1
|
Yang C, Yang Y, Xu Y, Zhang Z, Lake M, Fu W. Whole leg compression garments influence lower limb kinematics and associated muscle synergies during running. Front Bioeng Biotechnol 2024; 12:1310464. [PMID: 38444649 PMCID: PMC10912955 DOI: 10.3389/fbioe.2024.1310464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Accepted: 01/19/2024] [Indexed: 03/07/2024] Open
Abstract
The utilization of compression garments (CGs) has demonstrated the potential to improve athletic performance; however, the specific mechanisms underlying this enhancement remain a subject of further investigation. This study aimed to examine the impact of CGs on running mechanics and muscle synergies from a neuromuscular control perspective. Twelve adult males ran on a treadmill at 12 km/h, while data pertaining to lower limb kinematics, kinetics, and electromyography were collected under two clothing conditions: whole leg compression garments and control. The Non-negative matrix factorization algorithm was employed to extract muscle synergy during running, subsequently followed by cluster analysis and correlation analysis. The findings revealed that the CGs increased knee extension and reduced hip flexion at foot strike compared with the control condition. Moreover, CGs were found to enhance stance-phase peak knee extension, while diminishing hip flexion and maximal hip extension during the stance-phase, and the ankle kinematics remained unaltered. We extracted and classified six synergies (SYN1-6) during running and found that only five SYNs were observed after wearing CGs. CGs altered the structure of the synergies and changed muscle activation weights and durations. The current study is the first to apply muscle synergy to discuss the effect of CGs on running biomechanics. Our findings provide neuromuscular evidence for the idea of previous studies that CGs alter the coordination of muscle groups, thereby affecting kinematic characteristics during running.
Collapse
Affiliation(s)
- Chenhao Yang
- School of Exercise and Health, Shanghai University of Sport, Shanghai, China
- Key Laboratory of Exercise and Health Sciences of Ministry of Education, Shanghai University of Sport, Shanghai, China
| | - Yang Yang
- School of Exercise and Health, Shanghai University of Sport, Shanghai, China
- Key Laboratory of Exercise and Health Sciences of Ministry of Education, Shanghai University of Sport, Shanghai, China
| | - Yongxin Xu
- School of Exercise and Health, Shanghai University of Sport, Shanghai, China
- Key Laboratory of Exercise and Health Sciences of Ministry of Education, Shanghai University of Sport, Shanghai, China
| | - Zhenyuan Zhang
- Research Institute for Sport and Exercise Science (RISES), Liverpool John Moores University, Liverpool, United Kingdom
| | - Mark Lake
- Research Institute for Sport and Exercise Science (RISES), Liverpool John Moores University, Liverpool, United Kingdom
| | - Weijie Fu
- School of Exercise and Health, Shanghai University of Sport, Shanghai, China
- Key Laboratory of Exercise and Health Sciences of Ministry of Education, Shanghai University of Sport, Shanghai, China
| |
Collapse
|
2
|
Cashaback JGA, Allen JL, Chou AHY, Lin DJ, Price MA, Secerovic NK, Song S, Zhang H, Miller HL. NSF DARE-transforming modeling in neurorehabilitation: a patient-in-the-loop framework. J Neuroeng Rehabil 2024; 21:23. [PMID: 38347597 PMCID: PMC10863253 DOI: 10.1186/s12984-024-01318-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 01/25/2024] [Indexed: 02/15/2024] Open
Abstract
In 2023, the National Science Foundation (NSF) and the National Institute of Health (NIH) brought together engineers, scientists, and clinicians by sponsoring a conference on computational modelling in neurorehabiilitation. To facilitate multidisciplinary collaborations and improve patient care, in this perspective piece we identify where and how computational modelling can support neurorehabilitation. To address the where, we developed a patient-in-the-loop framework that uses multiple and/or continual measurements to update diagnostic and treatment model parameters, treatment type, and treatment prescription, with the goal of maximizing clinically-relevant functional outcomes. This patient-in-the-loop framework has several key features: (i) it includes diagnostic and treatment models, (ii) it is clinically-grounded with the International Classification of Functioning, Disability and Health (ICF) and patient involvement, (iii) it uses multiple or continual data measurements over time, and (iv) it is applicable to a range of neurological and neurodevelopmental conditions. To address the how, we identify state-of-the-art and highlight promising avenues of future research across the realms of sensorimotor adaptation, neuroplasticity, musculoskeletal, and sensory & pain computational modelling. We also discuss both the importance of and how to perform model validation, as well as challenges to overcome when implementing computational models within a clinical setting. The patient-in-the-loop approach offers a unifying framework to guide multidisciplinary collaboration between computational and clinical stakeholders in the field of neurorehabilitation.
Collapse
Affiliation(s)
- Joshua G A Cashaback
- Biomedical Engineering, Mechanical Engineering, Kinesiology and Applied Physiology, Biome chanics and Movement Science Program, Interdisciplinary Neuroscience Graduate Program, University of Delaware, 540 S College Ave, Newark, DE, 19711, USA.
| | - Jessica L Allen
- Department of Mechanical Engineering, University of Florida, Gainesville, USA
| | | | - David J Lin
- Division of Neurocritical Care and Stroke Service, Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, USA
- Department of Veterans Affairs, Center for Neurorestoration and Neurotechnology, Rehabilitation Research and Development Service, Providence, USA
| | - Mark A Price
- Department of Mechanical and Industrial Engineering, Department of Kinesiology, University of Massachusetts Amherst, Amherst, USA
| | - Natalija K Secerovic
- School of Electrical Engineering, The Mihajlo Pupin Institute, University of Belgrade, Belgrade, Serbia
- Laboratory for Neuroengineering, Institute for Robotics and Intelligent Systems ETH Zürich, Zurich, Switzerland
| | - Seungmoon Song
- Mechanical and Industrial Engineering, Northeastern University, Boston, USA
| | - Haohan Zhang
- Department of Mechanical Engineering, University of Utah, Salt Lake City, USA
| | - Haylie L Miller
- School of Kinesiology, University of Michigan, 830 N University Ave, Ann Arbor, MI, 48109, USA.
| |
Collapse
|
3
|
Koo YJ, Hwangbo J, Koo S. Higher coactivations of lower limb muscles increase stability during walking on slippery ground in forward dynamics musculoskeletal simulation. Sci Rep 2023; 13:22808. [PMID: 38129534 PMCID: PMC10739792 DOI: 10.1038/s41598-023-49865-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 12/12/2023] [Indexed: 12/23/2023] Open
Abstract
The energy efficiency theory of human bipedal locomotion has been widely accepted as a neuro-musculoskeletal control method. However, coactivation of agonist and antagonist muscles in the lower limb has been observed during various limb movements, including walking. The emergence of this coactivation cannot be explained solely by the energy efficiency theory and remains a subject of debate. To shed light on this, we investigated the role of muscle coactivations in walking stability using a forward dynamics musculoskeletal simulation combined with neural-network-based gait controllers. Our study revealed that a gait controller with minimal muscle activations had a high probability of falls under challenging gait conditions such as slippery ground and uneven terrain. Lower limb muscle coactivations emerged in the process of gait controller training on slippery ground. Controllers with physiological coactivation levels demonstrated a significantly reduced probability of falls. Our results suggest that achieving stable walking requires muscle coactivations beyond the minimal level of muscle energy. This study implies that coactivations likely emerge to maintain gait stability under challenging conditions, and both coactivation and energy optimization of lower limb muscles should be considered when exploring the foundational control mechanisms of human walking.
Collapse
Affiliation(s)
- Young-Jun Koo
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea
| | - Jemin Hwangbo
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea
| | - Seungbum Koo
- Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Republic of Korea.
| |
Collapse
|
4
|
Di Russo A, Stanev D, Sabnis A, Danner SM, Ausborn J, Armand S, Ijspeert A. Investigating the roles of reflexes and central pattern generators in the control and modulation of human locomotion using a physiologically plausible neuromechanical model. J Neural Eng 2023; 20:066006. [PMID: 37757805 DOI: 10.1088/1741-2552/acfdcc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 09/27/2023] [Indexed: 09/29/2023]
Abstract
Objective.Studying the neural components regulating movement in human locomotion is obstructed by the inability to perform invasive experimental recording in the human neural circuits. Neuromechanical simulations can provide insights by modeling the locomotor circuits. Past neuromechanical models proposed control of locomotion either driven by central pattern generators (CPGs) with simple sensory commands or by a purely reflex-based network regulated by state-machine mechanisms, which activate and deactivate reflexes depending on the detected gait cycle phases. However, the physiological interpretation of these state machines remains unclear. Here, we present a physiologically plausible model to investigate spinal control and modulation of human locomotion.Approach.We propose a bio-inspired controller composed of two coupled CPGs that produce the rhythm and pattern, and a reflex-based network simulating low-level reflex pathways and Renshaw cells. This reflex network is based on leaky-integration neurons, and the whole system does not rely on changing reflex gains according to the gait cycle state. The musculoskeletal model is composed of a skeletal structure and nine muscles per leg generating movement in sagittal plane.Main results.Optimizing the open parameters for effort minimization and stability, human kinematics and muscle activation naturally emerged. Furthermore, when CPGs were not activated, periodic motion could not be achieved through optimization, suggesting the necessity of this component to generate rhythmic behavior without a state machine mechanism regulating reflex activation. The controller could reproduce ranges of speeds from 0.3 to 1.9 m s-1. The results showed that the net influence of feedback on motoneurons (MNs) during perturbed locomotion is predominantly inhibitory and that the CPGs provide the timing of MNs' activation by exciting or inhibiting muscles in specific gait phases.Significance.The proposed bio-inspired controller could contribute to our understanding of locomotor circuits of the intact spinal cord and could be used to study neuromotor disorders.
Collapse
Affiliation(s)
| | | | | | - Simon M Danner
- Department of Neurobiology and Anatomy, College of Medicine, Drexel University, Philadelphia, PA, United States of America
| | - Jessica Ausborn
- Department of Neurobiology and Anatomy, College of Medicine, Drexel University, Philadelphia, PA, United States of America
| | - Stéphane Armand
- Kinesiology Laboratory, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | | |
Collapse
|
5
|
Damonte F, Durandau G, Gonzalez-Vargas J, Van Der Kooij H, Sartori M. Synergy-Driven Musculoskeletal Modeling to Estimate Muscle Excitations and Joint Moments at Different Walking Speeds in Individuals with Transtibial Amputation. IEEE Int Conf Rehabil Robot 2023; 2023:1-6. [PMID: 37941287 DOI: 10.1109/icorr58425.2023.10304814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
The main requirement for an amputee is to regain the function of the lost limb. In order to fully benefit from powered prosthetic legs, the user must rely on the dynamic control of the device. Progress in high-level control for powered prosthetic legs is currently challenged by the inability of current control schemes to generalize to large repertoires of movements as well as adapting to external mechanical demands. This ultimately leads the user to adopt compensatory movements, lack of comfort, higher energy requirements during walking and standing. This study uses a feedforward model of muscle activation and force generation that applies mathematical formulations of muscle synergies to generate synthetic activation profiles underlying walking across different speeds. Estimated activation profiles are used to drive forward subject-specific numerical models of the lower extremity musculoskeletal system. The model was validated on one individual with uni-lateral transtibial amputation and its predictions were compared to experimental torques from inverse dynamic calculations. Results showed that a generic muscle synergy driven personalized musculoskeletal model can fit the ankle torques of the intact limb of a person with transtibial amputation (RMSD = 0.1329±0.02). The estimated moments might be suitable as the control signal to drive powered prostheses to ultimately improve physical interaction between the user and a powered prostheses during dynamic motor tasks.
Collapse
|
6
|
Ijspeert AJ, Daley MA. Integration of feedforward and feedback control in the neuromechanics of vertebrate locomotion: a review of experimental, simulation and robotic studies. J Exp Biol 2023; 226:jeb245784. [PMID: 37565347 DOI: 10.1242/jeb.245784] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/12/2023]
Abstract
Animal locomotion is the result of complex and multi-layered interactions between the nervous system, the musculo-skeletal system and the environment. Decoding the underlying mechanisms requires an integrative approach. Comparative experimental biology has allowed researchers to study the underlying components and some of their interactions across diverse animals. These studies have shown that locomotor neural circuits are distributed in the spinal cord, the midbrain and higher brain regions in vertebrates. The spinal cord plays a key role in locomotor control because it contains central pattern generators (CPGs) - systems of coupled neuronal oscillators that provide coordinated rhythmic control of muscle activation that can be viewed as feedforward controllers - and multiple reflex loops that provide feedback mechanisms. These circuits are activated and modulated by descending pathways from the brain. The relative contributions of CPGs, feedback loops and descending modulation, and how these vary between species and locomotor conditions, remain poorly understood. Robots and neuromechanical simulations can complement experimental approaches by testing specific hypotheses and performing what-if scenarios. This Review will give an overview of key knowledge gained from comparative vertebrate experiments, and insights obtained from neuromechanical simulations and robotic approaches. We suggest that the roles of CPGs, feedback loops and descending modulation vary among animals depending on body size, intrinsic mechanical stability, time required to reach locomotor maturity and speed effects. We also hypothesize that distal joints rely more on feedback control compared with proximal joints. Finally, we highlight important opportunities to address fundamental biological questions through continued collaboration between experimentalists and engineers.
Collapse
Affiliation(s)
- Auke J Ijspeert
- BioRobotics Laboratory, EPFL - Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Monica A Daley
- Department of Ecology and Evolutionary Biology, University of California, Irvine, Irvine, CA 92697, USA
| |
Collapse
|
7
|
Ichimura D, Hobara H, Hisano G, Maruyama T, Tada M. Acquisition of bipedal locomotion in a neuromusculoskeletal model with unilateral transtibial amputation. Front Bioeng Biotechnol 2023; 11:1130353. [PMID: 36937747 PMCID: PMC10014613 DOI: 10.3389/fbioe.2023.1130353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Accepted: 02/20/2023] [Indexed: 03/05/2023] Open
Abstract
Adaptive locomotion is an essential behavior for animals to survive. The central pattern generator in the spinal cord is responsible for the basic rhythm of locomotion through sensory feedback coordination, resulting in energy-efficient locomotor patterns. Individuals with symmetrical body proportions exhibit an energy-efficient symmetrical gait on flat ground. In contrast, individuals with lower limb amputation, who have morphologically asymmetrical body proportions, exhibit asymmetrical gait patterns. However, it remains unclear how the nervous system adjusts the control of the lower limbs. Thus, in this study, we investigated how individuals with unilateral transtibial amputation control their left and right lower limbs during locomotion using a two-dimensional neuromusculoskeletal model. The model included a musculoskeletal model with 7 segments and 18 muscles, as well as a neural model with a central pattern generator and sensory feedback systems. Specifically, we examined whether individuals with unilateral transtibial amputation acquire prosthetic gait through a symmetric or asymmetric feedback control for the left and right lower limbs. After acquiring locomotion, the metabolic costs of transport and the symmetry of the spatiotemporal gait factors were evaluated. Regarding the metabolic costs of transportation, the symmetric control model showed values approximately twice those of the asymmetric control model, whereas both scenarios showed asymmetry of spatiotemporal gait patterns. Our results suggest that individuals with unilateral transtibial amputation can reacquire locomotion by modifying sensory feedback parameters. In particular, the model reacquired reasonable locomotion for activities of daily living by re-searching asymmetric feedback parameters for each lower limb. These results could provide insight into effective gait assessment and rehabilitation methods to reacquire locomotion in individuals with unilateral transtibial amputation.
Collapse
Affiliation(s)
- Daisuke Ichimura
- Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan
- *Correspondence: Daisuke Ichimura,
| | - Hiroaki Hobara
- Faculty of Advanced Engineering, Tokyo University of Science, Tokyo, Japan
| | - Genki Hisano
- Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan
- Department of Systems and Control Engineering, Tokyo Institute of Technology, Tokyo, Japan
- Research Fellow of Japan Society for the Promotion of Science (JSPS), Tokyo, Japan
| | - Tsubasa Maruyama
- Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan
| | - Mitsunori Tada
- Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan
| |
Collapse
|
8
|
Ramadan R, Meischein F, Reimann H. High-level motor planning allows flexible walking at different gait patterns in a neuromechanical model. Front Bioeng Biotechnol 2022; 10:959357. [PMID: 36568295 PMCID: PMC9772469 DOI: 10.3389/fbioe.2022.959357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 11/04/2022] [Indexed: 12/13/2022] Open
Abstract
Humans can freely adopt gait parameters like walking speed, step length, or cadence on the fly when walking. Planned movement that can be updated online to account for changes in the environment rather than having to rely on habitual, reflexive control that is adapted over long timescales. Here we present a neuromechanical model that accounts for this flexibility by combining movement goals and motor plans on a kinematic task level with low-level spinal feedback loops. We show that the model can walk at a wide range of different gait patterns by choosing a small number of high-level control parameters representing a movement goal. A larger number of parameters governing the low-level reflex loops in the spinal cord, on the other hand, remain fixed. We also show that the model can generalize the learned behavior by recombining the high-level control parameters and walk with gait patterns that it had not encountered before. Furthermore, the model can transition between different gaits without the loss of balance by switching to a new set of control parameters in real time.
Collapse
Affiliation(s)
- Rachid Ramadan
- Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany,*Correspondence: Rachid Ramadan,
| | - Fabian Meischein
- Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany
| | - Hendrik Reimann
- Department of Kinesiology and Applied Physiology, University of Delaware, Newark, DE, United States
| |
Collapse
|
9
|
Di Fede E, Grazioli P, Lettieri A, Parodi C, Castiglioni S, Taci E, Colombo EA, Ancona S, Priori A, Gervasini C, Massa V. Epigenetic disorders: Lessons from the animals–animal models in chromatinopathies. Front Cell Dev Biol 2022; 10:979512. [PMID: 36225316 PMCID: PMC9548571 DOI: 10.3389/fcell.2022.979512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 09/05/2022] [Indexed: 11/13/2022] Open
Abstract
Chromatinopathies are defined as genetic disorders caused by mutations in genes coding for protein involved in the chromatin state balance. So far 82 human conditions have been described belonging to this group of congenital disorders, sharing some molecular features and clinical signs. For almost all of these conditions, no specific treatment is available. For better understanding the molecular cascade caused by chromatin imbalance and for envisaging possible therapeutic strategies it is fundamental to combine clinical and basic research studies. To this end, animal modelling systems represent an invaluable tool to study chromatinopathies. In this review, we focused on available data in the literature of animal models mimicking the human genetic conditions. Importantly, affected organs and abnormalities are shared in the different animal models and most of these abnormalities are reported as clinical manifestation, underlying the parallelism between clinics and translational research.
Collapse
Affiliation(s)
- Elisabetta Di Fede
- Department of Health Sciences, Università Degli Studi di Milano, Milan, Italy
| | - Paolo Grazioli
- Department of Health Sciences, Università Degli Studi di Milano, Milan, Italy
| | - Antonella Lettieri
- Department of Health Sciences, Università Degli Studi di Milano, Milan, Italy
| | - Chiara Parodi
- Department of Health Sciences, Università Degli Studi di Milano, Milan, Italy
| | - Silvia Castiglioni
- Department of Health Sciences, Università Degli Studi di Milano, Milan, Italy
| | - Esi Taci
- Department of Health Sciences, Università Degli Studi di Milano, Milan, Italy
| | - Elisa Adele Colombo
- Department of Health Sciences, Università Degli Studi di Milano, Milan, Italy
| | - Silvia Ancona
- Department of Health Sciences, Università Degli Studi di Milano, Milan, Italy
| | - Alberto Priori
- Department of Health Sciences, Università Degli Studi di Milano, Milan, Italy
- “Aldo Ravelli” Center for Neurotechnology and Experimental Brain Therapeutics, Università Degli Studi di Milano, Milan, Italy
| | - Cristina Gervasini
- Department of Health Sciences, Università Degli Studi di Milano, Milan, Italy
- “Aldo Ravelli” Center for Neurotechnology and Experimental Brain Therapeutics, Università Degli Studi di Milano, Milan, Italy
| | - Valentina Massa
- Department of Health Sciences, Università Degli Studi di Milano, Milan, Italy
- “Aldo Ravelli” Center for Neurotechnology and Experimental Brain Therapeutics, Università Degli Studi di Milano, Milan, Italy
- *Correspondence: Valentina Massa,
| |
Collapse
|
10
|
Almani MN, Saxena S. Recurrent neural networks controlling musculoskeletal models predict motor cortex activity during novel limb movements. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:3350-3356. [PMID: 36086532 DOI: 10.1109/embc48229.2022.9871085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Goal-driven networks trained to perform a task analogous to that performed by biological neural populations are being increasingly utilized as insightful computational models of motor control. The resulting dynamics of the trained networks are then analyzed to uncover the neural strategies employed by the motor cortex to produce movements. However, these networks do not take into account the role of sensory feedback in producing movement, nor do they consider the complex biophysical underpinnings of the underlying musculoskeletal system. Moreover, these models can not be used in context of predictive neuromechanical simulations for hypothesis generation and prediction of neural strategies during novel movements. In this research, we adapt state-of-the-art deep reinforcement learning (DRL) algorithms to train a controller to drive a developed anatomically accurate monkey arm model to track experimentally recorded kinematics. We validate that the trained controller mimics biologically observed neural strategies to produce movement. The trained controller generalizes well to unobserved conditions as well as to perturbation analyses. The recorded firing rates of motor cortex neurons can be predicted from the controller activity with high accuracy even on unseen conditions. Finally, we validate that the trained controller outperforms existing goal-driven and representational models of motor cortex in single neuron decoding accuracy, thus showing the utility of the complex underpinnings of anatomically accurate models in shaping motor cortex neural activity during limb movements. The learned controller can be used for hypothesis generation and prediction of neural strategies during novel movements and unobserved conditions.
Collapse
|
11
|
Okamoto K, Obayashi I, Kokubu H, Senda K, Tsuchiya K, Aoi S. Contribution of Phase Resetting to Statistical Persistence in Stride Intervals: A Modeling Study. Front Neural Circuits 2022; 16:836121. [PMID: 35814485 PMCID: PMC9257880 DOI: 10.3389/fncir.2022.836121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 05/19/2022] [Indexed: 11/13/2022] Open
Abstract
Stride intervals in human walking fluctuate from one stride to the next, exhibiting statistical persistence. This statistical property is changed by aging, neural disorders, and experimental interventions. It has been hypothesized that the central nervous system is responsible for the statistical persistence. Human walking is a complex phenomenon generated through the dynamic interactions between the central nervous system and the biomechanical system. It has also been hypothesized that the statistical persistence emerges through the dynamic interactions during walking. In particular, a previous study integrated a biomechanical model composed of seven rigid links with a central pattern generator (CPG) model, which incorporated a phase resetting mechanism as sensory feedback as well as feedforward, trajectory tracking, and intermittent feedback controllers, and suggested that phase resetting contributes to the statistical persistence in stride intervals. However, the essential mechanisms remain largely unclear due to the complexity of the neuromechanical model. In this study, we reproduced the statistical persistence in stride intervals using a simplified neuromechanical model composed of a simple compass-type biomechanical model and a simple CPG model that incorporates only phase resetting and a feedforward controller. A lack of phase resetting induced a loss of statistical persistence, as observed for aging, neural disorders, and experimental interventions. These mechanisms were clarified based on the phase response characteristics of our model. These findings provide useful insight into the mechanisms responsible for the statistical persistence of stride intervals in human walking.
Collapse
Affiliation(s)
- Kota Okamoto
- Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Kyoto Daigaku-Katsura, Kyoto, Japan
| | - Ippei Obayashi
- Cyber-Physical Engineering Information Research Core (Cypher), Okayama University, Okayama, Japan
| | - Hiroshi Kokubu
- Department of Mathematics, Graduate School of Science, Kyoto University, Kyoto, Japan
| | - Kei Senda
- Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Kyoto Daigaku-Katsura, Kyoto, Japan
| | - Kazuo Tsuchiya
- Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Kyoto Daigaku-Katsura, Kyoto, Japan
| | - Shinya Aoi
- Department of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University, Osaka, Japan
- *Correspondence: Shinya Aoi
| |
Collapse
|
12
|
Bruel A, Ghorbel SB, Russo AD, Stanev D, Armand S, Courtine G, Ijspeert A. Investigation of neural and biomechanical impairments leading to pathological toe and heel gaits using neuromusculoskeletal modelling. J Physiol 2022; 600:2691-2712. [PMID: 35442531 PMCID: PMC9401908 DOI: 10.1113/jp282609] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 04/11/2022] [Indexed: 11/08/2022] Open
Abstract
KEY POINTS Pathological toe and heel gaits are commonly present in various conditions such as spinal cord injury, stroke or cerebral palsy. These conditions present various neural and biomechanical impairments and the cause-effect relationships between these impairments and pathological gaits are hard to establish clinically. Based on neuromechanical simulation, this study focuses on the plantarflexor 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 in pathological toe gait. This "what if" based on neuromechanical modelling is thus deemed of great interest to target potential pathological gait causes. ABSTRACT This study investigates the pathological toe and heel gaits in human locomotion using neuromusculoskeletal modelling and simulation. In particular, it aims at investigating potential cause-effect relationships between biomechanical or neural impairments and pathological gaits. Toe and heel gaits are commonly present in spinal cord injury, stroke or cerebral palsy. Toe walking is mainly attributed to spasticity and contracture at plantarflexor muscles, whereas heel walking can be attributed to muscle weakness from 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 on top of Geyer and Herr's work (2010) with additional pathways affecting the plantarflexor 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 plantarflexors 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 induce partially heel gait. Thus, this "what if" approach is deemed of great interest as it allows the investigation of the effect of various impairments on gait and suggests an important contribution of active reflex mechanisms in pathological toe gait. Abstract figure legend Various biomechanical and neural impairments are individually modelled at the level of the plantarflexor muscles in a musculoskeletal model and a complex reflex circuit-based gait controller. For instance, as shown on the left, the plantarflexors spindle reflex gain (KS) is increased to mimic hyperreflexia. The gait controller is then optimised for each of the impaired condition and the resulting gaits are characterised as pathological gait 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. This article is protected by copyright. All rights reserved.
Collapse
Affiliation(s)
- Alice Bruel
- BioRobotics laboratory, EPFL, Lausanne, 1015, Switzerland
| | | | | | - Dimitar Stanev
- BioRobotics laboratory, EPFL, Lausanne, 1015, Switzerland
| | | | | | - Auke Ijspeert
- BioRobotics laboratory, EPFL, Lausanne, 1015, Switzerland
| |
Collapse
|
13
|
Kamimura T, Sato K, Aoi S, Higurashi Y, Wada N, Tsuchiya K, Sano A, Matsuno F. Three Characteristics of Cheetah Galloping Improve Running Performance Through Spinal Movement: A Modeling Study. Front Bioeng Biotechnol 2022; 10:825638. [PMID: 35497345 PMCID: PMC9049215 DOI: 10.3389/fbioe.2022.825638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 03/18/2022] [Indexed: 11/13/2022] Open
Abstract
Cheetahs are the fastest land animal. Their galloping shows three characteristics: small vertical movement of their center of mass, small whole-body pitching movement, and large spine bending movement. We hypothesize that these characteristics lead to enhanced gait performance in cheetahs, including higher gait speed. In this study, we used a simple model with a spine joint and torsional spring, which emulate the body flexibility, to verify our hypothesis from a dynamic perspective. Specifically, we numerically searched periodic solutions and evaluated what extent each solution shows the three characteristics. We then evaluated the gait performance and found that the solutions with the characteristics achieve high performances. This result supports our hypothesis. Furthermore, we revealed the mechanism for the high performances through the dynamics of the spine movement. These findings extend the current understanding of the dynamic mechanisms underlying high-speed locomotion in cheetahs.
Collapse
Affiliation(s)
- Tomoya Kamimura
- Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Aichi, Japan
- *Correspondence: Tomoya Kamimura, ; Shinya Aoi,
| | - Kaho Sato
- Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Aichi, Japan
| | - Shinya Aoi
- Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Kyoto, Japan
- *Correspondence: Tomoya Kamimura, ; Shinya Aoi,
| | - Yasuo Higurashi
- Laboratory of System Physiology, Joint Faculty of Veterinary Medicine, Yamaguchi University, Yamaguchi, Japan
| | - Naomi Wada
- Laboratory of System Physiology, Joint Faculty of Veterinary Medicine, Yamaguchi University, Yamaguchi, Japan
| | - Kazuo Tsuchiya
- Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Kyoto, Japan
| | - Akihito Sano
- Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Aichi, Japan
| | - Fumitoshi Matsuno
- Department of Mechanical Engineering and Science, Graduate School of Engineering, Kyoto University, Kyoto, Japan
| |
Collapse
|
14
|
Continuous Estimation of Finger and Wrist Joint Angles Using a Muscle Synergy Based Musculoskeletal Model. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12083772] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Recently, many muscle synergy-based human motion prediction models and algorithms have been proposed. In this study, the muscle synergies extracted from electromyography (EMG) data were used to construct a musculoskeletal model (MSM) to predict the joint angles of the wrist, thumb, index finger, and middle finger. EMG signals were analyzed using independent component analysis to reduce signal noise and task-irrelevant artifacts. The weights of each independent component (IC) were converted into a heat map related to the motion pattern and compared with human anatomy to find a different number of ICs matching the motion pattern. Based on the properties of the MSM, non-negative matrix factorization was used to extract muscle synergies from selected ICs that represent the extensor and flexor muscle groups. The effects of these choices on the prediction accuracy was also evaluated. The performance of the model was evaluated using the correlation coefficient (CC) and normalized root-mean-square error (NRMSE). The proposed method has a higher prediction accuracy than those of traditional methods, with an average CC of 92.0% and an average NRMSE of 10.7%.
Collapse
|
15
|
Badri-Spröwitz A, Aghamaleki Sarvestani A, Sitti M, Daley MA. BirdBot achieves energy-efficient gait with minimal control using avian-inspired leg clutching. Sci Robot 2022; 7:eabg4055. [PMID: 35294220 DOI: 10.1126/scirobotics.abg4055] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Designers of legged robots are challenged with creating mechanisms that allow energy-efficient locomotion with robust and minimalistic control. Sources of high energy costs in legged robots include the rapid loading and high forces required to support the robot's mass during stance and the rapid cycling of the leg's state between stance and swing phases. Here, we demonstrate an avian-inspired robot leg design, BirdBot, that challenges the reliance on rapid feedback control for joint coordination and replaces active control with intrinsic, mechanical coupling, reminiscent of a self-engaging and disengaging clutch. A spring tendon network rapidly switches the leg's slack segments into a loadable state at touchdown, distributes load among joints, enables rapid disengagement at toe-off through elastically stored energy, and coordinates swing leg flexion. A bistable joint mediates the spring tendon network's disengagement at the end of stance, powered by stance phase leg angle progression. We show reduced knee-flexing torque to a 10th of what is required for a nonclutching, parallel-elastic leg design with the same kinematics, whereas spring-based compliance extends the leg in stance phase. These mechanisms enable bipedal locomotion with four robot actuators under feedforward control, with high energy efficiency. The robot offers a physical model demonstration of an avian-inspired, multiarticular elastic coupling mechanism that can achieve self-stable, robust, and economic legged locomotion with simple control and no sensory feedback. The proposed design is scalable, allowing the design of large legged robots. BirdBot demonstrates a mechanism for self-engaging and disengaging parallel elastic legs that are contact-triggered by the foot's own lever-arm action.
Collapse
Affiliation(s)
| | | | - Metin Sitti
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, Stuttgart, Germany.,Institute for Biomedical Engineering, ETH-Zürich, Zürich, Switzerland.,School of Medicine and College of Engineering, Koç University, Istanbul, Turkey
| | - Monica A Daley
- Department of Ecology and Evolutionary Biology, University of California, Irvine, CA, USA.,Royal Veterinary College, London, UK
| |
Collapse
|
16
|
The walking and running control of a human musculoskeletal model using a low-power consumption hardware central pattern generator model. INT J ADV ROBOT SYST 2022. [DOI: 10.1177/17298806221080633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Applying a control system with low energy consumption and low load of motion control to robots, similar to living organisms, is considered to be one of the most important issues in robot development. We have been studying systems that use pulse-type hardware neural networks to control robotic motion with a small number of control signals, as is the case in living organisms. In particular, it has been mimicking the function of the central pattern generator localized in the spinal cord of living organisms to generate motion patterns. In the present article, a new biomimetic control system using pulse-type hardware neural networks for biped gait control is reported.
Collapse
|
17
|
Kitano K, Ito A, Tsujiuchi N. Analysis of Dexterity Motion by Singular Value Decomposition for Hand Movement Measured Using Inertial Sensors. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:7136-7139. [PMID: 34892746 DOI: 10.1109/embc46164.2021.9630361] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Finger movements play an important role in many daily human actions. Among the studies on the dexterity of fingers required for various tasks in neurology and simple evaluation tests, few have focused on detailed finger movements themselves. Therefore, in this study, we improved the hand motion measurement system using inertial sensors and the motion analysis method developed in our previous study and measured the motion of the upper limbs (including the fingers) during a general finger dexterity test. By applying singular value decomposition to the obtained joint angles and decomposing them into simpler movement units, we obtained the timing of each movement unit and the purpose of each movement as the coordination state of the joints. By applying hierarchical clustering to multiple trials in a finger dexterity test, we also determined the similarity between trials and investigated the characteristics of movements with higher dexterity. We investigated the motor characteristics in finger dexterity by analyzing our results.
Collapse
|
18
|
Pequera G, Ramírez Paulino I, Biancardi CM. Common motor patterns of asymmetrical and symmetrical bipedal gaits. PeerJ 2021; 9:e11970. [PMID: 34458023 PMCID: PMC8375508 DOI: 10.7717/peerj.11970] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 07/23/2021] [Indexed: 11/20/2022] Open
Abstract
Background Synergy modules have been used to describe activation of lower limb muscles during locomotion and hence to understand how the system controls movement. Walking and running have been shown shared synergy patterns suggesting common motor control of both symmetrical gaits. Unilateral skipping, an equivalent gait to the quadrupedal gallop in humans, has been defined as the third locomotion paradigm but the use by humans is limited due to its high metabolic cost. Synergies in skipping have been little investigated. In particular, to the best of our knowledge, the joint study of both trailing and leading limbs has never been addressed before. Research question How are organized muscle activation patterns in unilateral skipping? Are they organized in the same way that in symmetrical gaits? If yes, which are the muscle activation patterns in skipping that make it a different gait to walking or running? In the present research, we investigate if there are shared control strategies for all gaits in locomotion. Addressing these questions in terms of muscle synergies could suggest possible determinants of the scarce use of unilateral skipping in humans. Methods Electromyographic data of fourteen bilateral muscles were collected from volunteers while performing walking, running and unilateral skipping on a treadmill. Also, spatiotemporal gait parameters were computed from 3D kinematics. The modular composition and activation timing extracted by non-negative matrix factorization were analyzed to detect similarities and differences among symmetrical gaits and unilateral skipping. Results Synergy modules showed high similarity throughout the different gaits and between trailing and leading limbs during unilateral skipping. The synergy associated with the propulsion force operated by calf muscles was anticipated in bouncing gaits. Temporal features of synergies in the leading leg were very similar to those observed for running. The different role of trailing and leading legs in unilateral skipping was reflected by the different timing in two modules. Activation for weight acceptance was anticipated and extended in the trailing leg, preparing the body for landing impact after the flight phase. A different behaviour was detected in the leading leg, which only deals with a pendular weight transference. Significance The evidence gathered in this work supports the hypothesis of shared modules among symmetrical and asymmetrical gaits, suggesting a common motor control despite of the infrequent use of unilateral skipping in humans. Unilateral skipping results from phase-shifted activation of similar muscular groups used in symmetrical gaits, without the need for new muscular groups. The high and anticipated muscle activation in the trailing leg for landing could be the key distinctive event of unilateral skipping.
Collapse
Affiliation(s)
- Germán Pequera
- Ingeniería Biológica, CENUR Litoral Norte, Universidad de la República, Paysandú, Uruguay.,Biomechanics Lab., Dept. de Ciencias Biológicas, CENUR Litoral Norte, Universidad de la República, Paysandú, Uruguay
| | - Ignacio Ramírez Paulino
- Inst. de Ingeniería Eléctrica, Fac. de Ingeniería, Universidad de la República, Montevideo, Uruguay
| | - Carlo M Biancardi
- Biomechanics Lab., Dept. de Ciencias Biológicas, CENUR Litoral Norte, Universidad de la República, Paysandú, Uruguay
| |
Collapse
|
19
|
Song S, Kidziński Ł, Peng XB, Ong C, Hicks J, Levine S, Atkeson CG, Delp SL. Deep reinforcement learning for modeling human locomotion control in neuromechanical simulation. J Neuroeng Rehabil 2021; 18:126. [PMID: 34399772 PMCID: PMC8365920 DOI: 10.1186/s12984-021-00919-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Accepted: 07/29/2021] [Indexed: 11/10/2022] Open
Abstract
Modeling human motor control and predicting how humans will move in novel environments is a grand scientific challenge. Researchers in the fields of biomechanics and motor control have proposed and evaluated motor control models via neuromechanical simulations, which produce physically correct motions of a musculoskeletal model. Typically, researchers have developed control models that encode physiologically plausible motor control hypotheses and compared the resulting simulation behaviors to measurable human motion data. While such plausible control models were able to simulate and explain many basic locomotion behaviors (e.g. walking, running, and climbing stairs), modeling higher layer controls (e.g. processing environment cues, planning long-term motion strategies, and coordinating basic motor skills to navigate in dynamic and complex environments) remains a challenge. Recent advances in deep reinforcement learning lay a foundation for modeling these complex control processes and controlling a diverse repertoire of human movement; however, reinforcement learning has been rarely applied in neuromechanical simulation to model human control. In this paper, we review the current state of neuromechanical simulations, along with the fundamentals of reinforcement learning, as it applies to human locomotion. We also present a scientific competition and accompanying software platform, which we have organized to accelerate the use of reinforcement learning in neuromechanical simulations. This “Learn to Move” competition was an official competition at the NeurIPS conference from 2017 to 2019 and attracted over 1300 teams from around the world. Top teams adapted state-of-the-art deep reinforcement learning techniques and produced motions, such as quick turning and walk-to-stand transitions, that have not been demonstrated before in neuromechanical simulations without utilizing reference motion data. We close with a discussion of future opportunities at the intersection of human movement simulation and reinforcement learning and our plans to extend the Learn to Move competition to further facilitate interdisciplinary collaboration in modeling human motor control for biomechanics and rehabilitation research
Collapse
Affiliation(s)
- Seungmoon Song
- Department of Mechanical Engineering, Stanford University, Stanford, CA, USA.
| | - Łukasz Kidziński
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Xue Bin Peng
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA, USA
| | - Carmichael Ong
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Jennifer Hicks
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Sergey Levine
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA, USA
| | | | - Scott L Delp
- Department of Mechanical Engineering, Stanford University, Stanford, CA, USA.,Department of Bioengineering, Stanford University, Stanford, CA, USA
| |
Collapse
|
20
|
Hagio S, Nakazato M, Kouzaki M. Modulation of spatial and temporal modules in lower limb muscle activations during walking with simulated reduced gravity. Sci Rep 2021; 11:14749. [PMID: 34285306 PMCID: PMC8292403 DOI: 10.1038/s41598-021-94201-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 07/05/2021] [Indexed: 11/17/2022] Open
Abstract
Gravity plays a crucial role in shaping patterned locomotor output to maintain dynamic stability during locomotion. The present study aimed to clarify the gravity-dependent regulation of modules that organize multiple muscle activities during walking in humans. Participants walked on a treadmill at seven speeds (1-6 km h-1 and a subject- and gravity-specific speed determined by the Froude number (Fr) corresponding to 0.25) while their body weight was partially supported by a lift to simulate walking with five levels of gravity conditions from 0.07 to 1 g. Modules, i.e., muscle-weighting vectors (spatial modules) and phase-dependent activation coefficients (temporal modules), were extracted from 12 lower-limb electromyographic (EMG) activities in each gravity (Fr ~ 0.25) using nonnegative matrix factorization. Additionally, a tensor decomposition model was fit to the EMG data to quantify variables depending on the gravity conditions and walking speed with prescribed spatial and temporal modules. The results demonstrated that muscle activity could be explained by four modules from 1 to 0.16 g and three modules at 0.07 g, and the modules were shared for both spatial and temporal components among the gravity conditions. The task-dependent variables of the modules acting on the supporting phase linearly decreased with decreasing gravity, whereas that of the module contributing to activation prior to foot contact showed nonlinear U-shaped modulation. Moreover, the profiles of the gravity-dependent modulation changed as a function of walking speed. In conclusion, reduced gravity walking was achieved by regulating the contribution of prescribed spatial and temporal coordination in muscle activities.
Collapse
Affiliation(s)
- Shota Hagio
- Laboratory of Neurophysiology, Graduate School of Human and Environmental Studies, Kyoto University, Yoshida-nihonmatsu-cho, Sakyo-ku, Kyoto, 606-8501, Japan.
- Unit of Synergetic Studies for Space, Kyoto University, Kyoto, 606-8502, Japan.
| | - Makoto Nakazato
- Laboratory of Neurophysiology, Graduate School of Human and Environmental Studies, Kyoto University, Yoshida-nihonmatsu-cho, Sakyo-ku, Kyoto, 606-8501, Japan
| | - Motoki Kouzaki
- Laboratory of Neurophysiology, Graduate School of Human and Environmental Studies, Kyoto University, Yoshida-nihonmatsu-cho, Sakyo-ku, Kyoto, 606-8501, Japan
- Unit of Synergetic Studies for Space, Kyoto University, Kyoto, 606-8502, Japan
| |
Collapse
|
21
|
A Novel Muscle Synergy Extraction Method Used for Motor Function Evaluation of Stroke Patients: A Pilot Study. SENSORS 2021; 21:s21113833. [PMID: 34205957 PMCID: PMC8199433 DOI: 10.3390/s21113833] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 05/21/2021] [Accepted: 05/28/2021] [Indexed: 12/12/2022]
Abstract
In this paper, we present a novel muscle synergy extraction method based on multivariate curve resolution–alternating least squares (MCR-ALS) to overcome the limitation of the nonnegative matrix factorization (NMF) method for extracting non-sparse muscle synergy, and we study its potential application for evaluating motor function of stroke survivors. Nonnegative matrix factorization (NMF) is the most widely used method for muscle synergy extraction. However, NMF is susceptible to components’ sparseness and usually provides inferior reliability, which significantly limits the promotion of muscle synergy. In this study, MCR-ALS was employed to extract muscle synergy from electromyography (EMG) data. Its performance was compared with two other matrix factorization algorithms, NMF and self-modeling mixture analysis (SMMA). Simulated data sets were utilized to explore the influences of the sparseness and noise on the extracted synergies. As a result, the synergies estimated by MCR-ALS were the most similar to true synergies as compared with SMMA and NMF. MCR-ALS was used to analyze the muscle synergy characteristics of upper limb movements performed by healthy (n = 11) and stroke (n = 5) subjects. The repeatability and intra-subject consistency were used to evaluate the performance of MCR-ALS. As a result, MCR-ALS provided much higher repeatability and intra-subject consistency as compared with NMF, which were important for the reliability of the motor function evaluation. The stroke subjects had lower intra-subject consistency and seemingly had more synergies as compared with the healthy subjects. Thus, MCR-ALS is a promising muscle synergy analysis method for motor function evaluation of stroke patients.
Collapse
|
22
|
Di Russo A, Stanev D, Armand S, Ijspeert A. Sensory modulation of gait characteristics in human locomotion: A neuromusculoskeletal modeling study. PLoS Comput Biol 2021; 17:e1008594. [PMID: 34010288 PMCID: PMC8168850 DOI: 10.1371/journal.pcbi.1008594] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 06/01/2021] [Accepted: 04/16/2021] [Indexed: 11/18/2022] Open
Abstract
The central nervous system of humans and other animals modulates spinal cord activity to achieve several locomotion behaviors. Previous neuromechanical models investigated the modulation of human gait changing selected parameters belonging to CPGs (Central Pattern Generators) feedforward oscillatory structures or to feedback reflex circuits. CPG-based models could replicate slow and fast walking by changing only the oscillation’s properties. On the other hand, reflex-based models could achieve different behaviors through optimizations of large dimensional parameter spaces. However, they could not effectively identify individual key reflex parameters responsible for gait characteristics’ modulation. This study investigates which reflex parameters modulate the gait characteristics through neuromechanical simulations. A recently developed reflex-based model is used to perform optimizations with different target behaviors on speed, step length, and step duration to analyze the correlation between reflex parameters and their influence on these gait characteristics. We identified nine key parameters that may affect the target speed ranging from slow to fast walking (0.48 and 1.71 m/s) as well as a large range of step lengths (0.43 and 0.88 m) and step duration (0.51, 0.98 s). The findings show that specific reflexes during stance significantly affect step length regulation, mainly given by positive force feedback of the ankle plantarflexors’ group. On the other hand, stretch reflexes active during swing of iliopsoas and gluteus maximus regulate all the gait characteristics under analysis. Additionally, the results show that the hamstrings’ group’s stretch reflex during the landing phase is responsible for modulating the step length and step duration. Additional validation studies in simulations demonstrated that the modulation of identified reflexes is sufficient to regulate the investigated gait characteristics. Thus, this study provides an overview of possible reflexes involved in modulating speed, step length, and step duration of human gaits. This study investigates the possible reflex parameters that the central nervous system could use to modulate human locomotion. Specifically, we target the modulation of three gait characteristics: speed, step length, and step duration. We utilize human locomotion simulations with a previously developed reflex-based model and perform multiple optimizations ranging targeting low to high values of the three gait characteristics investigated. From the data acquired in optimizations, we investigate which reflex parameter correlates most with the gait characteristics changes. We identified nine key reflex parameters affecting gait modulation, performed validation experiments, and verified that the optimization of key reflex parameters alone could generate modulation in the studied locomotion behaviors. Kinematics, ground reaction forces, and muscle activity obtained in simulations show similarities with past experimental studies on gait modulation. Therefore, the identified parameters could potentially be used by the nervous system to regulate locomotion behaviors in a task-dependent manner. Other circuits not modeled in this study could play a crucial role in gait modulation, and further investigations should be done in the co-optimization of feedforward and feedback circuits.
Collapse
Affiliation(s)
- Andrea Di Russo
- Biorobotics Laboratory, École polytechnique fédérale de Lausanne, School of Engineering, Institute of Bioengineering, Lausanne, Switzerland
- * E-mail:
| | - Dimitar Stanev
- Biorobotics Laboratory, École polytechnique fédérale de Lausanne, School of Engineering, Institute of Bioengineering, Lausanne, Switzerland
| | - Stéphane Armand
- Kinesiology Laboratory, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Auke Ijspeert
- Biorobotics Laboratory, École polytechnique fédérale de Lausanne, School of Engineering, Institute of Bioengineering, Lausanne, Switzerland
| |
Collapse
|
23
|
Kamimura T, Aoi S, Higurashi Y, Wada N, Tsuchiya K, Matsuno F. Dynamical determinants enabling two different types of flight in cheetah gallop to enhance speed through spine movement. Sci Rep 2021; 11:9631. [PMID: 33953253 PMCID: PMC8099890 DOI: 10.1038/s41598-021-88879-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 04/19/2021] [Indexed: 11/29/2022] Open
Abstract
Cheetahs use a galloping gait in their fastest speed range. It has been reported that cheetahs achieve high-speed galloping by performing two types of flight through spine movement (gathered and extended). However, the dynamic factors that enable cheetahs to incorporate two types of flight while galloping remain unclear. To elucidate this issue from a dynamical viewpoint, we developed a simple analytical model. We derived possible periodic solutions with two different flight types (like cheetah galloping), and others with only one flight type (unlike cheetah galloping). The periodic solutions provided two criteria to determine the flight type, related to the position and magnitude of ground reaction forces entering the body. The periodic solutions and criteria were verified using measured cheetah data, and provided a dynamical mechanism by which galloping with two flight types enhances speed. These findings extend current understanding of the dynamical mechanisms underlying high-speed locomotion in cheetahs.
Collapse
Affiliation(s)
- Tomoya Kamimura
- Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Nagoya, Japan.
| | - Shinya Aoi
- Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Kyoto, Japan
| | - Yasuo Higurashi
- Laboratory of System Physiology, Joint Faculty of Veterinary Medicine, Yamaguchi University, Yamaguchi, Japan
| | - Naomi Wada
- Laboratory of System Physiology, Joint Faculty of Veterinary Medicine, Yamaguchi University, Yamaguchi, Japan
| | - Kazuo Tsuchiya
- Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Kyoto, Japan
| | - Fumitoshi Matsuno
- Department of Mechanical Engineering and Science, Graduate School of Engineering, Kyoto University, Kyoto, Japan
| |
Collapse
|
24
|
A Conceptual Blueprint for Making Neuromusculoskeletal Models Clinically Useful. APPLIED SCIENCES-BASEL 2021. [DOI: 10.3390/app11052037] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
The ultimate goal of most neuromusculoskeletal modeling research is to improve the treatment of movement impairments. However, even though neuromusculoskeletal models have become more realistic anatomically, physiologically, and neurologically over the past 25 years, they have yet to make a positive impact on the design of clinical treatments for movement impairments. Such impairments are caused by common conditions such as stroke, osteoarthritis, Parkinson’s disease, spinal cord injury, cerebral palsy, limb amputation, and even cancer. The lack of clinical impact is somewhat surprising given that comparable computational technology has transformed the design of airplanes, automobiles, and other commercial products over the same time period. This paper provides the author’s personal perspective for how neuromusculoskeletal models can become clinically useful. First, the paper motivates the potential value of neuromusculoskeletal models for clinical treatment design. Next, it highlights five challenges to achieving clinical utility and provides suggestions for how to overcome them. After that, it describes clinical, technical, collaboration, and practical needs that must be addressed for neuromusculoskeletal models to fulfill their clinical potential, along with recommendations for meeting them. Finally, it discusses how more complex modeling and experimental methods could enhance neuromusculoskeletal model fidelity, personalization, and utilization. The author hopes that these ideas will provide a conceptual blueprint that will help the neuromusculoskeletal modeling research community work toward clinical utility.
Collapse
|
25
|
A computational study of fatigue resistance of nitinol stents subjected to walk-induced femoropopliteal artery motion. J Biomech 2021; 118:110295. [PMID: 33578053 DOI: 10.1016/j.jbiomech.2021.110295] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 01/20/2021] [Accepted: 01/23/2021] [Indexed: 11/21/2022]
Abstract
Fatigue resistance of nitinol stents implanted in femoropopliteal arteries is a critical issue because of their harsh biomechanical environment. Limb flexions due to daily walk expose the femoropopliteal arteries and, subsequently, the implanted stents to large cyclic deformations, which may lead to fatigue failure of the smart self-expandable stents. For the first time, this paper utilised the up-to-date measurements of walk-induced motion of a human femoropopliteal artery to investigate the fatigue behaviour of nitinol stent after implantation. The study was carried out by modelling the processes of angioplasty, stent crimping, self-expansion and deformation under diastolic-systolic blood pressure, repetitive bending, torsion and axial compression as well as their combination. The highest risk of fatigue failure of the nitinol stent occurs under a combined loading condition, with the bending contributing the most, followed by compression and torsion. The pulsatile blood pressure alone hardly causes any fatigue failure of the stent. The work is significant for understanding and improving the fatigue performance of nitinol stents through innovative design and procedural optimisation.
Collapse
|
26
|
Ramalingasetty ST, Danner SM, Arreguit J, Markin SN, Rodarie D, Kathe C, Courtine G, Rybak IA, Ijspeert AJ. A Whole-Body Musculoskeletal Model of the Mouse. IEEE ACCESS : PRACTICAL INNOVATIONS, OPEN SOLUTIONS 2021; 9:163861-163881. [PMID: 35211364 PMCID: PMC8865483 DOI: 10.1109/access.2021.3133078] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
Neural control of movement cannot be fully understood without careful consideration of interactions between the neural and biomechanical components. Recent advancements in mouse molecular genetics allow for the identification and manipulation of constituent elements underlying the neural control of movement. To complement experimental studies and investigate the mechanisms by which the neural circuitry interacts with the body and the environment, computational studies modeling motor behaviors in mice need to incorporate a model of the mouse musculoskeletal system. Here, we present the first fully articulated musculoskeletal model of the mouse. The mouse skeletal system has been developed from anatomical references and includes the sets of bones in all body compartments, including four limbs, spine, head and tail. Joints between all bones allow for simulation of full 3D mouse kinematics and kinetics. Hindlimb and forelimb musculature has been implemented using Hill-type muscle models. We analyzed the mouse whole-body model and described the moment-arms for different hindlimb and forelimb muscles, the moments applied by these muscles on the joints, and their involvement in limb movements at different limb/body configurations. The model represents a necessary step for the subsequent development of a comprehensive neuro-biomechanical model of freely behaving mice; this will close the loop between the neural control and the physical interactions between the body and the environment.
Collapse
Affiliation(s)
- Shravan Tata Ramalingasetty
- Biorobotic Laboratory (BioRob), School of Engineering, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Simon M. Danner
- Department of Neurobiology and Anatomy, College of Medicine, Drexel University, Philadelphia, PA 19104, USA
| | - Jonathan Arreguit
- Biorobotic Laboratory (BioRob), School of Engineering, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Sergey N. Markin
- Department of Neurobiology and Anatomy, College of Medicine, Drexel University, Philadelphia, PA 19104, USA
| | - Dimitri Rodarie
- BBP-CORE, Campus Biotech, École Polytechnique Fédérale de Lausanne, 1202 Geneva, Switzerland
| | - Claudia Kathe
- Center for Neuroprosthetics and Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Grégoire Courtine
- Center for Neuroprosthetics and Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Ilya A. Rybak
- Department of Neurobiology and Anatomy, College of Medicine, Drexel University, Philadelphia, PA 19104, USA
| | - Auke Jan Ijspeert
- Biorobotic Laboratory (BioRob), School of Engineering, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| |
Collapse
|
27
|
Parakkal Unni M, Menon PP, Wilson MR, Tsaneva-Atanasova K. Ankle Push-Off Based Mathematical Model for Freezing of Gait in Parkinson's Disease. Front Bioeng Biotechnol 2020; 8:552635. [PMID: 33195117 PMCID: PMC7658398 DOI: 10.3389/fbioe.2020.552635] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Accepted: 09/21/2020] [Indexed: 11/13/2022] Open
Abstract
Freezing is an involuntary stopping of gait observed in late-stage Parkinson's disease (PD) patients. This is a highly debilitating symptom lacking a clear understanding of its causes. Walking in these patients is also associated with high variability, making both prediction of freezing and its understanding difficult. A neuromechanical model describes the motion of the mechanical (motor) aspects of the body under the action of neuromuscular forcing. In this work, a simplified neuromechanical model of gait is used to infer the causes for both the observed variability and freezing in PD. The mathematical model consists of the stance leg (during walking) modeled as a simple inverted pendulum acted upon by the ankle-push off forces from the trailing leg and pathological forces by the plantar-flexors of the stance leg. We model the effect on walking of the swing leg in the biped model and provide a rationale for using an inverted pendulum model. Freezing and irregular walking is demonstrated in the biped model as well as the inverted pendulum model. The inverted pendulum model is further studied semi-analytically to show the presence of horseshoe and chaos. While the plantar flexors of the swing leg push the center of mass (CoM) forward, the plantar flexors of the stance leg generate an opposing torque. Our study reveals that these opposing forces generated by the plantar flexors can induce freezing. Other gait abnormalities nearer to freezing such as a reduction in step length, and irregular walking patterns can also be explained by the model.
Collapse
Affiliation(s)
- Midhun Parakkal Unni
- Department of Mathematics, College of Engineering Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom
| | - Prathyush P Menon
- Department of Mathematics, College of Engineering Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom
| | - Mark R Wilson
- Sport & Health Sciences, University of Exeter, Exeter, United Kingdom
| | - Krasimira Tsaneva-Atanasova
- Department of Mathematics, College of Engineering Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom.,Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria.,Living Systems Institute, University of Exeter, Exeter, United Kingdom.,EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, United Kingdom
| |
Collapse
|
28
|
Tamura D, Aoi S, Funato T, Fujiki S, Senda K, Tsuchiya K. Contribution of Phase Resetting to Adaptive Rhythm Control in Human Walking Based on the Phase Response Curves of a Neuromusculoskeletal Model. Front Neurosci 2020; 14:17. [PMID: 32116492 PMCID: PMC7015040 DOI: 10.3389/fnins.2020.00017] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Accepted: 01/09/2020] [Indexed: 12/03/2022] Open
Abstract
Humans walk adaptively in varying environments by manipulating their complicated and redundant musculoskeletal system. Although the central pattern generators in the spinal cord are largely responsible for adaptive walking through sensory-motor coordination, it remains unclear what neural mechanisms determine walking adaptability. It has been reported that locomotor rhythm and phase are regulated by the production of phase shift and rhythm resetting (phase resetting) for periodic motor commands in response to sensory feedback and perturbation. While the phase resetting has been suggested to make a large contribution to adaptive walking, it has only been investigated based on fictive locomotion in decerebrate cats, and thus it remains unclear if human motor control has such a rhythm regulation mechanism during walking. In our previous work, we incorporated a phase resetting mechanism into a motor control model and demonstrated that it improves the stability and robustness of walking through forward dynamic simulations of a human musculoskeletal model. However, this did not necessarily verify that phase resetting plays a role in human motor control. In our other previous work, we used kinematic measurements of human walking to identify the phase response curve (PRC), which explains phase-dependent responses of a limit cycle oscillator to a perturbation. This revealed how human walking rhythm is regulated by perturbations. In this study, we integrated these two approaches using a physical model and identification of the PRC to examine the hypothesis that phase resetting plays a role in the control of walking rhythm in humans. More specifically, we calculated the PRC using our neuromusculoskeletal model in the same way as our previous human experiment. In particular, we compared the PRCs calculated from two different models with and without phase resetting while referring to the PRC for humans. As a result, although the PRC for the model without phase resetting did not show any characteristic shape, the PRC for the model with phase resetting showed a characteristic phase-dependent shape with trends similar to those of the PRC for humans. These results support our hypothesis and will improve our understanding of adaptive rhythm control in human walking.
Collapse
Affiliation(s)
- Daiki Tamura
- Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Kyoto, Japan
| | - Shinya Aoi
- Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Kyoto, Japan
| | - Tetsuro Funato
- Department of Mechanical Engineering and Intelligent Systems, Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, Japan
| | - Soichiro Fujiki
- Department of Physiology and Biological Information, School of Medicine, Dokkyo Medical University, Tochigi, Japan
| | - Kei Senda
- Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Kyoto, Japan
| | - Kazuo Tsuchiya
- Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Kyoto, Japan
| |
Collapse
|
29
|
Toeda M, Aoi S, Fujiki S, Funato T, Tsuchiya K, Yanagihara D. Gait Generation and Its Energy Efficiency Based on Rat Neuromusculoskeletal Model. Front Neurosci 2020; 13:1337. [PMID: 32009870 PMCID: PMC6978804 DOI: 10.3389/fnins.2019.01337] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2019] [Accepted: 11/27/2019] [Indexed: 01/20/2023] Open
Abstract
Changing gait is crucial for adaptive and smooth animal locomotion. Although it remains unclear what makes animals decide on a specific gait, energy efficiency is an important factor. It has been reported that the relationship of oxygen consumption with speed is U-shaped for each horse gait and that different gaits have different speeds at which oxygen consumption is minimized. This allows the horse to produce energy-efficient locomotion in a wide speed range by changing gait. However, the underlying mechanisms causing oxygen consumption to be U-shaped and the speeds for the minimum consumption to be different between different gaits are unclear. In the present study, we used a neuromusculoskeletal model of the rat to examine the mechanism from a dynamic viewpoint. Specifically, we constructed the musculoskeletal part of the model based on empirical anatomical data on rats and the motor control model based on the physiological concepts of the spinal central pattern generator and muscle synergy. We also incorporated the posture and speed regulation models at the levels of the brainstem and cerebellum. Our model achieved walking through forward dynamic simulation, and the simulated joint kinematics and muscle activities were compared with animal data. Our model also achieved trotting by changing only the phase difference of the muscle-synergy-based motor commands between the forelimb and hindlimb. Furthermore, the speed of each gait varied by changing only the extension phase duration and amplitude of the muscle synergy-based motor commands and the reference values for the regulation models. The relationship between cost of transport (CoT) and speed was U-shaped for both the generated walking and trotting, and the speeds for the minimum CoT were different for the two gaits, as observed in the oxygen consumption of horses. We found that the resonance property and the posture and speed regulations contributed to the CoT shape and difference in speeds for the minimum CoT. We further discussed the energy efficiency of gait based on the simulation results.
Collapse
Affiliation(s)
- Misaki Toeda
- Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
| | - Shinya Aoi
- Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Kyoto, Japan
| | - Soichiro Fujiki
- Department of Physiology and Biological Information, School of Medicine, Dokkyo Medical University, Tochigi, Japan
| | - Tetsuro Funato
- Department of Mechanical Engineering and Intelligent Systems, Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, Japan
| | - Kazuo Tsuchiya
- Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Kyoto, Japan
| | - Dai Yanagihara
- Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
| |
Collapse
|
30
|
Avagliano L, Parenti I, Grazioli P, Di Fede E, Parodi C, Mariani M, Kaiser FJ, Selicorni A, Gervasini C, Massa V. Chromatinopathies: A focus on Cornelia de Lange syndrome. Clin Genet 2020; 97:3-11. [PMID: 31721174 DOI: 10.1111/cge.13674] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 10/22/2019] [Accepted: 10/24/2019] [Indexed: 01/01/2023]
Abstract
In recent years, many genes have been associated with chromatinopathies classified as "Cornelia de Lange Syndrome-like." It is known that the phenotype of these patients becomes less recognizable, overlapping to features characteristic of other syndromes caused by genetic variants affecting different regulators of chromatin structure and function. Therefore, Cornelia de Lange syndrome diagnosis might be arduous due to the seldom discordance between unexpected molecular diagnosis and clinical evaluation. Here, we review the molecular features of Cornelia de Lange syndrome, supporting the hypothesis that "CdLS-like syndromes" are part of a larger "rare disease family" sharing multiple clinical features and common disrupted molecular pathways.
Collapse
Affiliation(s)
- Laura Avagliano
- Department of Health Sciences, Università degli Studi di Milano, Milano, Italy
| | - Ilaria Parenti
- Section for Functional Genetics, Institute of Human Genetics, University of Lübeck, Lübeck, Germany
- Institute of Science and Technology (IST) Austria, Klosterneuburg, Austria
| | - Paolo Grazioli
- Department of Health Sciences, Università degli Studi di Milano, Milano, Italy
| | - Elisabetta Di Fede
- Department of Health Sciences, Università degli Studi di Milano, Milano, Italy
| | - Chiara Parodi
- Department of Health Sciences, Università degli Studi di Milano, Milano, Italy
| | | | - Frank J Kaiser
- Section for Functional Genetics, Institute of Human Genetics, University of Lübeck, Lübeck, Germany
- DZHK e.V. (German Center for Cardiovascular Research), Partner Site Hamburg/Kiel/Lübeck, Lübeck, Germany
- Institut für Humangenetik, Universitätsklinikum Essen, Universität Duisburg-Essen, Essen, Germany
| | | | - Cristina Gervasini
- Department of Health Sciences, Università degli Studi di Milano, Milano, Italy
| | - Valentina Massa
- Department of Health Sciences, Università degli Studi di Milano, Milano, Italy
| |
Collapse
|
31
|
Santuz A, Brüll L, Ekizos A, Schroll A, Eckardt N, Kibele A, Schwenk M, Arampatzis A. Neuromotor Dynamics of Human Locomotion in Challenging Settings. iScience 2019; 23:100796. [PMID: 31962235 PMCID: PMC6971393 DOI: 10.1016/j.isci.2019.100796] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2019] [Revised: 09/15/2019] [Accepted: 12/19/2019] [Indexed: 12/20/2022] Open
Abstract
Is the control of movement less stable when we walk or run in challenging settings? Intuitively, one might answer that it is, given that challenging locomotion externally (e.g., rough terrain) or internally (e.g., age-related impairments) makes our movements more unstable. Here, we investigated how young and old humans synergistically activate muscles during locomotion when different perturbation levels are introduced. Of these control signals, called muscle synergies, we analyzed the local stability and the complexity (or irregularity) over time. Surprisingly, we found that perturbations force the central nervous system to produce muscle activation patterns that are less unstable and less complex. These outcomes show that robust locomotion control in challenging settings is achieved by producing less complex control signals that are more stable over time, whereas easier tasks allow for more unstable and irregular control. We examined the dynamics of motor control of locomotion in challenging settings We extracted muscle synergies (motor modules and primitives) from electromyography The dynamics of the time-dependent motor primitives were modified by perturbations Primitives were wider, less unstable, and complex in the presence of perturbations
Collapse
Affiliation(s)
- Alessandro Santuz
- Department of Training and Movement Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; Berlin School of Movement Science, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; Atlantic Mobility Action Project, Brain Repair Centre, Department of Medical Neuroscience, Dalhousie University, Halifax, Nova Scotia B3H 4R2, Canada.
| | - Leon Brüll
- Department of Training and Movement Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; Berlin School of Movement Science, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; Network Aging Research, Heidelberg University, 69117 Heidelberg, Germany
| | - Antonis Ekizos
- Department of Training and Movement Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; Berlin School of Movement Science, Humboldt-Universität zu Berlin, 10115 Berlin, Germany
| | - Arno Schroll
- Department of Training and Movement Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; Berlin School of Movement Science, Humboldt-Universität zu Berlin, 10115 Berlin, Germany
| | - Nils Eckardt
- Department of Training and Movement Science, Institute for Sport and Sports Science, University of Kassel, 34125 Kassel, Germany; Department of Sport and Movement Science, Institute of Sport Science, Carl von Ossietzky University of Oldenburg, 26129 Oldenburg, Germany
| | - Armin Kibele
- Department of Training and Movement Science, Institute for Sport and Sports Science, University of Kassel, 34125 Kassel, Germany
| | - Michael Schwenk
- Network Aging Research, Heidelberg University, 69117 Heidelberg, Germany; Institute of Sports and Sports Sciences, Heidelberg University, 69117 Heidelberg, Germany
| | - Adamantios Arampatzis
- Department of Training and Movement Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; Berlin School of Movement Science, Humboldt-Universität zu Berlin, 10115 Berlin, Germany
| |
Collapse
|
32
|
Abstract
Human walking speeds can be influenced by multiple factors, from energetic considerations to the time to reach a destination. Neurological deficits or lower-limb injuries can lead to slower walking speeds, and the recovery of able-bodied gait speed and behavior from impaired gait is considered an important rehabilitation goal. Because gait studies are typically performed at faster speeds, little normative data exists for very slow speeds (less than 0.6 ms[Formula: see text]). The purpose of our study was to investigate healthy gait mechanics at extremely slow walking speeds. We recorded kinematic and kinetic data from eight adult subjects walking at four slow speeds from 0.1 ms[Formula: see text] to 0.6 ms[Formula: see text] and at their self-selected speed. We found that known relations for spatiotemporal and work measures are still valid at very slow speeds. Trends derived from slow speeds largely provided reasonable estimates of gait measures at self-selected speeds. Our study helps enable valuable comparisons between able-bodied and impaired gait, including which pathological behaviors can be attributed to slow speeds and which to gait deficits. We also provide a slow walking dataset, which may serve as normative data for clinical evaluations and gait rehabilitative devices.
Collapse
|
33
|
Fujiki S, Aoi S, Tsuchiya K, Danner SM, Rybak IA, Yanagihara D. Phase-Dependent Response to Afferent Stimulation During Fictive Locomotion: A Computational Modeling Study. Front Neurosci 2019; 13:1288. [PMID: 31849596 PMCID: PMC6896512 DOI: 10.3389/fnins.2019.01288] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Accepted: 11/14/2019] [Indexed: 11/13/2022] Open
Abstract
Central pattern generators (CPGs) in the spinal cord generate rhythmic neural activity and control locomotion in vertebrates. These CPGs operate under the control of sensory feedback that affects the generated locomotor pattern and adapt it to the animal's biomechanics and environment. Studies of the effects of afferent stimulation on fictive locomotion in immobilized cats have shown that brief stimulation of peripheral nerves can reset the ongoing locomotor rhythm. Depending on the phase of stimulation and the stimulated nerve, the applied stimulation can either shorten or prolong the current locomotor phase and the locomotor cycle. Here, we used a mathematical model of a half-center CPG to investigate the phase-dependent effects of brief stimulation applied to CPG on the CPG-generated locomotor oscillations. The CPG in the model consisted of two half-centers mutually inhibiting each other. The rhythmic activity in each half-center was based on a slowly inactivating, persistent sodium current. Brief stimulation was applied to CPG half-centers in different phases of the locomotor cycle to produce phase-dependent changes in CPG activity. The model reproduced several results from experiments on the effect of afferent stimulation of fictive locomotion in cats. The mechanisms of locomotor rhythm resetting under different conditions were analyzed using dynamic systems theory methods.
Collapse
Affiliation(s)
- Soichiro Fujiki
- Department of Physiology and Biological Information, Dokkyo Medical University School of Medicine, Mibu, Japan
| | - Shinya Aoi
- Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Kyoto, Japan
| | - Kazuo Tsuchiya
- Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Kyoto, Japan
| | - Simon M Danner
- Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, PA, United States
| | - Ilya A Rybak
- Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, PA, United States
| | - Dai Yanagihara
- Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
| |
Collapse
|
34
|
Oshima H, Aoi S, Funato T, Tsujiuchi N, Tsuchiya K. Variant and Invariant Spatiotemporal Structures in Kinematic Coordination to Regulate Speed During Walking and Running. Front Comput Neurosci 2019; 13:63. [PMID: 31616271 PMCID: PMC6764191 DOI: 10.3389/fncom.2019.00063] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Accepted: 08/27/2019] [Indexed: 12/20/2022] Open
Abstract
Humans walk, run, and change their speed in accordance with circumstances. These gaits are rhythmic motions generated by multi-articulated movements, which have specific spatiotemporal patterns. The kinematic characteristics depend on the gait and speed. In this study, we focused on the kinematic coordination of locomotor behavior to clarify the underlying mechanism for the effect of speed on the spatiotemporal kinematic patterns for each gait. In particular, we used seven elevation angles for the whole-body motion and separated the measured data into different phases depending on the foot-contact condition, that is, single-stance phase, double-stance phase, and flight phase, which have different physical constraints during locomotion. We extracted the spatiotemporal kinematic coordination patterns with singular value decomposition and investigated the effect of speed on the coordination patterns. Our results showed that most of the whole-body motion could be explained by only two sets of temporal and spatial coordination patterns in each phase. Furthermore, the temporal coordination patterns were invariant for different speeds, while the spatial coordination patterns varied. These findings will improve our understanding of human adaptation mechanisms to tune locomotor behavior for changing speed.
Collapse
Affiliation(s)
- Hiroko Oshima
- Department of Mechanical and Systems Engineering, Faculty of Science and Engineering, Doshisha University, Kyoto, Japan.,Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Kyoto, Japan
| | - Shinya Aoi
- Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Kyoto, Japan
| | - Tetsuro Funato
- Department of Mechanical Engineering and Intelligent Systems, Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, Japan
| | - Nobutaka Tsujiuchi
- Department of Mechanical and Systems Engineering, Faculty of Science and Engineering, Doshisha University, Kyoto, Japan
| | - Kazuo Tsuchiya
- Department of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto University, Kyoto, Japan
| |
Collapse
|
35
|
Ichimura D, Yamazaki T. A Pathological Condition Affects Motor Modules in a Bipedal Locomotion Model. Front Neurorobot 2019; 13:79. [PMID: 31616276 PMCID: PMC6763684 DOI: 10.3389/fnbot.2019.00079] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Accepted: 09/05/2019] [Indexed: 12/24/2022] Open
Abstract
Bipedal locomotion is a basic motor activity that requires simultaneous control of multiple muscles. Physiological experiments suggest that the nervous system controls bipedal locomotion efficiently by using motor modules of synergistic muscle activations. If these modules were merged, abnormal locomotion patterns would be realized as observed in patients with neural impairments such as chronic stroke. However, sub-acute patients have been reported not to show such merged motor modules. Therefore, in this study, we examined what conditions in the nervous system merges motor modules. we built a two-dimensional bipedal locomotion model that included a musculoskeletal model with 7 segments and 18 muscles, a neural system with a hierarchical central pattern generator (CPG), and various feedback inputs from reflex organs. The CPG generated synergistic muscle activations comprising 5 motor modules to produce locomotion phases. Our model succeeded to acquire stable locomotion by using the motor modules and reflexes. Next, we examined how a pathological condition altered motor modules. Specifically, we weakened neural inputs to muscles on one leg to simulate a stroke condition. Immediately after the simulated stroke, the model did not walk. Then, internal parameters were modified to recover stable locomotion. We refitted either (a) reflex parameters or (b) CPG parameters to compensate the locomotion by adapting (a) reflexes or (b) the controller. Stable locomotion was recovered in both conditions. However the motor modules were merged only in (b). These results suggest that light or sub-acute stroke patients, who can compensate stable locomotion by just adapting reflexes, would not show merge of motor modules, whereas severe or chronic patients, who needed to adapt the controller for compensation, would show the merge, as consistent with experimental findings.
Collapse
Affiliation(s)
- Daisuke Ichimura
- Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, Japan.,Heisei Ougi Hospital, Tokyo, Japan
| | - Tadashi Yamazaki
- Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, Japan
| |
Collapse
|