Modeling Human Suboptimal Control: A Review.
EMG informed
feedback control
muscle control
optimization methods
stochastic approach
Journal
Journal of applied biomechanics
ISSN: 1543-2688
Titre abrégé: J Appl Biomech
Pays: United States
ID NLM: 9315240
Informations de publication
Date de publication:
01 Oct 2023
01 Oct 2023
Historique:
received:
16
01
2023
revised:
03
07
2023
accepted:
03
07
2023
pubmed:
17
8
2023
medline:
17
8
2023
entrez:
16
8
2023
Statut:
epublish
Résumé
This review paper provides an overview of the approaches to model neuromuscular control, focusing on methods to identify nonoptimal control strategies typical of populations with neuromuscular disorders or children. Where possible, the authors tightened the description of the methods to the mechanisms behind the underlying biomechanical and physiological rationale. They start by describing the first and most simplified approach, the reductionist approach, which splits the role of the nervous and musculoskeletal systems. Static optimization and dynamic optimization methods and electromyography-based approaches are summarized to highlight their limitations and understand (the need for) their developments over time. Then, the authors look at the more recent stochastic approach, introduced to explore the space of plausible neural solutions, thus implementing the uncontrolled manifold theory, according to which the central nervous system only controls specific motions and tasks to limit energy consumption while allowing for some degree of adaptability to perturbations. Finally, they explore the literature covering the explicit modeling of the coupling between the nervous system (acting as controller) and the musculoskeletal system (the actuator), which may be employed to overcome the split characterizing the reductionist approach.
Identifiants
pubmed: 37586711
doi: 10.1123/jab.2023-0015
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM