unobtrusive room-level tracking of people in homes using doorway sensors. In Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems, SenSys'12, pages 309--322, New York, NY, USA, 2012. ACM.

Digital Library

[29]

P.M. Ireland. The role of changing contact in sliding triboelectrification. Journal of Physics D: Applied Physics, 41(2), 2008.

[30]

C.D. Kidd, R. Orr, G.D. Abowd, C.G. Atkeson, I.A. Essa, B. MacIntyre, E. Mynatt, T.E. Starner, and W. Newstetter. The aware home: A living laboratory for ubiquitous computing research. In Cooperative Buildings. Integrating Information, Organizations, and Architecture, volume 1670 of Lecture Notes in Computer Science, pages 191--198. Springer Berlin Heidelberg, 1999.

Digital Library

[31]

F. Kirchbuchner, T. Grosse-Puppendahl, M.R. Hastall, M. Distler, and A. Kuijper. Ambient intelligence from senior citizens' perspectives: Understanding privacy concerns, technology acceptance, and expectations. In Ambient Intelligence, volume 9425 of Lecture Notes in Computer Science, pages 48--59. Springer International Publishing, 2015.

[32]

T. Kivim\"aki, T. Vuorela, P. Peltola, and J. Vanhala. A review on device-free passive indoor positioning methods. International Journal of Smart Home, 8(1):71--91, 2014.

[33]

K. Kurita, R. Takizawa, and H. Kumon. Detection of human walking motion based on measurement system of current generated by electrostatic induction. In ICCAS-SICE, 2009, pages 5485--5488, 2009.

[34]

G. Laput, C. Yang, R. Xiao, A. Sample, and C. Harrison. Em-sense: Touch recognition of uninstrumented, electrical and electromechanical objects. In Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology, UIST'15, pages 157--166, New York, NY, USA, 2015. ACM.

Digital Library

[35]

H. Liu, H. Darabi, P. Banerjee, and J. Liu. Survey of wireless indoor positioning techniques and systems. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 37(6):1067--1080, 2007.

Digital Library

[36]

J. Liu, Y. Wang, Y. Chen, J. Yang, X. Chen, and J. Cheng. Tracking vital signs during sleep leveraging off-the-shelf wifi. In Proceedings of the 16th ACM International Symposium on Mobile Ad Hoc Networking and Computing, pages 267--276. ACM, 2015.

Digital Library

[37]

P. Llovera, P. Molinié, A. Soria, and A. Quijano. Measurements of electrostatic potentials and electric fields in some industrial applications: Basic principles. Journal of Electrostatics, 67(2/3):457--461, 2009.

[38]

J. Lowell and A.C. Rose-Innes. Contact electrification. Advances in Physics, 29(6):947--1023, 1980.

[39]

R. Mautz. Indoor positioning technologies. ETH Zurich, 2012. Habilitation thesis.

[40]

Microsoft. Kinect for Windows features. http://www.microsoft.com/en-us/kinectforwindows/meetkinect/features.aspx (date accessed 2015-08--24).

[41]

G. Monaci and A. Pandharipande. Indoor user zoning and tracking in passive infrared sensing systems. In Proceedings of the 20th European Signal Processing Conference (EUSIPCO), pages 1089--1093, 2012.

[42]

S. Narayana, R.V. Prasad, V.S. Rao, T.V. Prabhakar, S.S. Kowshik, and M.S. Iyer. PIR sensors: Characterization and novel localization technique. In Proceedings of the 14th International Conference on Information Processing in Sensor Networks, IPSN'15, pages 142--153, 2015.

Digital Library

[43]

A. Pachi and T. Ji. Frequency and velocity of people walking. The Structural Engineer, 83(3):36--40, 2005.

[44]

Plessey Semiconductors. EPIC sensor. http://www.plesseysemiconductors.com/epic-plessey-semiconductors.php (date accessed 2015--12-09).

[45]

H. Prance, P. Watson, R.J. Prance, and S.T. Beardsmore-Rust. Position and movement sensing at metre standoff distances using ambient electric field. Meas. Sci. Technol., 23, 2012.

[46]

R. Prance and C. Harland. Electric potential sensor, July 2 2009. US Patent App. 12/374,359.

[47]

Q. Pu, S. Gupta, S. Gollakota, and S. Patel. Whole-home gesture recognition using wireless signals. In Proceedings of the 19th Annual International Conference on Mobile Computing & Networking, MobiCom '13, pages 27--38, New York, NY, USA, 2013. ACM.

Digital Library

[48]

T.S. Ralston, G.L. Charvat, and J.E. Peabody. Real-time through-wall imaging using an ultrawideband multiple-input multiple-output (mimo) phased array radar system. In Phased Array Systems and Technology (ARRAY), 2010 IEEE International Symposium on, pages 551--558, Oct 2010.

[49]

J. Rekimoto and H. Wang. Sensing gamepad: Electrostatic potential sensing for enhancing entertainment oriented interactions. In Extended Abstracts on Human Factors in Computing Systems, pages 1457--1460, 2004.

Digital Library

[50]

C.A. Rezende, R.F. Gouveia, M.A. da Silva, and F. Galembeck. Detection of charge distributions in insulator surfaces. Journal of Physics: Condensed Matter, 21(26), 2009.

[51]

H. Rimminen. Detection of human movement by near field imaging: development of a novel method and applications. PhD thesis, Aalto University, School of Science and Technology, 2011.

[52]

M. Shankar, J.B. Burchett, Q. Hao, B.D. Guenther, and D.J. Brady. Human-tracking systems using pyroelectric infrared detectors. Optical Engineering, 45(10):106401--106401, 2006.

[53]

J.R. Smith. Electric Field Imaging. PhD thesis, Massachusetts Institute of Technology, 1999.

Digital Library

[54]

R. Srinivasan, C. Chen, and D.J. Cook. Activity recognition using actigraph sensor. In Proceedings of the Fourth Int. Workshop on Knowledge Discovery form Sensor Data (ACM SensorKDD'10), Washington, DC, July, pages 25--28, 2010.

[55]

Statistisches Bundesamt. Mikrozensus - Fragen zur Gesundheit - Körpermaße der Bevölkerung 2013 (in German), 2014.

[56]

T. Teixeira, G. Dublon, and A. Savvides. A survey of human-sensing: Methods for detecting presence, count, location, track, and identity. Technical report, ENALAB, 2010.

[57]

M. Valtonen, T. Vuorela, L. Kaila, and J. Vanhala. Capacitive indoor positioning and contact sensing for activity recognition in smart homes. J. Ambient Intell. Smart Environ., 4(4):305--334, 2012.

Digital Library

[58]

G. Wang, Y. Zou, and K.and Ni L.M. Zhou, Z.and Wu. We can hear you with wi-fi! In Proceedings of the 20th Annual International Conference on Mobile Computing and Networking, MobiCom '14, pages 593--604, New York, NY, USA, 2014. ACM.

Digital Library

[59]

Q. Wang. Dynamic time warping (dtw), 2014. http://mathworks.com/matlabcentral/fileexchange/43156 (date accessed: 2015/11/15).

[60]

A. Williams, D. Ganesan, and A. Hanson. Aging in place: Fall detection and localization in a distributed smart camera network. In Proceedings of the 15th ACM International Conference on Multimedia, MM'07, pages 892--901, New York, NY, USA, 2007. ACM.

Digital Library

[61]

J. Wilson and N. Patwari. See-through walls: Motion tracking using variance-based radio tomography networks. Mobile Computing, IEEE Transactions on, 10(5):612--621, May 2011.

Digital Library

[62]

K. Woolford. Defining accuracy in the use of kinect v2 for exercise monitoring. In Proceedings of the 2nd International Workshop on Movement and Computing, pages 112--119. ACM, 2015.

Digital Library

[63]

P. Wu and F. Li. The pyroelectric sensor based system: Human tracking and self-calibration scheme. In 2012 International Conference on Information Science and Technology (ICIST), pages 839--846, 2012.

[64]

C. You, H. Kao, B. Ho, N. Chen, Y. Hsieh, P. Huang, and H. Chu. Thermalprobe: Exploring the use of thermal identification for per-user energy metering. In Internet of Things (iThings), 2014 IEEE International Conference on, pages 554--561, Sept 2014.

Digital Library

[65]

X. Zhou, Q. Hao, and H. Fei. 1-bit walker recognition with distributed binary pyroelectric sensors. In 2010 IEEE Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), pages 168--173, 2010.

Cited By

Bian SLiu MZhou BLukowicz PMagno M(2024)Body-Area Capacitive or Electric Field Sensing for Human Activity Recognition and Human-Computer InteractionProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435558:1(1-49)Online publication date: 6-Mar-2024
https://dl.acm.org/doi/10.1145/3643555
Wang RTan RYan ZLu C(2024)Orientation-Aware 3D SLAM in Alternating Magnetic Field from PowerlinesProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314467:4(1-25)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3631446
Cao HLiu DJiang HLuo J(2024)MagSign: Harnessing Dynamic Magnetism for User Authentication on IoT DevicesIEEE Transactions on Mobile Computing10.1109/TMC.2022.321685123:1(597-611)Online publication date: Jan-2024
https://doi.org/10.1109/TMC.2022.3216851
Show More Cited By

Index Terms

Platypus: Indoor Localization and Identification through Sensing of Electric Potential Changes in Human Bodies

Recommendations

Flexible Localization and Identification System Based on RFID and Vision Tracking Technologies
ISCCS '11: Proceedings of the 2011 International Symposium on Computer Science and Society

Among existing indoor localization systems, considering the costs and accuracy, RFID has been one of the best choices for indoor positioning. However, years of research experiences found that the signal strength of RFID is not sufficiently stable and ...
Application and Modeling of a Magnetic WSN for Target Localization
UKSIM '13: Proceedings of the 2013 UKSim 15th International Conference on Computer Modelling and Simulation

The aim of this study is modeling ferromagnetic targets for localization and identification of such objects by a wireless sensor network (WSN). MICAz motes were used for setting up a wireless sensor network utilizing a centralized tree -based system. ...
Localization Using Anonymous Measurements
DCOSS '15: Proceedings of the 2015 International Conference on Distributed Computing in Sensor Systems

Range-based IEEE 802.15.4 localization systems currently require relatively high anchor density for indoor deployments. It can therefore be beneficial to use external sources of transmission as additional anchors. We present methods for using WiFi ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

MobiSys '16: Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services

June 2016

440 pages

ISBN:9781450342698

DOI:10.1145/2906388

General Chairs:
Rajesh Balan
Singapore Management University
,
Archan Misra
Singapore Management University
,
Program Chairs:
Sharad Agarwal
Microsoft
,
Cecilia Mascolo
University of Cambridge

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Sponsors

SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

In-Cooperation

SIGOPS: ACM Special Interest Group on Operating Systems

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 June 2016

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

MobiSys'16

Sponsor:

SIGMOBILE

MobiSys'16: The 14th Annual International Conference on Mobile Systems, Applications, and Services

June 26 - 30, 2016

Singapore, Singapore

Acceptance Rates

MobiSys '16 Paper Acceptance Rate 31 of 197 submissions, 16%;

Overall Acceptance Rate 274 of 1,679 submissions, 16%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

56
Total Citations
View Citations
675
Total Downloads

Downloads (Last 12 months)28
Downloads (Last 6 weeks)3

Reflects downloads up to 01 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Bian SLiu MZhou BLukowicz PMagno M(2024)Body-Area Capacitive or Electric Field Sensing for Human Activity Recognition and Human-Computer InteractionProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435558:1(1-49)Online publication date: 6-Mar-2024
https://dl.acm.org/doi/10.1145/3643555
Wang RTan RYan ZLu C(2024)Orientation-Aware 3D SLAM in Alternating Magnetic Field from PowerlinesProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314467:4(1-25)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3631446
Cao HLiu DJiang HLuo J(2024)MagSign: Harnessing Dynamic Magnetism for User Authentication on IoT DevicesIEEE Transactions on Mobile Computing10.1109/TMC.2022.321685123:1(597-611)Online publication date: Jan-2024
https://doi.org/10.1109/TMC.2022.3216851
Kurita K(2024)Noncontact Measurement Technique for Simulated Hemiplegia Walking Motion Using Ultrahigh Sensitive Electrostatic Induction SensorIEEE Sensors Journal10.1109/JSEN.2024.338802524:11(17817-17824)Online publication date: 1-Jun-2024
https://doi.org/10.1109/JSEN.2024.3388025
Kusneniwar HGhosh SSen S(2024)SonicGlass: An Obstacle Detection and Navigation System Using Smartglass-Based Ultrasonic Sensors2024 16th International Conference on COMmunication Systems & NETworkS (COMSNETS)10.1109/COMSNETS59351.2024.10427277(603-607)Online publication date: 3-Jan-2024
https://doi.org/10.1109/COMSNETS59351.2024.10427277
Miao YGu CYan ZChau STan RLin QHu WHe SChen J(2023)TouchKeyProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35962647:2(1-21)Online publication date: 12-Jun-2023
https://dl.acm.org/doi/10.1145/3596264
Li XYin MZhang YYang PWan CGuo XTan H(2023)Back-Guard: Wireless Backscattering Based User Sensing With Parallel Attention ModelIEEE Transactions on Mobile Computing10.1109/TMC.2022.321501222:12(7466-7481)Online publication date: Dec-2023
https://doi.org/10.1109/TMC.2022.3215012
Yan ZSong QTan R(2023)Touch-to-Access Device Authentication For Indoor Smart ObjectsIEEE Transactions on Mobile Computing10.1109/TMC.2021.308949722:2(1185-1197)Online publication date: 1-Feb-2023
https://doi.org/10.1109/TMC.2021.3089497
Hu YWang JLi YYan Y(2023)Localization of Charged Objects Using a Planar Electrostatic Sensor ArrayIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2023.332809072(1-5)Online publication date: 2023
https://doi.org/10.1109/TIM.2023.3328090
Man MWei M(2023)A Field High Resolution Measurement Method for Irregular Surface Electrostatic PotentialIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2023.323408072(1-11)Online publication date: 2023
https://doi.org/10.1109/TIM.2023.3234080
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

EPUB

View this article in ePub.

Figures

Tables

Media

View Table of Conten