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      Investigation of neural and biomechanical impairments leading to pathological toe and heel gaits using neuromusculoskeletal modelling

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          Abstract

          Abstract

          This study investigates the pathological toe and heel gaits seen in human locomotion using neuromusculoskeletal modelling and simulation. In particular, it aims to investigate potential cause–effect relationships between biomechanical or neural impairments and pathological gaits. Toe and heel gaits are commonly present in spinal cord injury, stroke and cerebral palsy. Toe walking is mainly attributed to spasticity and contracture at plantar flexor muscles, whereas heel walking can be attributed to muscle weakness of biomechanical or neural origin. To investigate the effect of these impairments on gait, this study focuses on the soleus and gastrocnemius muscles as they contribute to ankle plantarflexion. We built a reflex circuit model based on previous work by Geyer and Herr with additional pathways affecting the plantar flexor muscles. The SCONE software, which provides optimisation tools for 2D neuromechanical simulation of human locomotion, is used to optimise the corresponding reflex parameters and simulate healthy gait. We then modelled various bilateral plantar flexor biomechanical and neural impairments, and individually introduced them in the healthy model. We characterised the resulting simulated gaits as pathological or not by comparing ankle kinematics and ankle moment with the healthy optimised gait based on metrics used in clinical studies. Our simulations suggest that toe walking can be generated by hyperreflexia, whereas muscle and neural weaknesses partially induce heel gait. Thus, this ‘what if’ approach is deemed of great interest as it allows investigation of the effect of various impairments on gait and suggests an important contribution of active reflex mechanisms to pathological toe gait.

          Key points

          • Pathological toe and heel gaits are commonly present in various conditions such as spinal cord injury, stroke and cerebral palsy.

          • These conditions present various neural and biomechanical impairments, but the cause–effect relationships between these impairments and pathological gaits are difficult to establish clinically.

          • Based on neuromechanical simulation, this study focuses on the plantar flexor muscles and builds a new reflex circuit controller to model and evaluate the potential effect of both neural and biomechanical impairments on gait.

          • Our results suggest an important contribution of active reflex mechanisms to pathological toe gait.

          • This ‘what if’ based on neuromechanical modelling is thus deemed of great interest to target potential causes of pathological gait.

          Abstract

          Abstract figure legend Various biomechanical and neural impairments are individually modelled at the level of the plantar flexor muscles in a musculoskeletal model and a complex reflex circuit‐based gait controller. For instance, as shown on the left, the plantar flexor spindle reflex gain (KS) is increased to mimic hyperreflexia. The gait controller is then optimised for each of the impaired conditions and the resulting gaits are characterised as pathological based on ankle kinematics and ankle moment metrics used in clinical studies. Thus, this ‘what if’ approach allows the investigation of the effect of various impairments on gait presented in the table on the right.

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          Most cited references78

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          Decoding the organization of spinal circuits that control locomotion.

          Ole Kiehn (2016)
          Unravelling the functional operation of neuronal networks and linking cellular activity to specific behavioural outcomes are among the biggest challenges in neuroscience. In this broad field of research, substantial progress has been made in studies of the spinal networks that control locomotion. Through united efforts using electrophysiological and molecular genetic network approaches and behavioural studies in phylogenetically diverse experimental models, the organization of locomotor networks has begun to be decoded. The emergent themes from this research are that the locomotor networks have a modular organization with distinct transmitter and molecular codes and that their organization is reconfigured with changes to the speed of locomotion or changes in gait.
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            Dynamic sensorimotor interactions in locomotion.

            Locomotion results from intricate dynamic interactions between a central program and feedback mechanisms. The central program relies fundamentally on a genetically determined spinal circuitry (central pattern generator) capable of generating the basic locomotor pattern and on various descending pathways that can trigger, stop, and steer locomotion. The feedback originates from muscles and skin afferents as well as from special senses (vision, audition, vestibular) and dynamically adapts the locomotor pattern to the requirements of the environment. The dynamic interactions are ensured by modulating transmission in locomotor pathways in a state- and phase-dependent manner. For instance, proprioceptive inputs from extensors can, during stance, adjust the timing and amplitude of muscle activities of the limbs to the speed of locomotion but be silenced during the opposite phase of the cycle. Similarly, skin afferents participate predominantly in the correction of limb and foot placement during stance on uneven terrain, but skin stimuli can evoke different types of responses depending on when they occur within the step cycle. Similarly, stimulation of descending pathways may affect the locomotor pattern in only certain phases of the step cycle. Section ii reviews dynamic sensorimotor interactions mainly through spinal pathways. Section iii describes how similar sensory inputs from the spinal or supraspinal levels can modify locomotion through descending pathways. The sensorimotor interactions occur obviously at several levels of the nervous system. Section iv summarizes presynaptic, interneuronal, and motoneuronal mechanisms that are common at these various levels. Together these mechanisms contribute to the continuous dynamic adjustment of sensorimotor interactions, ensuring that the central program and feedback mechanisms are congruous during locomotion.
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              An interactive graphics-based model of the lower extremity to study orthopaedic surgical procedures.

              We have developed a model of the human lower extremity to study how surgical changes in musculoskeletal geometry and musculotendon parameters affect muscle force and its moment about the joints. The lines of action of 43 musculotendon actuators were defined based on their anatomical relationships to three-dimensional bone surface representations. A model for each actuator was formulated to compute its isometric force-length relation. The kinematics of the lower extremity were defined by modeling the hip, knee, ankle, subtalar, and metatarsophalangeal joints. Thus, the force and joint moment that each musculotendon actuator develops can be computed for any body position. The joint moments calculated with the model compare well with experimentally measured isometric joint moments. We developed a graphical interface to the model that allows the user to visualize the musculoskeletal geometry and to manipulate the model parameters to study the biomechanical consequences of orthopaedic surgical procedures. For example, tendon transfer and lengthening procedures can be simulated by adjusting the model parameters according to various surgical techniques. Results of the simulated surgeries can be analyzed quickly in terms of postsurgery muscle forces and other biomechanical variables. Just as interactive graphics have enhanced engineering design and analysis, we have found that graphics-based musculoskeletal models are effective tools for designing and analyzing surgical procedures.
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                Author and article information

                Contributors
                alice.bruel@epfl.ch
                Journal
                J Physiol
                J Physiol
                10.1111/(ISSN)1469-7793
                TJP
                jphysiol
                The Journal of Physiology
                John Wiley and Sons Inc. (Hoboken )
                0022-3751
                1469-7793
                06 May 2022
                01 June 2022
                06 May 2022
                : 600
                : 11 ( doiID: 10.1113/tjp.v600.11 )
                : 2691-2712
                Affiliations
                [ 1 ] BioRobotics Laboratory EPFL Lausanne Switzerland
                [ 2 ] Kinesiology Laboratory – HUG/UNIGE Switzerland
                [ 3 ] Upcourtine EPFL USA
                Author notes
                [*] [* ] Corresponding author Alice Bruel: BioRobotics Laboratory, EPFL, 1015 Lausanne, Switzerland. Email: alice.bruel@ 123456epfl.ch

                Author information
                https://orcid.org/0000-0002-5467-2852
                Article
                TJP15057
                10.1113/JP282609
                9401908
                35442531
                9be83365-fd4e-48ad-a9ba-dd4a0291fc8e
                © 2022 The Authors. The Journal of Physiology published by John Wiley & Sons Ltd on behalf of The Physiological Society.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 19 November 2021
                : 11 April 2022
                Page count
                Figures: 15, Tables: 3, Pages: 22, Words: 13137
                Funding
                Funded by: Swiss National Science Foundation , doi 10.13039/501100001711;
                Award ID: 177179
                Categories
                Research Article
                Computational Physiology and Modelling
                Custom metadata
                2.0
                1 June 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.7 mode:remove_FC converted:24.08.2022

                Human biology
                heel walking,locomotion,neuromusculoskeletal modelling,pathological gait,spasticity,toe walking,weakness

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