A practical strategy for sEMG-based knee joint moment estimation during gait and its validation in individuals with cerebral palsy

IEEE Trans Biomed Eng. 2012 May;59(5):1480-7. doi: 10.1109/TBME.2012.2187651. Epub 2012 Mar 9.

Abstract

Individuals with cerebral palsy have neurological deficits that may interfere with motor function and lead to abnormal walking patterns. It is important to know the joint moment generated by the patient's muscles during walking in order to assist the suboptimal gait patterns. In this paper, we describe a practical strategy for estimating the internal moment of a knee joint from surface electromyography (sEMG) and knee joint angle measurements. This strategy requires only isokinetic knee flexion and extension tests to obtain a relationship between the sEMG and the knee internal moment, and it does not necessitate comprehensive laboratory calibration, which typically requires a 3-D motion capture system and ground reaction force plates. Four estimation models were considered based on different assumptions about the functions of the relevant muscles during the isokinetic tests and the stance phase of walking. The performance of the four models was evaluated by comparing the estimated moments with the gold standard internal moment calculated from inverse dynamics. The results indicate that an optimal estimation model can be chosen based on the degree of cocontraction. The estimation error of the chosen model is acceptable (normalized root-mean-squared error: 0.15-0.29, R: 0.71-0.93) compared to previous studies (Doorenbosch and Harlaar, 2003; Doorenbosch and Harlaar, 2004; Doorenbosch, Joosten, and Harlaar, 2005), and this strategy provides a simple and effective solution for estimating knee joint moment from sEMG.

Publication types

  • Research Support, N.I.H., Intramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Biomechanical Phenomena
  • Cerebral Palsy / physiopathology*
  • Child
  • Electromyography / methods*
  • Female
  • Gait / physiology*
  • Humans
  • Knee Joint / physiology*
  • Male
  • Models, Biological
  • Muscle Contraction / physiology
  • Reproducibility of Results
  • Signal Processing, Computer-Assisted*