FEMO : A platform for free-weight exercise monitoring with RFIDs
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Author(s)
Detail(s)
| Original language | English |
|---|---|
| Title of host publication | SenSys 2015 - Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 141-154 |
| ISBN (print) | 9781450336314 |
| Publication status | Published - 1 Nov 2015 |
| Externally published | Yes |
Publication series
| Name | SenSys 2015 - Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems |
|---|
Conference
| Title | 13th ACM Conference on Embedded Networked Sensor Systems, SenSys 2015 |
|---|---|
| Place | Korea, Republic of |
| City | Seoul |
| Period | 1 - 4 November 2015 |
Link(s)
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 counting etc. 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. © 2015 ACM.
Research Area(s)
- Activity recognition and assessment, RFID
Bibliographic Note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
Citation Format(s)
FEMO: A platform for free-weight exercise monitoring with RFIDs. / Ding, Han; Shangguan, Longfei; Yang, Zheng et al.
SenSys 2015 - Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems. Association for Computing Machinery, Inc, 2015. p. 141-154 (SenSys 2015 - Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems).
SenSys 2015 - Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems. Association for Computing Machinery, Inc, 2015. p. 141-154 (SenSys 2015 - Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems).
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
