Phascope: Fine-grained, Fast, Flexible Motion Profiling based on Phase Offset in Acoustic OFDM Signal
Pages 292 - 301
Abstract
Acoustic Doppler shift estimation is a cost-effective way to implement Human-Computer Interaction applications across existing smart devices such as smart phones and smart spekaers. However, due to the inherent uncertainty principle in the traditional time-frequency analysis, it remains challenging to profile motions accurately and timely. In this paper, phase offset in acoustic OFDM signal is leveraged for developing Phascope, a fine-grained, fast and flexible motion profiling scheme. We evaluate Phascope using simulation and experiment on COTS devices. Sub-millisecond response time is achieved for Phascope in our experiment. Besides, with optimal subcarrier selection and SNR of 30 dB over all subcarriers, Phascope can estimate motion speed of 0.1 m/s with 6.75% root-mean-square error (RMSE) compared to optimized FFT method.
References
[1]
Daniel Ashbrook, Daniel Ashbrook, Sung Hyuck Lee, Sung Hyuck Lee, and Shwetak Patel. 2014. AirLink: sharing files between multiple devices using in-air gestures. In ACM International Joint Conference on Pervasive and Ubiquitous Computing. 565--569.
[2]
Md Tanvir Islam Aumi, Sidhant Gupta, Mayank Goel, Eric Larson, and Shwetak Patel. 2013. DopLink: using the doppler effect for multi-device interaction. In Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing. ACM, 583--586.
[3]
Huijie Chen, Fan Li, and Yu Wang. 2017. EchoTrack: Acoustic device-free hand tracking on smart phones. In INFOCOM 2017-IEEE Conference on Computer Communications, IEEE. IEEE, 1--9.
[4]
Yong Soo Cho, Jaekwon Kim, Won Young Yang, and Chung G Kang. 2010. MIMO-OFDM wireless communications with MATLAB. John Wiley & Sons.
[5]
Leon Cohen. 1995. Time-frequency analysis. Vol. 778. Prentice Hall PTR Englewood Cliffs, NJ:.
[6]
Biying Fu, Dinesh Vaithyalingam Gangatharan, Arjan Kuijper, Florian Kirchbuchner, and Andreas Braun. 2017. Exercise Monitoring On Consumer Smart Phones Using Ultrasonic Sensing. In Proceedings of the 4th international Workshop on Sensor-based Activity Recognition and Interaction. ACM, 9.
[7]
Hang Gao, Xiangyu Xu, Jiadi Yu, Yingying Chen, Yanmin Zhu, Guangtao Xue, and Minglu Li. {n. d.}. ER: Early Recognition of Inattentive Driving Leveraging Audio Devices on Smartphones. ({n. d.}).
[8]
Marcel Golay. 1961. Complementary series. IRE Transactions on Information Theory 7, 2 (1961), 82--87.
[9]
Sidhant Gupta, Daniel Morris, Shwetak Patel, and Desney Tan. 2012. Soundwave: using the doppler effect to sense gestures. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 1911--1914.
[10]
Seung Hee Han and Jae Hong Lee. 2005. An overview of peak-to-average power ratio reduction techniques for multicarrier transmission. IEEE wireless communications 12, 2 (2005), 56--65.
[11]
Wenguang Mao, Jian He, and Lili Qiu. 2016. CAT: high-precision acoustic motion tracking. In International Conference on Mobile Computing and NETWORKING. 69--81.
[12]
Rajalakshmi Nandakumar, Shyamnath Gollakota, and Nathaniel Watson. 2015. Contactless Sleep Apnea Detection on Smartphones. In International Conference on Mobile Systems, Applications, and Services. 45--57.
[13]
Rajalakshmi Nandakumar, Vikram Iyer, Desney Tan, and Shyamnath Gollakota. 2016. Fingerio: Using active sonar for fine-grained finger tracking. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. ACM, 1515--1525.
[14]
Wenjie Ruan, Quan Z. Sheng, Lei Yang, Tao Gu, Peipei Xu, and Longfei Shangguan. 2016. AudioGest:enabling fine-grained hand gesture detection by decoding echo signal. In ACM International Joint Conference on Pervasive and Ubiquitous Computing. 474--485.
[15]
Zheng Sun, Aveek Purohit, Raja Bose, and Pei Zhang. 2013. Spartacus:spatially-aware interaction for mobile devices through energy-efficient audio sensing. In Proceeding of the International Conference on Mobile Systems, Applications, and Services. 263--276.
[16]
Wei Wang, Alex X Liu, and Ke Sun. 2016. Device-free gesture tracking using acoustic signals. In International Conference on Mobile Computing and NETWORKING. 82--94.
[17]
Xuyu Wang, Runze Huang, and Shiwen Mao. 2017. SonarBeat: Sonar phase for breathing beat monitoring with smartphones. In Sensing, Communication, and Networking (SECON), 2017 14th Annual IEEE International Conference on. IEEE, 1--2.
[18]
Jie Yang, Simon Sidhom, Gayathri Chandrasekaran, Tam Vu, Hongbo Liu, Nicolae Cecan, Yingying Chen, Marco Gruteser, and Richard P Martin. 2011. Detecting driver phone use leveraging car speakers. In Proceedings of the 17th annual international conference on Mobile computing and networking. ACM, 97--108.
[19]
Qifan Yang, Tang Hao, Xuebing Zhao, Li Yin, and Sanfeng Zhang. 2015. Dolphin: Ultrasonic-Based Gesture Recognition on Smartphone Platform. In IEEE International Conference on Computational Science and Engineering. 1461--1468.
[20]
Sangki Yun, Yi Chao Chen, and Lili Qiu. 2015. Turning a Mobile Device into a Mouse in the Air. In International Conference on Mobile Systems, Applications, and Services. 15--29.
[21]
Sangki Yun, Yi-Chao Chen, Huihuang Zheng, Lili Qiu, and Wenguang Mao. 2017. Strata: Fine-Grained Acoustic-based Device-Free Tracking. In Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services. ACM, 15--28.
[22]
Huanle Zhang, Wan Du, Pengfei Zhou, Mo Li, and Prasant Mohapatra. 2016. DopEnc: acoustic-based encounter profiling using smartphones. In International Conference on Mobile Computing and NETWORKING. 294--307.
Index Terms
- Phascope: Fine-grained, Fast, Flexible Motion Profiling based on Phase Offset in Acoustic OFDM Signal
Recommendations
Phascope: Fine-Grained, Fast, Flexible Motion Profiling based on Phase Offset in Acoustic OFDM Signal
AbstractAcoustic Doppler shift estimation is a cost-effective way to implement Human-Computer Interaction applications across existing smart devices such as smart phones and smart spekaers. However, due to the inherent uncertainty principle in the ...
A novel carrier frequency offset tracking scheme in MQAM-OFDM systems
WiCOM'09: Proceedings of the 5th International Conference on Wireless communications, networking and mobile computingA novel carrier frequency offset tracking scheme for Multilevel Quadrature Amplitude Modulation-Orthogonal Frequency Division Multiplexing (MQAM-OFDM) systems is proposed using a designed conjugate code composed of MQAM mapping values and their complex ...
Limits of the OFDM use in the radio mobile context
Orthogonal frequency division multiplexing (OFDM) is very vulnerable to the carrier frequency offset (CFO) generated mainly by the Doppler effect. The inter-carrier interference (ICI) generated by this offset degrades the system performances. Before ...
Comments
Information & Contributors
Information
Published In
November 2018
490 pages
Copyright © 2018 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].
In-Cooperation
- EAI: The European Alliance for Innovation
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 05 November 2018
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
MobiQuitous '18
Acceptance Rates
Overall Acceptance Rate 26 of 87 submissions, 30%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 91Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 06 Nov 2024
Other Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in