Demo of MagnifiSense: inferring device interaction using wrist-worn passive magneto-inductive sensors
Authors: 
Edward Wang, Tien-Jui Lee, Alex Maraiakakis, 
Mayank Goel, 
Shwetak Patel, 
Sidhant GuptaAuthors Info & Claims
Edward Wang, Tien-Jui Lee, Alex Maraiakakis, Mayank Goel, Shwetak Patel, Sidhant GuptaAuthors Info & ClaimsPages 415 - 417
Abstract
The different electronic devices we use on a daily basis produce distinct electromagnetic radiation due to the differences in their underlying electrical components. We present MagnifiSense, a low-power wearable system that uses three passive magneto-inductive sensors and a minimal ADC setup to identify the device a person is operating. MagnifiSense achieves this by analyzing the near-field electromagnetic radiation from common components such as motors, rectifiers, and modulators. MagnifiSense achieves a classification accuracy of 82.6% using a model-agnostic classifier and 94.0% using a model-specific classifier. The purpose of this demo is to both illustrate the real-time waveform the system uses and also demonstrate the classification capability to attendees.
References
[1]
Arrillaga, J. and Watson, N., Power System Harmonics. 2003.
[2]
Wang, E., Ipser, S., Little, P., Duncan, N., and Liu, B. Design Considerations for Leveraging Over-familiar Items for Elderly Health Monitors 2 Overview of Current Solution Space.
[3]
Wang, E. J., Lee, T.-J., Mariakakis, A., Goel, M., Gupta, S., and Patel, S. N. MagnifiSense: Inferring Device Interaction using Wrist-Worn Passive Magneto-Inductive Sensors. Ubicomp '15, (2015).
[4]
Zouba, N., Boulay, B., Bremond, F., and Thonnat, M. Monitoring activities of daily living (ADLs) of elderly based on 3D key human postures. ICVW '08, (2008), 37--50.
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- Demo of MagnifiSense: inferring device interaction using wrist-worn passive magneto-inductive sensors
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Information & Contributors
Information
Published In
September 2015
1626 pages
ISBN:9781450335751
DOI:10.1145/2800835
- General Chairs:
- Kenji Mase,
- Marc Langheinrich,
- Daniel Gatica-Perez,
- Program Chairs:
- Hans Gellersen,
- Tanzeem Choudhury,
- Koji Yatani
Copyright © 2015 Owner/Author.
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.
Sponsors
- Yahoo! Japan: Yahoo! Japan
- SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
- FX Palo Alto Laboratory, Inc.: FX Palo Alto Laboratory, Inc.
- Google Inc.
- ACM: Association for Computing Machinery
- Rakuten Institute of Technology: Rakuten Institute of Technology
- Microsoft: Microsoft
- Bell Labs: Bell Laboratories
- SIGCHI: ACM Special Interest Group on Computer-Human Interaction
- KDDI
- Panasonic: Panasonic Corporation
- NTT DoCoMo
- Telefónica: Telefónica
- ISTC-PC: Intel Science and Technology Center for Pervasive Computing
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 07 September 2015
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Qualifiers
- Demonstration
Conference
UbiComp '15
UbiComp '15: The 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing
September 7 - 11, 2015
Osaka, Japan
Acceptance Rates
Overall Acceptance Rate 764 of 2,912 submissions, 26%
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