A body sensor network with electromyogram and inertial sensors: Multimodal interpretation of muscular activities

Hassan Ghasemzadeh, Roozbeh Jafari, Balakrishnan Prabhakaran

Research output: Contribution to journalArticlepeer-review

89 Scopus citations


The evaluation of the postural control system (PCS) has applications in rehabilitation, sports medicine, gait analysis, fall detection, and diagnosis of many diseases associated with a reduction in balance ability. Standing involves significant muscle use to maintain balance, making standing balance a good indicator of the health of the PCS. Inertial sensor systems have been used to quantify standing balance by assessing displacement of the center of mass, resulting in several standardized measures. Electromyogram (EMG) sensors directly measure the muscle control signals. Despite strong evidence of the potential of muscle activity for balance evaluation, less study has been done on extracting unique features from EMG data that express balance abnormalities. In this paper, we present machine learning and statistical techniques to extract parameters from EMG sensors placed on the tibialis anterior and gastrocnemius muscles, which show a strong correlation to the standard parameters extracted from accelerometer data. This novel interpretation of the neuromuscular system provides a unique method of assessing human balance based on EMG signals. In order to verify the effectiveness of the introduced features in measuring postural sway, we conduct several classification tests that operate on the EMG features and predict significance of different balance measures.

Original languageEnglish (US)
Article number5308441
Pages (from-to)198-206
Number of pages9
JournalIEEE Transactions on Information Technology in Biomedicine
Issue number2
StatePublished - Mar 2010
Externally publishedYes


  • Accelerometer
  • Body sensor networks
  • Electromyogram (EMG)
  • Standing balance

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science Applications
  • Electrical and Electronic Engineering


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