Quantifying Joint Stiffness During Movement: A Quantitative Comparison of Time-Varying System Identification Methods

Careful control of joint impedance, or dynamic joint stiffness, is crucial for successful performance of movement. Time-varying system identification (TV-SysID) enables quantification of joint impedance during movement. Several TV-SysID methods exist, but have never been systematically compared. Here, we simulate time-varying joint behavior...

Quantitative comparison of time-varying system identification methods to describe human joint impedance

Accurate and swift tuning of joint impedance is crucial to perform movement and interaction with our environment. Time-varying system identification enables quantification of joint impedance during movement. Many methods have been developed over the years, each with their own mathematical approach and underlying assumptions. Yet, for the...

The Cortical Response Evoked by Robotic Wrist Perturbations Reflects Level of Proprioceptive Impairment After Stroke

Background: Proprioception is important for regaining motor function in the paretic upper extremity after stroke. However, clinical assessments of proprioception are subjective and require verbal responses from the patient to applied proprioceptive stimuli. Cortical responses evoked by robotic wrist perturbations and measured by...

Revealing time-varying joint impedance with kernel-based regression and nonparametric decomposition

During movements, humans continuously regulate their joint impedance to minimize control effort and optimize performance. Joint impedance describes the relationship between a joint's position and torque acting around the joint. Joint impedance varies with joint angle and muscle activation and differs from trial-to-trial due to inherent...

Adaptation rate in joint dynamics depends on the time-varying properties of the environment

During movement, our central nervous system (CNS) takes into account the dynamics of our environment to optimally adapt our joint dynamics. In this study we explored the adaptation of shoulder joint dynamics when a participant interacted with a time-varying virtual environment created by a haptic manipulator. Participants performed a position...

Nonparametric identification of time-varying human joint admittance

In this study, a nonparametric method, developed in Lataire et al. (2012), is applied to the identification of linear time-varying human joint admittance. The aim of the method, denoted Skirt Decomposition method, is to reconstruct the time-varying system function. The main contribution of the paper is to evaluate the possibilities and...

Nonlinear coupling between cortical oscillations and muscle activity during isotonic wrist flexion

Coupling between cortical oscillations and muscle activity facilitates neuronal communication during motor control. The linear part of this coupling, known as corticomuscular coherence, has received substantial attention, even though neuronal communication underlying motor control has been demonstrated to be highly nonlinear. A full assessment...