A Highly Efficient Semiphenomenological Model of a Half-Sarcomere for Real-Time Prediction of Mechanical Behavior

Abstract

With existent biomechanical models of skeletal muscle, challenges still exist in implementing real-time predictions for contraction statuses that are particularly significant to biomechanical and biomedical engineering. Because of this difficulty, this paper proposed a decoupled scheme of the links involved in the working process of a sarcomere and established a semiphenomenological model integrating both linear and nonlinear frames of no higher than a second-order system. In order to facilitate engineering application and cybernetics, the proposed model contains a reduced number of parameters and no partial differential equation, making it highly concise and computationally efficient. Through the simulations of various contraction modes, including isometric, isotonic, successive stretch and release, and cyclic contractions, the correctness and efficiency of the model, are validated. Although this study targets half-sarcomeres, the proposed model can be easily extended to describe the larger-scale mechanical behavior of a muscle fiber or a whole muscle.

Improving the Transparency of an Exoskeleton Knee Joint Based on the Understanding of Motor Intent Using Energy Kernel Method of EMG

“…As presented in the earlier work [19], the harmonic oscillator hypothesis also leads to another characteristic quantity of "natural frequency" of EMG signal, the physical meaning of which is still under investigation, but initial analysis showed that this natural frequency is independent of MU firing rate, further supporting the oscillator hypothesis of EMG. The semiphenomenological model can be used as a cybernetic model because the inputs and outputs of the model are all external measureable quantities, and linear frames are extracted from basic in vitro experimental data, ensuring the high computational efficiency for engineering applications [13].…”

“…From the perspective of biophysics, the boundary between cybernetic and biomechanical models of muscle is very dim, while the word "cybernetic" here refers to a model that can take effect in practical engineering. For this purpose, a semiphenomenological model was developed in our previous work [13] to derive an engineering-oriented cybernetic model.…”

“…In fact, all these issues are leading us to a common solution, i.e., building a clearly structured cybernetic model for muscular contraction based on a deep understanding of biomechanics, which thus serves as the theoretical basis for introducing EMG-based estimates to the control system and explaining HMIM. For this purpose, the semiphenomenological biomechanical/cybernetic model of skeletal muscle established in our previous work [13] would be applied in this paper. As for motion decoding using EMG, many methods, such as RMS, MPF [14], wavelet, fractal, and FIR [15]- [17], etc., have been proposed, while for dynamic control, the real-time performance, robustness, and the accuracy of existent methods are still at issue.…”

Gaussian Process-Integrated State Space Model for Continuous Joint Angle Prediction from EMG and Interactive Force in a Human-Exoskeleton System

“…In order to better interpret the mechanism of human-exoskeleton interaction, the SP muscular model which aims at concise structure, high efficiency, and comprehensive descriptive function is applied here [31].…”

“…In the proposed model, interactive force is applied as the measurement model output and the EMG signal is used as the state model input to indicate muscle activation. Hill's muscle model and semi-phenomenological (SP) model [31] are adopted to acquire the forward dynamics of joint motion for the state model and the human-machine interaction mechanism interpretation for the measurement model, respectively. In practical applications, the GP-based NARX model and back propagation neural network (BPNN) are applied to provide better flexibility and adaptivity.…”