Task-relevant adaptation of musculoskeletal impedance during posture and movement

Abstract

One approach to designing robotic prostheses that interact with the environment in a naturally compliant fashion is to design them with mechanical properties that replicate the functions of an intact limb. Limb and joint mechanics can be quantified using estimates of impedance, a measure that can also be regulated in robotic systems using feedback control. Numerous studies have quantified the impedance of intact joints under static postural conditions. However, the few studies that have quantified impedance during movement have shown that it differs drastically from estimates obtained during static postural conditions. Specifically, the static component of impedance, known as stiffness, is substantially lower during movement control than during postural control. This difference has important implications for designing biomimetic prostheses and other robotic systems, though the factors contributing to the differences between posture and movement and the extent of these differences under different movement conditions are not yet known. In this paper, we systematically explore how human knee stiffness is affected by the kinematic and mechanical variables that constantly vary during movement. To do so we used a non-parametric system identification algorithm that makes few assumptions on the structure of the system or the relationship of the system to these changing kinematic and mechanical variables. We found that stiffness did not correlate with the net joint torque, as occurs during postural conditions, but rather with computed active muscle torque. Furthermore, we found that externally imposed movements during passive conditions cause a drop in joint stiffness, implying that at least some of the observed results are due to changes in intrinsic muscle or joint mechanics rather than altered neural control.