Modeling the Human Elbow Joint Dynamics from Surface Electromyography

Modeling the Human Elbow Joint Dynamics from Surface Electromyography

Andrés Felipe Ruiz-Olaya (Antonio Nariño University, Colombia)
DOI: 10.4018/978-1-4666-6090-8.ch005

Abstract

Biomechanical modelling and analysis of human motion are main topics of interest for a number of disciplines, ranging from biomechanics to human movement science. There exist various experimental and theoretical techniques developed to model the biomechanics and human motor system. A classic way to characterize a system is done by perturbation analysis, through applying an external perturbation and the observation of changes in the dynamic of system. In literature, human joint dynamics has been studied mainly in relation to external perturbations. However, those perturbations interact with the natural human motor behaviour. This chapter describes an approximation for non-invasive biomechanical modelling of the elbow joint dynamics from electromyographic information. A case study presents results obtained aimed at deriving a relationship between the dynamic behaviour of the human elbow joint and Surface Electromyography (SEMG) information in postural control. A set of experiments were carried out to measure bioelectrical (SEMG) and biomechanics information from human elbow joint, during postural control (i.e. isometric contractions) and correlate them with mechanical impedance at elbow joint. Estimates of elbow impedance were obtained by applying torque perturbations to the forearm. The results demonstrate that it is possible to estimate human joint dynamics from SEMG. The obtained results can contribute to the field of human motor control and also to its application in robotics and other engineering applications through the definition, specification and characterization of properties associated with the human upper limb and strategies used by people to command it.
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Introduction

It is well known phenomena that human skeletal muscle has elastic-like and viscous-like properties, which change widely with the level of muscle activation. Also, the human neuromuscular control system has highly developed self-adaptive properties. The dynamic response of a limb is largely insensitive to external forces in a wide range. It also appears that adaptive compensation for external changes occurs very rapidly in relation to the dominant dynamics of the limb/joint system and the dynamic behavior may include a feedback and a feedforward component (van der Helm et al., 2002). In literature, numerous studies have modeled the dynamic behavior of human body segments and joints as mechanical impedance (Dolan et al., 1993; Tsuji et al., 1995). Mechanical impedance in this context may be defined as the dynamic relationship between forces and position variations, and can be characterized by its stiffness, viscosity and inertia (which are functions of the muscle condition).

Measurement and understanding of these dynamics is important in several areas such as rehabilitation engineering, biomechanics, basic motor control research, bionics, humanoid robotics, among others (Tanaka et al., 2007). This understanding about the human limb/joint dynamics permits to develop bio-inspired control strategies to be implemented in new devices, such as prostheses and orthoses and to explore new therapies in disabled people by pathologies and disorders affecting the human motor system.

Human joints dynamics may be approximate as mechanical impedance (Dolan, 1993). Modulation of mechanical impedance provides the basis for several theories in human motor control such as the α-model and λ-model equilibrium point theories, the virtual trajectory theory, and dynamic interaction in manipulation, (Hogan, 1985). The general finding is that increasing joint impedance, both through co-contraction and reflex modulation, stabilises the limb to external force fields.

Quantification of the mechanical impedance of the human joints and the muscle-skeletal system has a long history (Kearney & Hunter, 1990). The mechanical impedance of a system is best described by its transfer function, which can have been estimated using continuous perturbations. In fact, in literature human joint dynamics has been studied mainly in relation to external perturbations (Acosta et al., 2000; Franklin et al., 2003; Xu & Hollerbach, 1999); however, such perturbations interact with the natural behaviour of the motor control system and disturb the task under study (Kirsch et al., 1994). It will be beneficial to estimate such mechanical impedance in a non-invasive way; in this context, electromyography may provide such non-invasive way. Recently, researchers have been studying the relationship between the Surface Electromyography (SEMG) and torque produced about a joint, as a means of non-invasively estimating the joint/musculoskeletal dynamics (Bru & Amarantini, 2008; Clancy et al., 2012).

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