Neuromusculoskeletal models have been used to investigate the neural control and the biomechanical requirements of a physical behavior. Neuromusculoskeletal simulations are commonly performed through inverse dynamics to analyze the already observed human movements in silico. Although this simulation technique can provide great insight into the kinematics and kinetics of the observed data, it cannot predict the movements that have not been observed. On the other hand, motion predictive simulations, by considering the task constraints and the neuromuscular requirements, can predict kinematics of a novel movement. Such simulation methods must ideally capture the features and functionalities of the motor control system to mimic human neuromechanical behavior. Although, in the past few years, several studies have developed models and techniques for such predictive frameworks, a well-established rigorous method that can accurately predict neuromusculoskeletal dynamics of healthy and pathologic individuals is still lacking in the research community.
A nice application example that seems to be an emerging need for such musculoskeletal models is in the design of assistive devices for rehabilitation and augmentations purposes. The integrated human and device models would save time and cost of multiple prototyping steps in both the design and evaluation phases of such devices. Bio-fidelic predictive neuromusculoskeletal models could delineate crucial parameters of a design and elucidate the effect of a device conceptual design on the human’s kinematics and kinetics. Therefore, the design process will become human-centered in which a design optimization step includes all important factors, such as mechanical, electrical, material, as well as physiological.
This Research Topic calls for submissions that cover following subtopics:
? New methods and approaches in the field of musculoskeletal modeling and simulation, including motion prediction, neural control, central pattern generators, subject-robot co-simulations, subject-specific simulations
? Simulated effects of neurological conditions such as stroke, spinal cord injury, and cerebral palsy on the neural control and muscle properties.
? Design of human-centered assistive devices such as prostheses, orthoses, and hard and soft exoskeletons by investigating properties such as kinematic alignment, changes in subject movement pattern, strap and joint reaction forces, metabolic energy consumption, etc.
? Studies of human-robot interaction by taking advantage of musculoskeletal models.
Neuromusculoskeletal models have been used to investigate the neural control and the biomechanical requirements of a physical behavior. Neuromusculoskeletal simulations are commonly performed through inverse dynamics to analyze the already observed human movements in silico. Although this simulation technique can provide great insight into the kinematics and kinetics of the observed data, it cannot predict the movements that have not been observed. On the other hand, motion predictive simulations, by considering the task constraints and the neuromuscular requirements, can predict kinematics of a novel movement. Such simulation methods must ideally capture the features and functionalities of the motor control system to mimic human neuromechanical behavior. Although, in the past few years, several studies have developed models and techniques for such predictive frameworks, a well-established rigorous method that can accurately predict neuromusculoskeletal dynamics of healthy and pathologic individuals is still lacking in the research community.
A nice application example that seems to be an emerging need for such musculoskeletal models is in the design of assistive devices for rehabilitation and augmentations purposes. The integrated human and device models would save time and cost of multiple prototyping steps in both the design and evaluation phases of such devices. Bio-fidelic predictive neuromusculoskeletal models could delineate crucial parameters of a design and elucidate the effect of a device conceptual design on the human’s kinematics and kinetics. Therefore, the design process will become human-centered in which a design optimization step includes all important factors, such as mechanical, electrical, material, as well as physiological.
This Research Topic calls for submissions that cover following subtopics:
? New methods and approaches in the field of musculoskeletal modeling and simulation, including motion prediction, neural control, central pattern generators, subject-robot co-simulations, subject-specific simulations
? Simulated effects of neurological conditions such as stroke, spinal cord injury, and cerebral palsy on the neural control and muscle properties.
? Design of human-centered assistive devices such as prostheses, orthoses, and hard and soft exoskeletons by investigating properties such as kinematic alignment, changes in subject movement pattern, strap and joint reaction forces, metabolic energy consumption, etc.
? Studies of human-robot interaction by taking advantage of musculoskeletal models.