An EMG-driven model of the upper extremity and estimation of long head biceps force

Joseph Langenderfer, Suzanne LaScalza, Amy Mell, James E. Carpenter, John E. Kuhn, Richard E. Hughes

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

An electromyography (EMG) driven model of the upper extremity has been developed that incorporates musculoskeletal geometry of the glenohumeral and elbow joints, estimated relevant physiologic muscle parameters including optimal muscle lengths, and EMG activity. The model is designed to predict forces in muscles spanning the glenohumeral joint resulting from functionally relevant tasks. The model is composed of four sub-models that comprise a mathematical as well as graphical three-dimensional representation of the upper extremity: a musculoskeletal model for estimation of muscle-tendon lengths and moment arms, a Hill-based muscle force model, a model for estimating optimal muscle lengths, and a model for estimation of muscle activation from EMG signal of the biceps. The purpose of this paper is to describe the components of the model, as well as the data required to drive the model. Collection of data is described in the context of applying the model to determine biceps muscle forces for testing of functional tasks. Results obtained from applying the model to analyze the functional tasks are summarized, and model strengths and limitations are discussed.

Original languageEnglish
Pages (from-to)25-39
Number of pages15
JournalComputers in Biology and Medicine
Volume35
Issue number1
DOIs
StatePublished - Jan 2005
Externally publishedYes

Keywords

  • Elbow
  • Musculoskeletal model
  • Shoulder
  • Upper extremity

Fingerprint

Dive into the research topics of 'An EMG-driven model of the upper extremity and estimation of long head biceps force'. Together they form a unique fingerprint.

Cite this