Muscle synergies in neuroscience and robotics: from input-space to task-space perspectives

In this paper we review the works related to muscle synergies that have been carried-out in neuroscience and control engineering. In particular, we refer to the hypothesis that the central nervous system (CNS) generates desired muscle contractions by combining a small number of predefined modules, called muscle synergies. We provide an overview of the methods that have been employed to test the validity of this scheme, and we show how the concept of muscle synergy has been generalized for the control of artificial agents. The comparison between these two lines of research, in particular their different goals and approaches, is instrumental to explain the computational implications of the hypothesized modular organization. Moreover, it clarifies the importance of assessing the functional role of muscle synergies: although these basic modules are defined at the level of muscle activations (input-space), they should result in the effective accomplishment of the desired task. This requirement is not always explicitly considered in experimental neuroscience, as muscle synergies are often estimated solely by analyzing recorded muscle activities. We suggest that synergy extraction methods should explicitly take into account task execution variables, thus moving from a perspective purely based on input-space to one grounded on task-space as well

Biomechanics

Biomechanics is a vast discipline within the field of Biomedical Engineering. It explores the underlying mechanics of how biological and physiological systems move. It encompasses important clinical applications to address questions related to medicine using engineering mechanics principles. Biomechanics includes interdisciplinary concepts from engineers, physicians, therapists, biologists, physicists, and mathematicians. Through their collaborative efforts, biomechanics research is ever changing and expanding, explaining new mechanisms and principles for dynamic human systems. Biomechanics is used to describe how the human body moves, walks, and breathes, in addition to how it responds to injury and rehabilitation. Advanced biomechanical modeling methods, such as inverse dynamics, finite element analysis, and musculoskeletal modeling are used to simulate and investigate human situations in regard to movement and injury. Biomechanical technologies are progressing to answer contemporary medical questions. The future of biomechanics is dependent on interdisciplinary research efforts and the education of tomorrow’s scientists

On the Origin of Frictional Adhesion in Geckos: Small Morphological Changes Lead to a Major Biomechanical Transition in the Genus \u3cem\u3eGonatodes\u3c/em\u3e

The evolutionary history of vertebrate locomotion is punctuated by innovations that have permitted expansion into novel ecological niches. Frictional adhesion of geckos is an innovation renowned for enabling locomotion on vertical and inverted smooth surfaces. Much is known about the microstructure and function of the fully-expressed gekkotan adhesive apparatus, although how it originated is poorly understood. Therefore, identifying species that exhibit the earliest stages of expression of frictional adhesion will provide significant insights into the evolution of this trait. Our previous investigation of digital proportions, shape, scalation, skeletal form, and subdigital epidermal micro-ornamentation in the genus Gonatodes led us to hypothesize that Gonatodes humeralisexpresses incipient frictional adhesion. To test this, we first conducted a phylogenetic analysis of Gonatodes and related sphaerodactyl genera to clarify the historical context of the evolution of frictional adhesive capability in the genus. We then measured the ability of G. humeralis and its close relatives to generate frictional adhesive force, examined their locomotor capabilities on low-friction surfaces, and observed animals in their natural habitat. After accounting for body mass and phylogenetic relationships, we found that G. humeralis generates frictional adhesive force essentially equivalent to that of Anolis, and can scale vertical smooth surfaces. Gonatodes vittatus, a species that lacks elaborated epidermal setae, generates negligible frictional adhesive force and can only ascend smooth inclined surfaces with a pitch of ≤ 40°. We conclude that the ostensibly padless G. humeralis, with feet lacking the musculoskeletal, tendinous, and vascular modifications typical of pad-bearing geckos, nevertheless can employ frictional adhesive contact to assist locomotion. As in Anolis, the release of frictional adhesive contact occurs when the foot is plantar flexed after the heel has lifted from the surface. Our findings indicate that the origin of frictional adhesion was likely gradual but that, ultimately, this led to major shifts in ecology and function

Adaptive, fast walking in a biped robot under neuronal control and learning

Human walking is a dynamic, partly self-stabilizing process relying on the interaction of the biomechanical design with its neuronal control. The coordination of this process is a very difficult problem, and it has been suggested that it involves a hierarchy of levels, where the lower ones, e.g., interactions between muscles and the spinal cord, are largely autonomous, and where higher level control (e.g., cortical) arises only pointwise, as needed. This requires an architecture of several nested, sensori–motor loops where the walking process provides feedback signals to the walker's sensory systems, which can be used to coordinate its movements. To complicate the situation, at a maximal walking speed of more than four leg-lengths per second, the cycle period available to coordinate all these loops is rather short. In this study we present a planar biped robot, which uses the design principle of nested loops to combine the self-stabilizing properties of its biomechanical design with several levels of neuronal control. Specifically, we show how to adapt control by including online learning mechanisms based on simulated synaptic plasticity. This robot can walk with a high speed (> 3.0 leg length/s), self-adapting to minor disturbances, and reacting in a robust way to abruptly induced gait changes. At the same time, it can learn walking on different terrains, requiring only few learning experiences. This study shows that the tight coupling of physical with neuronal control, guided by sensory feedback from the walking pattern itself, combined with synaptic learning may be a way forward to better understand and solve coordination problems in other complex motor tasks

Computationally efficient modeling of proprioceptive signals in the upper limb for prostheses: a simulation study.

Accurate models of proprioceptive neural patterns could one day play an important role in the creation of an intuitive proprioceptive neural prosthesis for amputees. This paper looks at combining efficient implementations of biomechanical and proprioceptor models in order to generate signals that mimic human muscular proprioceptive patterns for future experimental work in prosthesis feedback. A neuro-musculoskeletal model of the upper limb with 7 degrees of freedom and 17 muscles is presented and generates real time estimates of muscle spindle and Golgi Tendon Organ neural firing patterns. Unlike previous neuro-musculoskeletal models, muscle activation and excitation levels are unknowns in this application and an inverse dynamics tool (static optimisation) is integrated to estimate these variables. A proprioceptive prosthesis will need to be portable and this is incompatible with the computationally demanding nature of standard biomechanical and proprioceptor modelling. This paper uses and proposes a number of approximations and optimisations to make real time operation on portable hardware feasible. Finally technical obstacles to mimicking natural feedback for an intuitive proprioceptive prosthesis, as well as issues and limitations with existing models, are identified and discussed

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions

A solution strategy to include the opening of the opercular slits in moving-mesh CFD models of suction feeding

The gill cover of fish and pre-metamorphic salamanders has a key role in suction feeding by acting as a one-way valve. It initially closes to avoid an inflow of water through the gill slits, after which it opens to allow outflow of the water that was sucked through the mouth into the expanded buccopharyngeal cavity. However, due to the inability of analytical models (relying on the continuity principle) to calculate a fluid flow through a shape-and-size-changing cavity with two openings, stringent boundary conditions had to be used in previously developed mathematical models after the moment of valve opening. By solving additionally for momentum conservation, computational fluid dynamics (CFD) has the capacity to dynamically simulate these flows, but this technique also faces complications to model a transition from closed to open valves. Here, I present a relatively simple solution strategy to incorporate valve opening, exemplified in an axisymmetrical model of a suction-feeding sunfish in ANSYS Fluent software. By controlling viscosity of a separately defined fluid entity at the opercular cavity region, early inflow can be blocked (high viscosity assigned) and later outflow can be allowed (changing viscosity to that of water). Finally, by analysing the CFD solution obtained for the sunfish model, a few new insights in the biomechanics of suction feeding will be discussed