Mechanisms contributing to reduced knee stiffness during movement

Abstract

The ability to modulate the mechanical properties of our limbs contributes to our ability to interact with the physical world in a consistent and predictable manner. An individual joint’s contributions to whole limb mechanics can be quantified by its joint impedance, which characterizes the torque generated about a joint in response to external perturbations of position. A number of studies have estimated joint impedance during movement and have shown that it can be much lower than it is during posture. However, the mechanisms contributing to these differences remain unknown partly because conditions known to affect impedance, including muscle activation and joint angles, have not been carefully controlled across studies. The goal of this study was to contrast knee impedance during continuous volitional movements with that during maintained postures spanning a similar range of joint angles and muscle activations, and to explore physiological mechanisms likely to contribute to the observed differences. We found that knee impedance was substantially lower during movement than during matched postural tasks, even for matched muscle activations. At times, the impedance during movement was even lower than that measured during isometric tasks with no volitional muscle activity. These decreases in impedance could be attributed in part to reduced stretch reflexes during movement, and to an effect of movement itself on reducing knee impedance.

Neurophysiological validation of simultaneous intrinsic and reflexive joint impedance estimates

“…Thus, self-generated movements cannot be analyzed using the PC model and other system identification techniques are required, e.g. [ 23 ]. Compared to our experimental conditions, recent advances did show that isometric conditions with faster variations in voluntary torques can be studied using the PC model [ 24 ].…”

Unifying system identification and biomechanical formulations for the estimation of muscle, tendon and joint stiffness during human movement

“…Computationally, the short data segment (SDS) method (such as Ludvig et al [31]) is a desirable option to estimate the nonparametric model dynamics, which slowly vary with time. The SDS method has been widely used in the literature to estimate joint impedance and stiffness from human experimental data [33][34][35][36]. An overview of pros and cons relative to the SDS method is depicted in figure 3.…”

Revealing Time-Varying Joint Impedance With Kernel-Based Regression and Nonparametric Decomposition

“…Both methods are ensemble averaging methods, requiring multiple repetitions of the same timevarying behavior. The first is a method proposed by Ludvig and Perreault [44] who used a nonparametric estimator in the time domain to successfully identify joint impedance averaging across short data segments (SDS) and multiple (but a reduced number of) realizations [27]. We implemented this method ourselves.…”