Exercise recognition using accelerometer based body-attached platform

Joo Hyung Kim, Jeong Eom Lee, Yong Chan Park, Daehwan Kim, Gwi Tae Park

Research output: Contribution to journalArticlepeer-review


u-Healthcare service is one of attractive applications in ubiquitous environment. In this paper, we propose a method to recognize exercises using a new accelerometer based body-attached platform for supporting u-Healthcare service. The platform consists of a device for measuring accelerometer data and a device for receiving the data. The former measures a user's motion data using a 3~axis accelerometer. The latter transmits the accelerometer data to a computer for recognizing the user's exercise. The algorithm for exercise recognition classifies the type of exercise using principle components analysis(PCA) from the accelerometer data transformed by discrete fourier transform(DFT), and estimates the repetition count of the recognized exercise using a peak detection algorithm. We evaluate the performance of the algorithm from the accuracy of the recognition of exercise type and the error rate of the estimation of repetition count. In our experimental result, the algorithm shows the accuracy about 98%.

Original languageEnglish (US)
Pages (from-to)2275-2280
Number of pages6
JournalTransactions of the Korean Institute of Electrical Engineers
Issue number11
StatePublished - Nov 2009
Externally publishedYes


  • Accelerometer
  • Exercise recognition
  • Principle components analysis
  • U-Healthcare service

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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