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

Große-Puppendahl, Tobias and Dellangnol, Xavier and Hatzfeld, Christian and Fu, Biying and Kupnik, Mario and Kuijper, Arjan and Hastall, Matthias R. and Scott, James and Gruteser, Marco (2016):
Platypus - Indoor Localization and Identification through Sensing Electric Potential Changes in Human Bodies.
ACM, New York, In: The 14th ACM International Conference on Mobile Systems, Applications, and Services, Singapore, DOI: 10.1145/2906388.2906402,
[Conference or Workshop Item]

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 0.16m. 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.

Item Type: Conference or Workshop Item
Erschienen: 2016
Creators: Große-Puppendahl, Tobias and Dellangnol, Xavier and Hatzfeld, Christian and Fu, Biying and Kupnik, Mario and Kuijper, Arjan and Hastall, Matthias R. and Scott, James and Gruteser, Marco
Title: Platypus - Indoor Localization and Identification through Sensing Electric Potential Changes in Human Bodies
Language: English
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 0.16m. 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.

Publisher: ACM, New York
Uncontrolled Keywords: Guiding Theme: Smart City, Research Area: Human computer interaction (HCI), Research Area: Modeling (MOD), Capacitive sensors, Indoor localization systems, Human action recognition, Feature classifications
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Mathematical and Applied Visual Computing
Event Title: The 14th ACM International Conference on Mobile Systems, Applications, and Services
Event Location: Singapore
Date Deposited: 07 May 2019 09:38
DOI: 10.1145/2906388.2906402
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