Measurement of Dynamic Joint Stiffness from Multiple Short Data Segments

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 25; no. 7; pp. 925 - 934
• Main Authors: Jalaleddini, Kian, Golkar, Mahsa A., Kearney, Robert E.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.07.2017
• Subjects: Biological system modeling; biomechanics; Biomedical measurement; biomedical signal processing; Computer Simulation; Data models; Delays; Elastic Modulus - physiology; Female; Humans; Knee Joint - physiology; Mathematical model; Models, Biological; Muscle Contraction - physiology; Muscle, Skeletal - physiology; Muscles; Nonlinear dynamical systems; Range of Motion, Articular - physiology; Reproducibility of Results; Sensitivity and Specificity; state-space methods; system identification; Torque; Viscosity; Young Adult
• ISSN: 1534-4320; 1558-0210; 1558-0210
• DOI: 10.1109/TNSRE.2017.2659749

This paper presents our new method, Short Segment-Structural Decomposition SubSpace (SS-SDSS), for the estimation of dynamic joint stiffness from short data segments. The main application is for data sets that are only piecewise stationary. Our approach is to: 1) derive a data-driven, mathematical model for dynamic stiffness for short data segments; 2) bin the non-stationary data into a number of short, stationary data segments; and 3) estimate the model parameters from subsets of segments with the same properties. This method extends our previous state-spacework by recognizing that initial conditions have important effects for short data segments; consequently, initial conditions are incorporated into the stiffness model and estimated for each segment. A simulation study that faithfully replicated experimental conditions delineated the range of experimental conditions for which the method can successfully identify stiffness. An experimental study on the ankle of a healthy subject during a torque matching tasks demonstrated the successful estimation of dynamic stiffness in a slow, time-varying experiment. Together, the simulation and experimental studies demonstrate that the SS-SDSS method is a valuable tool to measure stiffness in functionally important tasks.