research-article

FEMO: A Platform for Free-weight Exercise Monitoring with RFIDs

Authors:

Longfei Shangguan,

Jizhong ZhaoAuthors Info & Claims

SenSys '15: Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems

Pages 141 - 154

https://doi.org/10.1145/2809695.2809708

Published: 01 November 2015 Publication History

Abstract

Regular free-weight exercise helps to strengthen the body's natural movements and stabilize muscles that are important to strength, balance, and posture of human beings. Prior works have exploited wearable sensors or RF signal changes (e.g., WiFi and Blue tooth) for activity sensing, recognition and countingetc. However, none of them have incorporate three key factors necessary for a practical free-weight exercise monitoring system: recognizing free-weight activities on site, assessing their qualities, and providing useful feedbacks to the bodybuilder promptly. Our FEMO system responds to these demands, providing an integrated free-weight exercise monitoring service that incorporates all the essential functionalities mentioned above. FEMO achieves this by attaching passive RFID tags on the dumbbells and leveraging the Doppler shift profile of the reflected backscatter signals for on-site free-weight activity recognition and assessment. The rationale behind FEMO is 1): since each free-weight activity owns unique arm motions, the corresponding Doppler shift profile should be distinguishable to each other and serves as a reliable signature for each activity. 2): the Doppler profile of each activity has a strong spatial-temporal correlation that implicitly reflects the quality of each performed activity. We implement FEMO with COTS RFID devices and conduct a two-week experiment. The preliminary result from 15 volunteers demonstrates that FEMO can be applied to a variety of free-weight activities and users, and provide valuable feedbacks for activity alignment.

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Cited By

Wei MZhao DZhang LWang CZhang YWang QFan XZhong YMao S(2025)Wi-Fitness: Improving Wi-Fi Sensing With Video Perception for Smart FitnessIEEE Internet of Things Journal10.1109/JIOT.2024.347629112:3(2876-2889)Online publication date: 1-Feb-2025
https://doi.org/10.1109/JIOT.2024.3476291
Maharjan RMendu SMariani MAbdullah SHansen J(2024)Exploring user engagement with real-time verbal feedback from an exoskeleton-based virtual exercise coachDIGITAL HEALTH10.1177/2055207624130265210Online publication date: 5-Dec-2024
https://doi.org/10.1177/20552076241302652
Wang FLv YZhu MDing HHan J(2024)XRF55Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435438:1(1-34)Online publication date: 6-Mar-2024
https://dl.acm.org/doi/10.1145/3643543
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cover image ACM Conferences

SenSys '15: Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems

November 2015

526 pages

ISBN:9781450336314

DOI:10.1145/2809695

General Chair:
Junehwa Song
KAIST, South Korea
,
Program Chairs:
Tarek Abdelzaher
University of Illinois at Urbana-Champaign, USA
,
Cecilia Mascolo
University of Cambridge, UK

Copyright © 2015 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 ACM 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]

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Publication History

Published: 01 November 2015

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Funding Sources

NSFC
Specialized Research Fund for the Doctoral Program of Higher Education
National Basic Research Program of China (973 Program)
Natural Science Basic Research Plan in Shaanxi Province of China

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SenSys '15

Sponsor:

SenSys '15: The 13th ACM Conference on Embedded Network Sensor Systems

November 1 - 4, 2015

Seoul, South Korea

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SenSys '15 Paper Acceptance Rate 27 of 132 submissions, 20%;

Overall Acceptance Rate 198 of 990 submissions, 20%

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Cited By

Wei MZhao DZhang LWang CZhang YWang QFan XZhong YMao S(2025)Wi-Fitness: Improving Wi-Fi Sensing With Video Perception for Smart FitnessIEEE Internet of Things Journal10.1109/JIOT.2024.347629112:3(2876-2889)Online publication date: 1-Feb-2025
https://doi.org/10.1109/JIOT.2024.3476291
Maharjan RMendu SMariani MAbdullah SHansen J(2024)Exploring user engagement with real-time verbal feedback from an exoskeleton-based virtual exercise coachDIGITAL HEALTH10.1177/2055207624130265210Online publication date: 5-Dec-2024
https://doi.org/10.1177/20552076241302652
Wang FLv YZhu MDing HHan J(2024)XRF55Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435438:1(1-34)Online publication date: 6-Mar-2024
https://dl.acm.org/doi/10.1145/3643543
Yang YChen THuang YGuo XShangguan L(2024)MAF: Exploring Mobile Acoustic Field for Hand-to-Face Gesture InteractionsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642437(1-20)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642437
Wang PJiang RGuo ZLiu C(2024)Afitness: Fitness Monitoring on Smart Devices via Acoustic Motion ImagesACM Transactions on Sensor Networks10.1145/359261220:4(1-24)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3592612
Kaur HRani VKumar M(2024)Human activity recognition: A comprehensive reviewExpert Systems10.1111/exsy.1368041:11Online publication date: 27-Jul-2024
https://doi.org/10.1111/exsy.13680
Chen YYu JKong LZhu YTang F(2024)Sensing Human Gait for Environment-Independent user Authentication using Commodity RFID DevicesIEEE Transactions on Mobile Computing10.1109/TMC.2023.3318753(1-13)Online publication date: 2024
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Ahmad IUllah AChoi W(2024)WiFi-Based Human Sensing With Deep Learning: Recent Advances, Challenges, and OpportunitiesIEEE Open Journal of the Communications Society10.1109/OJCOMS.2024.34115295(3595-3623)Online publication date: 2024
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Zhou SLu ZHan ZGuo LDeng JWen XYang XZhao J(2024)MuSense: Multiperson Continuous Activity Sensing Using Commodity Wi-FiIEEE Internet of Things Journal10.1109/JIOT.2023.334537611:8(15000-15021)Online publication date: 15-Apr-2024
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Liu XLi FCao YZhai SYang SWang Y(2024)PPGSpotter: Personalized Free Weight Training Monitoring Using Wearable PPG SensorIEEE INFOCOM 2024 - IEEE Conference on Computer Communications10.1109/INFOCOM52122.2024.10621212(2468-2477)Online publication date: 20-May-2024
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