IFC: Your invisible fitness coach based on csi sensing

Wei Zhang, Hongbo Ni, Meijuan He, Junqi Liu, Zhu Wang, Xingshe Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Exercise is of vital importance to people's health. Nowadays, more and more people trend to involve in it at home for lacking time and accelerating pace of modern life. However, many of them have difficulties in obtaining good performance due to the lack of professional guidance. For helping users with effective fitness evaluation in home environment and encouraging them to keep exercising, this paper presents a non-invasive, low-cost and high-precision fitness assistance system based on the commercial WIFI device. The IFC(Invisible Fitness Coach) system applies the CSI(Channel State Information) signal to perceive the user's exercise information in home, and accurately divides the continuous actions via the principal component variance, and then extracts the features from each completed action to train a multi-class SVM model to recognize them, finally, it analyzes the user's exercise frequency, intensity, duration, etc., then feeds back the comprehensive analysis based on the above features to him/her. The results of the experiment including 2160 workout samples from 6 volunteers shows that the continuous motion segmentation precision and accuracy of the system reached 94.8% and 96.5%, and the recognition rate of the activity reached 92.2%. To evaluate the IFC system, we record and analyze the fitness situation of a volunteer for one month. After the tracking experiment, the indicators of his exercise have observably been improved comparing with those one month ago. Experiments show that the IFC system can be applied as an individual family fitness coach in home environment.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1011-1018
Number of pages8
ISBN (Electronic)9781728140346
DOIs
StatePublished - Aug 2019
Event2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019 - Leicester, United Kingdom
Duration: 19 Aug 201923 Aug 2019

Publication series

NameProceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019

Conference

Conference2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019
Country/TerritoryUnited Kingdom
CityLeicester
Period19/08/1923/08/19

Keywords

  • Activity recognition
  • Channel state information
  • Device-free sensing
  • Fitness assistance

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