In the current research, the muscle equivalent linear damping coefficient which is introduced as the force-velocity relation in a muscle model and the corresponding time constant are investigated. In order to reach this goal, a 1D skeletal muscle model was used. Two characterizations of this model using a linear force-stiffness relationship (Hill-type model) and a nonlinear one have been implemented. The OpenSim platform was used for verification of the model. The isometric activation has been used for the simulation. The equivalent linear damping and the time constant of each model were extracted by using the results obtained from the simulation. The results provide a better insight into the characteristics of each model. It is found that the nonlinear models had a response rate closer to the reality compared to the Hill-type models.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s00422-016-0680-z | DOI Listing |
Updates Surg
January 2025
Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy.
Clinical risk prediction models are ubiquitous in many surgical domains. The traditional approach to develop these models involves the use of regression analysis. Machine learning algorithms are gaining in popularity as an alternative approach for prediction and classification problems.
View Article and Find Full Text PDFSensors (Basel)
January 2025
National Institute of Natural Hazards, Beijing 100085, China.
Borehole strainmeters are essential tools for observing crustal deformation. In long-term observational applications, the dynamic changes in crustal deformation over multi-year scales often exceed the single measurement range of borehole strainmeters. Expanding the measurement range while maintaining high precision is a critical technical challenge.
View Article and Find Full Text PDFSensors (Basel)
January 2025
College of Electrical and Information Engineering, Hunan University, Changsha 410082, China.
This paper presents the design and performance evaluation of an inductive conductivity sensor with a double tuning impedance matching network to enhance sensitivity and improve linearity. The sensor's equivalent circuit model is analyzed and verified through simulation, and impedance matching is shown to significantly increase the sensor's output signal, particularly at low conductivity measurements. Double tuning impedance matching expands the frequency response range and optimizes power transfer efficiency, achieving a higher power factor across a broader frequency range.
View Article and Find Full Text PDFMicroorganisms
December 2024
Advanced Institute of Convergence Technology, Suwon 16229, Republic of Korea.
The lipid content of nine dinoflagellates was analyzed using flow cytometry to compare lipid levels. Additionally, the correlation between lipid content, cell size, and carbon content in dinoflagellates was evaluated using BODIPY 505/515 staining. The flow cytometry side scatter (SSC) effectively represented relative cell size, showing a linear relationship with the equivalent spherical diameter (ESD).
View Article and Find Full Text PDFMed Biol Eng Comput
January 2025
State Key Laboratory of Power Transmission Equipment Technology, School of Electrical Engineering, Chongqing, University, Chongqing, 400044, People's Republic of China.
Selecting channels for motor imagery (MI)-based brain-computer interface (BCI) systems can not only enhance the portability of the systems, but also improve the decoding performance. Hence, we propose a cross-domain-based channel selection (CDCS) approach, which effectively minimizes the number of EEG channels used while maintaining high accuracy in MI recognition. The EEG source imaging (ESI) technique is employed to map scalp EEG into the cortical source domain.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!