A review of classification techniques of EMG signals during isotonic and isometric contractions

Nurhazimah Nazmi, Mohd Azizi Abdul Rahman, Shin Ichiroh Yamamoto, Siti Anom Ahmad, Hair Zamzuri, Saiful Amri Mazlan

Research output: Contribution to journalReview articlepeer-review

221 Citations (Scopus)


In recent years, there has been major interest in the exposure to physical therapy during rehabilitation. Several publications have demonstrated its usefulness in clinical/medical and human machine interface (HMI) applications. An automated system will guide the user to perform the training during rehabilitation independently. Advances in engineering have extended electromyography (EMG) beyond the traditional diagnostic applications to also include applications in diverse areas such as movement analysis. This paper gives an overview of the numerous methods available to recognize motion patterns of EMG signals for both isotonic and isometric contractions. Various signal analysis methods are compared by illustrating their applicability in real-time settings. This paper will be of interest to researchers who would like to select the most appropriate methodology in classifying motion patterns, especially during different types of contractions. For feature extraction, the probability density function (PDF) of EMG signals will be the main interest of this study. Following that, a brief explanation of the different methods for pre-processing, feature extraction and classifying EMG signals will be compared in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above.

Original languageEnglish
Article number1304
JournalSensors (Switzerland)
Issue number8
Publication statusPublished - 2016 Aug 17


  • Classifications
  • EMG signals
  • Feature extractions
  • Isometric contractions
  • Isotonic contractions
  • Probability density functions

ASJC Scopus subject areas

  • Analytical Chemistry
  • Information Systems
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering


Dive into the research topics of 'A review of classification techniques of EMG signals during isotonic and isometric contractions'. Together they form a unique fingerprint.

Cite this