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Wang S, Hase K, Funato T. Computational prediction of muscle synergy using a finite element framework for a musculoskeletal model on lower limb. Front Bioeng Biotechnol 2023; 11:1130219. [PMID: 37533695 PMCID: PMC10392837 DOI: 10.3389/fbioe.2023.1130219] [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: 12/23/2022] [Accepted: 07/03/2023] [Indexed: 08/04/2023] Open
Abstract
Previous studies have demonstrated that the central nervous system activates muscles in module patterns to reduce the complexity needed to control each muscle while producing a movement, which is referred to as muscle synergy. In previous musculoskeletal modeling-based muscle synergy analysis studies, as a result of simplification of the joints, a conventional rigid-body link musculoskeletal model failed to represent the physiological interactions of muscle activation and joint kinematics. However, the interaction between the muscle level and joint level that exists in vivo is an important relationship that influences the biomechanics and neurophysiology of the musculoskeletal system. In the present, a lower limb musculoskeletal model coupling a detailed representation of a joint including complex contact behavior and material representations was used for muscle synergy analysis using a decomposition method of non-negative matrix factorization (NMF). The complexity of the representation of a joint in a musculoskeletal system allows for the investigation of the physiological interactions in vivo on the musculoskeletal system, thereby facilitating the decomposition of the muscle synergy. Results indicated that, the activities of the 20 muscles on the lower limb during the stance phase of gait could be controlled by three muscle synergies, and total variance accounted for by synergies was 86.42%. The characterization of muscle synergy and musculoskeletal biomechanics is consistent with the results, thus explaining the formational mechanism of lower limb motions during gait through the reduction of the dimensions of control issues by muscle synergy and the central nervous system.
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Affiliation(s)
- Sentong Wang
- Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, Japan
- Graduate School of Systems Design, Tokyo Metropolitan University, Tokyo, Japan
| | - Kazunori Hase
- Faculty of Systems Design, Tokyo Metropolitan University, Tokyo, Japan
| | - Tetsuro Funato
- Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo, Japan
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Cappellini G, Sylos-Labini F, Avaltroni P, Dewolf AH, Assenza C, Morelli D, Lacquaniti F, Ivanenko Y. Comparison of the forward and sideways locomotor patterns in children with Cerebral Palsy. Sci Rep 2023; 13:7286. [PMID: 37142631 PMCID: PMC10160037 DOI: 10.1038/s41598-023-34369-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 04/28/2023] [Indexed: 05/06/2023] Open
Abstract
Switching locomotion direction is a common task in daily life, and it has been studied extensively in healthy people. Little is known, however, about the locomotor adjustments involved in changing locomotion direction from forward (FW) to sideways (SW) in children with cerebral palsy (CP). The importance of testing the ability of children with CP in this task lies in the assessment of flexible, adaptable adjustments of locomotion as a function of the environmental context. On the one hand, the ability of a child to cope with novel task requirements may provide prognostic cues as to the chances of modifying the gait adaptively. On the other hand, challenging the child with the novel task may represent a useful rehabilitation tool to improve the locomotor performance. SW is an asymmetrical locomotor task and requires a differential control of right and left limb muscles. Here, we report the results of a cross-sectional study comparing FW and SW in 27 children with CP (17 diplegic, 10 hemiplegic, 2-10 years) and 18 age-matched typically developing (TD) children. We analyzed gait kinematics, joint moments, EMG activity of 12 pairs of bilateral muscles, and muscle modules evaluated by factorization of EMG signals. Task performance in several children with CP differed drastically from that of TD children. Only 2/3 of children with CP met the primary outcome, i.e. they succeeded to step sideways, and they often demonstrated attempts to step forward. They tended to rotate their trunk FW, cross one leg over the other, flex the knee and hip. Moreover, in contrast to TD children, children with CP often exhibited similar motor modules for FW and SW. Overall, the results reflect developmental deficits in the control of gait, bilateral coordination and adjustment of basic motor modules in children with CP. We suggest that the sideways (along with the backward) style of locomotion represents a novel rehabilitation protocol that challenges the child to cope with novel contextual requirements.
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Affiliation(s)
- Germana Cappellini
- Laboratory of Neuromotor Physiology, Istituto di Ricovero e Cura a Carattere Scientifico Fondazione Santa Lucia, 306 Via Ardeatina, 00179, Rome, Italy
- Department of Systems Medicine and Center of Space Biomedicine, University of Rome Tor Vergata, 00133, Rome, Italy
| | - Francesca Sylos-Labini
- Laboratory of Neuromotor Physiology, Istituto di Ricovero e Cura a Carattere Scientifico Fondazione Santa Lucia, 306 Via Ardeatina, 00179, Rome, Italy
- Department of Systems Medicine and Center of Space Biomedicine, University of Rome Tor Vergata, 00133, Rome, Italy
| | - Priscilla Avaltroni
- Laboratory of Neuromotor Physiology, Istituto di Ricovero e Cura a Carattere Scientifico Fondazione Santa Lucia, 306 Via Ardeatina, 00179, Rome, Italy
| | - Arthur H Dewolf
- Department of Systems Medicine and Center of Space Biomedicine, University of Rome Tor Vergata, 00133, Rome, Italy
| | - Carla Assenza
- Department of Pediatric Neurorehabilitation, Istituto di Ricovero e Cura a Carattere Scientifico Fondazione Santa Lucia, 00179, Rome, Italy
| | - Daniela Morelli
- Department of Pediatric Neurorehabilitation, Istituto di Ricovero e Cura a Carattere Scientifico Fondazione Santa Lucia, 00179, Rome, Italy
| | - Francesco Lacquaniti
- Laboratory of Neuromotor Physiology, Istituto di Ricovero e Cura a Carattere Scientifico Fondazione Santa Lucia, 306 Via Ardeatina, 00179, Rome, Italy
- Department of Systems Medicine and Center of Space Biomedicine, University of Rome Tor Vergata, 00133, Rome, Italy
| | - Yury Ivanenko
- Laboratory of Neuromotor Physiology, Istituto di Ricovero e Cura a Carattere Scientifico Fondazione Santa Lucia, 306 Via Ardeatina, 00179, Rome, Italy.
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Bach MM, Zandvoort CS, Cappellini G, Ivanenko Y, Lacquaniti F, Daffertshofer A, Dominici N. Development of running is not related to time since onset of independent walking, a longitudinal case study. Front Hum Neurosci 2023; 17:1101432. [PMID: 36875237 PMCID: PMC9978154 DOI: 10.3389/fnhum.2023.1101432] [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: 11/18/2022] [Accepted: 01/23/2023] [Indexed: 02/18/2023] Open
Abstract
Introduction Children start to run after they master walking. How running develops, however, is largely unknown. Methods We assessed the maturity of running pattern in two very young, typically developing children in a longitudinal design spanning about three years. Leg and trunk 3D kinematics and electromyography collected in six recording sessions, with more than a hundred strides each, entered our analysis. We recorded walking during the first session (the session of the first independent steps of the two toddlers at the age of 11.9 and 10.6 months) and fast walking or running for the subsequent sessions. More than 100 kinematic and neuromuscular parameters were determined for each session and stride. The equivalent data of five young adults served to define mature running. After dimensionality reduction using principal component analysis, hierarchical cluster analysis based on the average pairwise correlation distance to the adult running cluster served as a measure for maturity of the running pattern. Results Both children developed running. Yet, in one of them the running pattern did not reach maturity whereas in the other it did. As expected, mature running appeared in later sessions (>13 months after the onset of independent walking). Interestingly, mature running alternated with episodes of immature running within sessions. Our clustering approach separated them. Discussion An additional analysis of the accompanying muscle synergies revealed that the participant who did not reach mature running had more differences in muscle contraction when compared to adults than the other. One may speculate that this difference in muscle activity may have caused the difference in running pattern.
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Affiliation(s)
- Margit M. Bach
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences & Institute of Brain and Behavior Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Coen S. Zandvoort
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences & Institute of Brain and Behavior Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Germana Cappellini
- Laboratory of Neuromotor Physiology, Istituto di Ricovero e Cura a Carattere Scientifico Fondazione Santa Lucia, Rome, Italy
- Department of Systems Medicine, Center of Space Biomedicine, University of Rome Tor Vergata, Rome, Italy
| | - Yury Ivanenko
- Laboratory of Neuromotor Physiology, Istituto di Ricovero e Cura a Carattere Scientifico Fondazione Santa Lucia, Rome, Italy
| | - Francesco Lacquaniti
- Laboratory of Neuromotor Physiology, Istituto di Ricovero e Cura a Carattere Scientifico Fondazione Santa Lucia, Rome, Italy
- Department of Systems Medicine, Center of Space Biomedicine, University of Rome Tor Vergata, Rome, Italy
| | - Andreas Daffertshofer
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences & Institute of Brain and Behavior Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Nadia Dominici
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences & Institute of Brain and Behavior Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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Saito H, Yokoyama H, Sasaki A, Matsushita K, Nakazawa K. Variability of trunk muscle synergies underlying the multidirectional movements and stability trunk motor tasks in healthy individuals. Sci Rep 2023; 13:1193. [PMID: 36681745 PMCID: PMC9867711 DOI: 10.1038/s41598-023-28467-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 01/18/2023] [Indexed: 01/22/2023] Open
Abstract
Muscle synergy analysis is useful for investigating trunk coordination patterns based on the assumption that the central nervous system reduces the dimensionality of muscle activation to simplify movement. This study aimed to quantify the variability in trunk muscle synergy during various trunk motor tasks in healthy participants to provide reference data for evaluating trunk control strategies in patients and athletes. Sixteen healthy individuals performed 11 trunk movement and stability tasks with electromyography (EMG) recording of their spinal and abdominal muscles (6 bilaterally). Non-negative matrix factorization applied to the concatenated EMG of all tasks identified the five trunk muscle synergies (W) with their corresponding temporal patterns (C). The medians of within-cluster similarity defined by scalar products in W and rmax coefficient using the cross-correlation function in C were 0.73-0.86 and 0.64-0.75, respectively, while the inter-session similarities were 0.81-0.96 and 0.74-0.84, respectively. However, the lowest and highest values of both similarity indices were broad, reflecting the musculoskeletal system's redundancy within and between participants. Furthermore, the significant differences in the degree of variability between the trunk synergies may represent the different neural features of synergy organization and strategies to overcome the various mechanical demands of a motor task.
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Affiliation(s)
- Hiroki Saito
- Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
- Department of Physical Therapy, Tokyo University of Technology, Tokyo, Japan
| | - Hikaru Yokoyama
- Institute of Engineering, Tokyo University of Agriculture and Technology, Tokyo, Japan.
| | - Atsushi Sasaki
- Department of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University, Osaka, Japan
- Japan Society for the Promotion of Science, Tokyo, Japan
| | | | - Kimitaka Nakazawa
- Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
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Beltrame G, Scano A, Marino G, Peccati A, Molinari Tosatti L, Portinaro N. Recent developments in muscle synergy analysis in young people with neurodevelopmental diseases: A Systematic Review. Front Bioeng Biotechnol 2023; 11:1145937. [PMID: 37180039 PMCID: PMC10174248 DOI: 10.3389/fbioe.2023.1145937] [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: 01/16/2023] [Accepted: 04/11/2023] [Indexed: 05/15/2023] Open
Abstract
The central nervous system simplifies motor control by sending motor commands activating groups of muscles, known as synergies. Physiological locomotion can be described as a coordinated recruitment of four to five muscle synergies. The first studies on muscle synergies in patients affected by neurological diseases were on stroke survivors. They showed that synergies can be used as biomarkers for motor impairment as they vary in patients with respect to healthy people. Likewise, muscle synergy analysis has been applied to developmental diseases (DD). The need for a comprehensive view of the present findings is crucial for comparing results achieved so far and promote future directions in the field. In the present review, we screened three scientific databases and selected thirty-six papers investigating muscle synergies extracted from locomotion in children affected by DD. Thirty-one articles investigate how cerebral palsy (CP) influences motor control, the currently exploited method in studying motor control in CP and finally the effects of treatments in these patients in terms of synergies and biomechanics; two articles investigate how muscle synergies vary in Duchenne muscular dystrophy (DMD), and three other articles assess other developmental pathologies, such as chronic and acute neuropathic pain. For CP, most of the studies demonstrate that the number of synergies is lower and that the synergy composition varies in the affected children with respect to normal controls. Still, the predictability of treatment's effects and the etiology of muscle synergy variation are open questions, as it has been reported that treatments minimally modify synergies, even if they improve biomechanics. The application of different algorithms in extracting synergies might bring about more subtle differences. Considering DMD, no correlation was found between non-neural muscle weakness and muscle modules' variation, while in chronic pain a decreased number of synergies was observed as a possible consequence of plastic adaptations. Even if the potential of the synergistic approach for clinical and rehabilitation practices is recognized, there is not full consensus on protocols nor widely accepted guidelines for the systematic clinical adoption of the method in DD. We critically commented on the current findings, on the methodological issues and the relative open points, and on the clinical impact of muscle synergies in neurodevelopmental diseases to fill the gap for applying the method in clinical practice.
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Affiliation(s)
- Giulia Beltrame
- Residency Program in Orthopedics and Traumatology, Universitá degli Studi di Milano, Milan, Italy
| | - Alessandro Scano
- Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (STIIMA), Italian Council of National Research (CNR), Milan, Italy
- *Correspondence: Alessandro Scano,
| | - Giorgia Marino
- Physiotherapy Unit, Humanitas Clinical and Research Center—IRCCS, Milan, Italy
| | - Andrea Peccati
- Department of Pediatric Surgery, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Lorenzo Molinari Tosatti
- Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (STIIMA), Italian Council of National Research (CNR), Milan, Italy
| | - Nicola Portinaro
- Residency Program in Orthopedics and Traumatology, Universitá degli Studi di Milano, Milan, Italy
- Department of Pediatric Surgery, Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, Milan, Italy
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Effect of Functional Electrical Stimulation on Gait Parameters in Children with Cerebral Palsy: A Meta-Analysis. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:3972958. [PMID: 36238472 PMCID: PMC9553333 DOI: 10.1155/2022/3972958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 09/01/2022] [Indexed: 12/05/2022]
Abstract
Objective At present, there are controversies on the effectiveness of functional electrical stimulation devices in gait improvement in the clinic, and the results reported in limited literature are contradictory. This paper summarizes and analyzes the relationship between functional electrical stimulation treatment and gait parameter changes in children with cerebral palsy, thus exploring the above controversies' results. Methods Two researchers conducted a detailed search of the literature from the establishment of the database to June 2022. Literature retrieved from databases, including PubMed, Embase, Ovid, Cochrane Library, and Web of Science and the search process followed the principles of Cochrane. The search keywords were “cerebral palsy”, “functional electrical stimulation”, “gait”, or “walk”. Gait and balance parameters were extracted from the literature. Gait parameters, such as walking speed and step length, were included in the meta-analysis. The study used standard mean difference (STD) and 95% confidence interval (CI) to calculate the mean difference between the two groups. The statistic I2 was used to evaluate the heterogeneity between the evaluation studies. Begg's test detected publication bias and the funnel chart was used for visual analysis. Furthermore, Review Manager software was used to make a risk bias map for literature publication bias analysis. Results 9 literatures were included in the analysis, with a total of 282 children with cerebral palsy, including 142 patients in the functional electrical stimulation treatment group and 140 patients in the comfort treatment, general nursing, or other physical therapy. The randomization scheme and result report used in most studies were low risk, which was important for the credibility of this study. Most studies have limitations in the blinding method of participants and subjects, and most of them were single-blind studies, which might have a high risk. The results showed that functional electrical stimulation could increase the walking speed of children with cerebral palsy (SMD = 0.82, P < 0.0001) and increase the walking step length of children with cerebral palsy (SMD = 1.34, 95%CI = 1.07, 1.60, Z = 9.91, P < 0.0001). Funnel plot analysis showed that the literature distribution was uniform and symmetrical, and Begg's test showed no publication bias in included literature. Conclusion This study compared the effects of the functional nerve stimulation treatment group and control group on improving gait parameters of children with cerebral palsy. The results indicated that functional nerve stimulation treatment could increase the gait speed and step length of children with cerebral palsy, which could improve the walking of children with cerebral palsy. Furthermore, this study needs more research data to support our findings. The results of this study might better guide the clinical practice and better use of health as well as financial resources.
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Sorek G, Goudriaan M, Schurr I, Schless SH. Influence of the number of muscles and strides on selective motor control during gait in individuals with cerebral palsy. J Electromyogr Kinesiol 2022; 66:102697. [PMID: 36027660 DOI: 10.1016/j.jelekin.2022.102697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 07/26/2022] [Accepted: 08/10/2022] [Indexed: 10/15/2022] Open
Abstract
OBJECTIVE To evaluate the influence of the number of muscles and strides on estimating motor control accuracy during treadmill-gait, in individuals with cerebral palsy (CP). METHODS Bilateral lower limb electromyography data were extracted for 44 children/adolescents with CP. The number of synergy solutions required to explain 90 % of the variance (tVAF-threshold) and the total variance accounted for by one synergy (tVAF1) were calculated for a different number of strides (between 5 and 50) and muscles both unilaterally (four to seven) and bilaterally (eight to 14). The kappa and intraclass correlation coefficients were used to assess similarities in tVAF-threshold and tVAF1 between the different number of strides and muscle sets. RESULTS In both analyses, the number of muscles influenced the tVAF-threshold. Additionally, using <30 strides led to only substantial-moderate agreement with 50 strides (k < 0.80). In both analyses, the mean tVAF1 values demonstrated high-agreement between the different number of muscles (intraclass-correlations = 0.88-0.93) and strides (intraclass-correlations = 0.96-0.99); In the group level, it may result in an error of ≤2.3 %. However, in the individual level, using different number of muscles or <40 strides may result in an error of ≥6 %. CONCLUSION Differing numbers of muscles and strides did not influence the group mean tVAF1 value, but it influenced the tVAF-threshold value. In addition, using different number of muscles or strides can lead to a large measurement error in the individual tVAF1 value.
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Affiliation(s)
- Gilad Sorek
- Laboratory for Paediatric Motion Analysis and Biofeedback Rehabilitation, ALYN Paediatric and Adolescent Rehabilitation Research Centre (ALYN PARC), Jerusalem, Israel
| | - Marije Goudriaan
- Department of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Department of Rehabilitation Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Itai Schurr
- Clinical Motion Analysis Laboratory, ALYN Paediatric and Adolescent Rehabilitation Centre, Jerusalem, Israel
| | - Simon-Henri Schless
- Laboratory for Paediatric Motion Analysis and Biofeedback Rehabilitation, ALYN Paediatric and Adolescent Rehabilitation Research Centre (ALYN PARC), Jerusalem, Israel; Clinical Motion Analysis Laboratory, ALYN Paediatric and Adolescent Rehabilitation Centre, Jerusalem, Israel.
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Zhvansky DS, Sylos-Labini F, Dewolf A, Cappellini G, d’Avella A, Lacquaniti F, Ivanenko Y. Evaluation of Spatiotemporal Patterns of the Spinal Muscle Coordination Output during Walking in the Exoskeleton. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22155708. [PMID: 35957264 PMCID: PMC9370895 DOI: 10.3390/s22155708] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Revised: 07/21/2022] [Accepted: 07/26/2022] [Indexed: 06/01/2023]
Abstract
Recent advances in the performance and evaluation of walking in exoskeletons use various assessments based on kinematic/kinetic measurements. While such variables provide general characteristics of gait performance, only limited conclusions can be made about the neural control strategies. Moreover, some kinematic or kinetic parameters are a consequence of the control implemented on the exoskeleton. Therefore, standard indicators based on kinematic variables have limitations and need to be complemented by performance measures of muscle coordination and control strategy. Knowledge about what happens at the spinal cord output level might also be critical for rehabilitation since an abnormal spatiotemporal integration of activity in specific spinal segments may result in a risk for abnormalities in gait recovery. Here we present the PEPATO software, which is a benchmarking solution to assess changes in the spinal locomotor output during walking in the exoskeleton with respect to reference data on normal walking. In particular, functional and structural changes at the spinal cord level can be mapped into muscle synergies and spinal maps of motoneuron activity. A user-friendly software interface guides the user through several data processing steps leading to a set of performance indicators as output. We present an example of the usage of this software for evaluating walking in an unloading exoskeleton that allows a person to step in simulated reduced (the Moon's) gravity. By analyzing the EMG activity from lower limb muscles, the algorithms detected several performance indicators demonstrating differential adaptation (shifts in the center of activity, prolonged activation) of specific muscle activation modules and spinal motor pools and increased coactivation of lumbar and sacral segments. The software is integrated at EUROBENCH facilities to benchmark the performance of walking in the exoskeleton from the point of view of changes in the spinal locomotor output.
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Affiliation(s)
- Dmitry S. Zhvansky
- Institute for Information Transmission Problems, Russian Academy of Sciences, 127994 Moscow, Russia;
| | - Francesca Sylos-Labini
- Laboratory of Neuromotor Physiology, IRCCS Santa Lucia Foundation, 00179 Rome, Italy; (F.S.-L.); (A.D.); (G.C.); (A.d.); (F.L.)
- Department of Systems Medicine, University of Rome Tor Vergata, 00133 Rome, Italy
| | - Arthur Dewolf
- Laboratory of Neuromotor Physiology, IRCCS Santa Lucia Foundation, 00179 Rome, Italy; (F.S.-L.); (A.D.); (G.C.); (A.d.); (F.L.)
- Department of Systems Medicine, University of Rome Tor Vergata, 00133 Rome, Italy
| | - Germana Cappellini
- Laboratory of Neuromotor Physiology, IRCCS Santa Lucia Foundation, 00179 Rome, Italy; (F.S.-L.); (A.D.); (G.C.); (A.d.); (F.L.)
- Department of Systems Medicine, University of Rome Tor Vergata, 00133 Rome, Italy
| | - Andrea d’Avella
- Laboratory of Neuromotor Physiology, IRCCS Santa Lucia Foundation, 00179 Rome, Italy; (F.S.-L.); (A.D.); (G.C.); (A.d.); (F.L.)
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, 98100 Messina, Italy
| | - Francesco Lacquaniti
- Laboratory of Neuromotor Physiology, IRCCS Santa Lucia Foundation, 00179 Rome, Italy; (F.S.-L.); (A.D.); (G.C.); (A.d.); (F.L.)
- Department of Systems Medicine and Center of Space Biomedicine, University of Rome Tor Vergata, 00133 Rome, Italy
| | - Yury Ivanenko
- Laboratory of Neuromotor Physiology, IRCCS Santa Lucia Foundation, 00179 Rome, Italy; (F.S.-L.); (A.D.); (G.C.); (A.d.); (F.L.)
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d'Avella A, Ivanenko Y, Lacquaniti F. Muscle synergies in cerebral palsy and variability: challenges and opportunities. Dev Med Child Neurol 2022; 64:404-405. [PMID: 34780675 DOI: 10.1111/dmcn.15106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- Andrea d'Avella
- Laboratory of Neuromotor Physiology, IRCCS Fondazione Santa Lucia, Rome, Italy.,Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy
| | - Yury Ivanenko
- Laboratory of Neuromotor Physiology, IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Francesco Lacquaniti
- Laboratory of Neuromotor Physiology, IRCCS Fondazione Santa Lucia, Rome, Italy.,Department of Systems Medicine and Center of Space Biomedicine, University of Rome Tor Vergata, Rome, Italy
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Liu H, Gao Y, Huang W, Li R, Houston M, Benoit JS, Roh J, Zhang Y. Inter-muscular coherence and functional coordination in the human upper extremity after stroke. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2022; 19:4506-4525. [PMID: 35430825 DOI: 10.3934/mbe.2022208] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Muscle coordination and motor function of stroke patients are weakened by stroke-related motor impairments. Our earlier studies have determined alterations in inter-muscular coordination patterns (muscle synergies). However, the functional connectivity of these synergistically paired or unpaired muscles is still unclear in stroke patients. The goal of this study is to quantify the alterations of inter-muscular coherence (IMC) among upper extremity muscles that have been shown to be synergistically or non-synergistically activated in stroke survivors. In a three-dimensional isometric force matching task, surface EMG signals are collected from 6 age-matched, neurologically intact healthy subjects and 10 stroke patients, while the target force space is divided into 8 subspaces. According to the results of muscle synergy identification with non-negative matrix factorization algorithm, muscle pairs are classified as synergistic and non-synergistic. In both control and stroke groups, IMC is then calculated for all available muscle pairs. The results show that synergistic muscle pairs have higher coherence in both groups. Furthermore, anterior and middle deltoids, identified as synergistic muscles in both groups, exhibited significantly weaker IMC at alpha band in stroke patients. The anterior and posterior deltoids, identified as synergistic muscles only in stroke patients, revealed significantly higher IMC in stroke group at low gamma band. On the contrary, anterior deltoid and pectoralis major, identified as synergistic muscles in control group only, revealed significantly higher IMC in control group in alpha band. The results of muscle synergy and IMC analyses provide congruent and complementary information for investigating the mechanism that underlies post-stroke motor recovery.
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Affiliation(s)
- Hongming Liu
- Zhuoyue Honors College, Hangzhou Dianzi University, Hangzhou 310018, China
- College of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
| | - Yunyuan Gao
- College of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
- Key labortory of Brain Machine Collaborative Intelligence of Zhejiang Province, Hangzhou 311247, China
| | - Wei Huang
- College of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
| | - Rihui Li
- Department of Biomedical Engineering, University of Houston, Houston 75835, United States
| | - Michael Houston
- Department of Biomedical Engineering, University of Houston, Houston 75835, United States
| | - Julia S Benoit
- Texas Institute for Measurement Evaluation and Statistics, University of Houston, Houston 75835, United States
| | - Jinsook Roh
- Department of Biomedical Engineering, University of Houston, Houston 75835, United States
| | - Yingchun Zhang
- Department of Biomedical Engineering, University of Houston, Houston 75835, United States
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