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Monte A, Benamati A, Pavan A, d'Avella A, Bertucco M. Muscle synergies for multidirectional isometric force generation during maintenance of upright standing posture. Exp Brain Res 2024; 242:1881-1902. [PMID: 38874594 PMCID: PMC11252224 DOI: 10.1007/s00221-024-06866-z] [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: 09/26/2023] [Accepted: 05/27/2024] [Indexed: 06/15/2024]
Abstract
Muscle synergies are defined as coordinated recruitment of groups of muscles with specific activation balances and time profiles aimed at generating task-specific motor commands. While muscle synergies in postural control have been investigated primarily in reactive balance conditions, the neuromechanical contribution of muscle synergies during voluntary control of upright standing is still unclear. In this study, muscle synergies were investigated during the generation of isometric force at the trunk during the maintenance of standing posture. Participants were asked to maintain the steady-state upright standing posture while pulling forces of different magnitudes were applied at the level at the waist in eight horizontal directions. Muscle synergies were extracted by nonnegative matrix factorization from sixteen lower limb and trunk muscles. An average of 5-6 muscle synergies were sufficient to account for a wide variety of EMG waveforms associated with changes in the magnitude and direction of pulling forces. A cluster analysis partitioned the muscle synergies of the participants into a large group of clusters according to their similarity, indicating the use of a subjective combination of muscles to generate a multidirectional force vector in standing. Furthermore, we found a participant-specific distribution in the values of cosine directional tuning parameters of synergy amplitude coefficients, suggesting the existence of individual neuromechanical strategies to stabilize the whole-body posture. Our findings provide a starting point for the development of novel diagnostic tools to assess muscle coordination in postural control and lay the foundation for potential applications of muscle synergies in rehabilitation.
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Affiliation(s)
- Andrea Monte
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Via Felice Casorati 43, 37131, Verona, Italy
| | - Anna Benamati
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Via Felice Casorati 43, 37131, Verona, Italy
| | - Agnese Pavan
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Via Felice Casorati 43, 37131, Verona, Italy
| | - Andrea d'Avella
- Laboratory of Neuromotor Physiology, IRCCS Fondazione Santa Lucia, Rome, Italy
- Department of Biology, University of Rome Tor Vergata, Rome, Italy
| | - Matteo Bertucco
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Via Felice Casorati 43, 37131, Verona, Italy.
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Zhao K, Zhang Z, Wen H, Liu B, Li J, Andrea d’Avella, Scano A. Muscle synergies for evaluating upper limb in clinical applications: A systematic review. Heliyon 2023; 9:e16202. [PMID: 37215841 PMCID: PMC10199229 DOI: 10.1016/j.heliyon.2023.e16202] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 04/11/2023] [Accepted: 05/09/2023] [Indexed: 09/28/2023] Open
Abstract
INTRODUCTION Muscle synergies have been proposed as a strategy employed by the central nervous system to control movements. Muscle synergy analysis is a well-established framework to examine the pathophysiological basis of neurological diseases and has been applied for analysis and assessment in clinical applications in the last decades, even if it has not yet been widely used in clinical diagnosis, rehabilitative treatment and interventions. Even if inconsistencies in the outputs among studies and lack of a normative pipeline including signal processing and synergy analysis limit the progress, common findings and results are identifiable as a basis for future research. Therefore, a literature review that summarizes methods and main findings of previous works on upper limb muscle synergies in clinical environment is needed to i) summarize the main findings so far, ii) highlight the barriers limiting their use in clinical applications, and iii) suggest future research directions needed for facilitating translation of experimental research to clinical scenarios. METHODS Articles in which muscle synergies were used to analyze and assess upper limb function in neurological impairments were reviewed. The literature research was conducted in Scopus, PubMed, and Web of Science. Experimental protocols (e.g., the aim of the study, number and type of participants, number and type of muscles, and tasks), methods (e.g., muscle synergy models and synergy extraction methods, signal processing methods), and the main findings of eligible studies were reported and discussed. RESULTS 383 articles were screened and 51 were selected, which involved a total of 13 diseases and 748 patients and 1155 participants. Each study investigated on average 15 ± 10 patients. Four to forty-one muscles were included in the muscle synergy analysis. Point-to-point reaching was the most used task. The preprocessing of EMG signals and algorithms for synergy extraction varied among studies, and non-negative matrix factorization was the most used method. Five EMG normalization methods and five methods for identifying the optimal number of synergies were used in the selected papers. Most of the studies report that analyses on synergy number, structure, and activations provide novel insights on the physiopathology of motor control that cannot be gained with standard clinical assessments, and suggest that muscle synergies may be useful to personalize therapies and to develop new therapeutic strategies. However, in the selected studies synergies were used only for assessment; different testing procedures were used and, in general, study-specific modifications of muscle synergies were observed; single session or longitudinal studies mainly aimed at assessing stroke (71% of the studies), even though other pathologies were also investigated. Synergy modifications were either study-specific or were not observed, with few analyses available for temporal coefficients. Thus, several barriers prevent wider adoption of muscle synergy analysis including a lack of standardized experimental protocols, signal processing procedures, and synergy extraction methods. A compromise in the design of the studies must be found to combine the systematicity of motor control studies and the feasibility of clinical studies. There are however several potential developments that might promote the use of muscle synergy analysis in clinical practice, including refined assessments based on synergistic approaches not allowed by other methods and the availability of novel models. Finally, neural substrates of muscle synergies are discussed, and possible future research directions are proposed. CONCLUSIONS This review provides new perspectives about the challenges and open issues that need to be addressed in future work to achieve a better understanding of motor impairments and rehabilitative therapy using muscle synergies. These include the application of the methods on wider scales, standardization of procedures, inclusion of synergies in the clinical decisional process, assessment of temporal coefficients and temporal-based models, extensive work on the algorithms and understanding of the physio-pathological mechanisms of pathology, as well as the application and adaptation of synergy-based approaches to various rehabilitative scenarios for increasing the available evidence.
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Affiliation(s)
- Kunkun Zhao
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Zhisheng Zhang
- School of Mechanical Engineering, Southeast University, Nanjing, China
| | - Haiying Wen
- School of Mechanical Engineering, Southeast University, Nanjing, China
| | - Bin Liu
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Jianqing Li
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - 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, Italy
| | - Alessandro Scano
- Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA), National Research Council of Italy (CNR), Milan, Italy
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Chen J, Sun Y, Sun S. Muscle Synergy of Lower Limb Motion in Subjects with and without Knee Pathology. Diagnostics (Basel) 2021; 11:diagnostics11081318. [PMID: 34441253 PMCID: PMC8392845 DOI: 10.3390/diagnostics11081318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 07/15/2021] [Accepted: 07/21/2021] [Indexed: 11/29/2022] Open
Abstract
Surface electromyography (sEMG) has great potential in investigating the neuromuscular mechanism for knee pathology. However, due to the complex nature of neural control in lower limb motions and the divergences in subjects’ health and habits, it is difficult to directly use the raw sEMG signals to establish a robust sEMG analysis system. To solve this, muscle synergy analysis based on non-negative matrix factorization (NMF) of sEMG is carried out in this manuscript. The similarities of muscle synergy of subjects with and without knee pathology performing three different lower limb motions are calculated. Based on that, we have designed a classification method for motion recognition and knee pathology diagnosis. First, raw sEMG segments are preprocessed and then decomposed to muscle synergy matrices by NMF. Then, a two-stage feature selection method is executed to reduce the dimension of feature sets extracted from aforementioned matrices. Finally, the random forest classifier is adopted to identify motions or diagnose knee pathology. The study was conducted on an open dataset of 11 healthy subjects and 11 patients. Results show that the NMF-based sEMG classifier can achieve good performance in lower limb motion recognition, and is also an attractive solution for clinical application of knee pathology diagnosis.
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Affiliation(s)
- Jingcheng Chen
- Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; (J.C.); (Y.S.)
- University of Science and Technology of China, Hefei 230026, China
| | - Yining Sun
- Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; (J.C.); (Y.S.)
- University of Science and Technology of China, Hefei 230026, China
| | - Shaoming Sun
- Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; (J.C.); (Y.S.)
- University of Science and Technology of China, Hefei 230026, China
- Correspondence:
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Marion MH, Hicklin LA. Botulinum toxin treatment of dystonic anterocollis: What to inject. Parkinsonism Relat Disord 2021; 88:34-39. [PMID: 34102419 DOI: 10.1016/j.parkreldis.2021.05.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Revised: 05/07/2021] [Accepted: 05/23/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND Anterocollis (AC) is a rare form of cervical dystonia, which responds poorly to botulinum toxin treatment. OBJECTIVES To recognise the different clinical phenotypes of AC and to detail the selection of muscles from the results of treating a cohort of 15 AC patients with Botulinum Toxin. METHODS The study was performed using prospectively collected data. We included 15 patients with cervical dystonia and AC posture, treated between 2016 and 2019 in our joint Neuro-ENT clinic. We excluded patients with posterior cervical muscle weakness and patients with Parkinsonism. We characterised the primary dystonic posture of every AC patient as posterior sagittal shift, head flexion or neck flexion, or a combination of the three. RESULTS All AC patients had a more widespread dystonic picture with a majority having Meige syndrome, but AC was the most problematic feature. Treatment with botulinum toxin required the injection not only of the deep cervical flexor (DCF), but also the sterno-cleido-mastoid (SCM) and moreover the supra-hyoid (SH) muscles. The choice between the longus capiti and the longus colli depended on the AC posture. Half of the patients had a dramatic improvement with 90% satisfaction or above. CONCLUSION AC posture is a complex but treatable type of CD. A joint Neuro-ENT clinic is an ideal setting in which to target all the dystonic muscles. This allows the injection of the longus capiti (under nasal endoscopic approach) as well as the supra-hyoid and SCM muscles in the same session.
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Affiliation(s)
| | - Lucy A Hicklin
- ENT Department, St George's Hospital NHS Foundation Trust, London, United Kingdom
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Jarque-Bou NJ, Sancho-Bru JL, Vergara M. A Systematic Review of EMG Applications for the Characterization of Forearm and Hand Muscle Activity during Activities of Daily Living: Results, Challenges, and Open Issues. SENSORS 2021; 21:s21093035. [PMID: 33925928 PMCID: PMC8123433 DOI: 10.3390/s21093035] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 04/23/2021] [Accepted: 04/24/2021] [Indexed: 11/16/2022]
Abstract
The role of the hand is crucial for the performance of activities of daily living, thereby ensuring a full and autonomous life. Its motion is controlled by a complex musculoskeletal system of approximately 38 muscles. Therefore, measuring and interpreting the muscle activation signals that drive hand motion is of great importance in many scientific domains, such as neuroscience, rehabilitation, physiotherapy, robotics, prosthetics, and biomechanics. Electromyography (EMG) can be used to carry out the neuromuscular characterization, but it is cumbersome because of the complexity of the musculoskeletal system of the forearm and hand. This paper reviews the main studies in which EMG has been applied to characterize the muscle activity of the forearm and hand during activities of daily living, with special attention to muscle synergies, which are thought to be used by the nervous system to simplify the control of the numerous muscles by actuating them in task-relevant subgroups. The state of the art of the current results are presented, which may help to guide and foster progress in many scientific domains. Furthermore, the most important challenges and open issues are identified in order to achieve a better understanding of human hand behavior, improve rehabilitation protocols, more intuitive control of prostheses, and more realistic biomechanical models.
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Borish CN, Bertucco M, Berger DJ, d’Avella A, Sanger TD. Can spatial filtering separate voluntary and involuntary components in children with dyskinetic cerebral palsy? PLoS One 2021; 16:e0250001. [PMID: 33852638 PMCID: PMC8046213 DOI: 10.1371/journal.pone.0250001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 03/30/2021] [Indexed: 11/18/2022] Open
Abstract
The design of myocontrolled devices faces particular challenges in children with dyskinetic cerebral palsy because the electromyographic signal for control contains both voluntary and involuntary components. We hypothesized that voluntary and involuntary components of movements would be uncorrelated and thus detectable as different synergistic patterns of muscle activity, and that removal of the involuntary components would improve online EMG-based control. Therefore, we performed a synergy-based decomposition of EMG-guided movements, and evaluated which components were most controllable using a Fitts' Law task. Similarly, we also tested which muscles were most controllable. We then tested whether removing the uncontrollable components or muscles improved overall function in terms of movement time, success rate, and throughput. We found that removal of less controllable components or muscles did not improve EMG control performance, and in many cases worsened performance. These results suggest that abnormal movement in dyskinetic CP is consistent with a pervasive distortion of voluntary movement rather than a superposition of separable voluntary and involuntary components of movement.
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Affiliation(s)
- Cassie N. Borish
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California, United States of America
| | - Matteo Bertucco
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Denise J. Berger
- Laboratory of Neuromotor Physiology, Foundation Santa Lucia, Rome, Italy
- Department of Systems Medicine and Centre of Space Bio-medicine, University of Rome Tor Vergata, Rome, Italy
| | - Andrea d’Avella
- Laboratory of Neuromotor Physiology, Foundation Santa Lucia, Rome, Italy
- Department of Biomedical, Dental, Morphological and Functional Imaging Sciences, University of Messina, Messina, Italy
| | - Terence D. Sanger
- School of Engineering, University of California, Irvine, California, United States of America
- School of Medicine, University of California, Irvine, California, United States of America
- Children’s Hospital of Orange County, Orange, California, United States of America
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Turpin NA, Uriac S, Dalleau G. How to improve the muscle synergy analysis methodology? Eur J Appl Physiol 2021; 121:1009-1025. [PMID: 33496848 DOI: 10.1007/s00421-021-04604-9] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Accepted: 01/10/2021] [Indexed: 01/02/2023]
Abstract
Muscle synergy analysis is increasingly used in domains such as neurosciences, robotics, rehabilitation or sport sciences to analyze and better understand motor coordination. The analysis uses dimensionality reduction techniques to identify regularities in spatial, temporal or spatio-temporal patterns of multiple muscle activation. Recent studies have pointed out variability in outcomes associated with the different methodological options available and there was a need to clarify several aspects of the analysis methodology. While synergy analysis appears to be a robust technique, it remain a statistical tool and is, therefore, sensitive to the amount and quality of input data (EMGs). In particular, attention should be paid to EMG amplitude normalization, baseline noise removal or EMG filtering which may diminish or increase the signal-to-noise ratio of the EMG signal and could have major effects on synergy estimates. In order to robustly identify synergies, experiments should be performed so that the groups of muscles that would potentially form a synergy are activated with a sufficient level of activity, ensuring that the synergy subspace is fully explored. The concurrent use of various synergy formulations-spatial, temporal and spatio-temporal synergies- should be encouraged. The number of synergies represents either the dimension of the spatial structure or the number of independent temporal patterns, and we observed that these two aspects are often mixed in the analysis. To select a number, criteria based on noise estimates, reliability of analysis results, or functional outcomes of the synergies provide interesting substitutes to criteria solely based on variance thresholds.
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Affiliation(s)
- Nicolas A Turpin
- IRISSE (EA 4075), UFR SHE-STAPS Department, University of La Réunion, 117 Rue du Général Ailleret, 97430, Le Tampon, France.
| | - Stéphane Uriac
- IRISSE (EA 4075), UFR SHE-STAPS Department, University of La Réunion, 117 Rue du Général Ailleret, 97430, Le Tampon, France
| | - Georges Dalleau
- IRISSE (EA 4075), UFR SHE-STAPS Department, University of La Réunion, 117 Rue du Général Ailleret, 97430, Le Tampon, France
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Neuromuscular incoordination in musician's dystonia. Parkinsonism Relat Disord 2019; 65:97-104. [DOI: 10.1016/j.parkreldis.2019.05.011] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Revised: 05/04/2019] [Accepted: 05/07/2019] [Indexed: 11/17/2022]
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Lunardini F, Antonietti A, Casellato C, Pedrocchi A. Synergy-Based Myocontrol of a Multiple Degree-of-Freedom Humanoid Robot for Functional Tasks. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2019; 2019:5108-5112. [PMID: 31947008 DOI: 10.1109/embc.2019.8857809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
In the context of sensor-based human-robot interaction, a particularly promising solution is represented by myoelectric control schemes based on synergy-derived signals. We developed and tested on healthy subjects a synergy-based control to achieve simultaneous, continuous actuation of three degrees of freedom of a humanoid robot, while performing functional reach-to-grasp movements. The control scheme exploits subject-specific muscle synergies extracted from eleven upper limb muscles through an easy semi-supervised calibration phase, and computes online activation coefficients to actuate the robot joints. The humanoid robot was able to well reproduce the subjects' motion, which consisted in free multi-degree-of-freedom reach-to-grasp movements at self-paced speeds. Furthermore, the synergy-based online control significantly outperformed a traditional muscle-pair approach (that uses a pair of antagonist muscles for each joint), in terms of decreased error, increased correlation, and peak correlation between the subjects' and the robot's joint angles. The delay introduced by the two algorithms was comparable. This work is a proof-of-concept for an intuitive and robust myocontrol interface, without the need for any training and practice. It has several potential applications, especially for functional assistive engaging devices in children with social and motor impairments.
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Motor primitives are determined in early development and are then robustly conserved into adulthood. Proc Natl Acad Sci U S A 2019; 116:12025-12034. [PMID: 31138689 DOI: 10.1073/pnas.1821455116] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Motor patterns in legged vertebrates show modularity in both young and adult animals, comprising motor synergies or primitives. Are such spinal modules observed in young mammals conserved into adulthood or altered? Conceivably, early circuit modules alter radically through experience and descending pathways' activity. We analyze lumbar motor patterns of intact adult rats and the same rats after spinal transection and compare these with adult rats spinal transected 5 days postnatally, before most motor experience, using only rats that never developed hind limb weight bearing. We use independent component analysis (ICA) to extract synergies from electromyography (EMG). ICA information-based methods identify both weakly active and strongly active synergies. We compare all spatial synergies and their activation/drive strengths as proxies of spinal modules and their underlying circuits. Remarkably, we find that spatial primitives/synergies of adult injured and neonatal injured rats differed insignificantly, despite different developmental histories. However, intact rats possess some synergies that differ significantly, although modestly, in spatial structure. Rats injured as adults were more similar in modularity to rats that had neonatal spinal transection than to themselves before injury. We surmise that spinal circuit modules for spatial synergy patterns may be determined early, before postnatal day 5 (P5), and remain largely unaltered by subsequent development or weight-bearing experience. An alternative explanation but equally important is that, after complete spinal transection, both neonatal and mature adult spinal cords rapidly converge to common synergy sets. This fundamental or convergent synergy circuitry, fully determined by P5, is revealed after spinal cord transection.
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Desrochers P, Brunfeldt A, Sidiropoulos C, Kagerer F. Sensorimotor Control in Dystonia. Brain Sci 2019; 9:brainsci9040079. [PMID: 30979073 PMCID: PMC6523253 DOI: 10.3390/brainsci9040079] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Revised: 04/03/2019] [Accepted: 04/08/2019] [Indexed: 12/24/2022] Open
Abstract
This is an overview of the sensorimotor impairments in dystonia, a syndrome characterized by sustained or intermittent aberrant movement patterns leading to abnormal movements and/or postures with or without a tremulous component. Dystonia can affect the entire body or specific body regions and results from a plethora of etiologies, including subtle changes in gray and white matter in several brain regions. Research over the last 25 years addressing topics of sensorimotor control has shown functional sensorimotor impairments related to sensorimotor integration, timing, oculomotor and head control, as well as upper and lower limb control. In the context of efforts to update the classification of dystonia, sensorimotor research is highly relevant for a better understanding of the underlying pathology, and potential mechanisms contributing to global and regional dysfunction within the central nervous system. This overview of relevant research regarding sensorimotor control in humans with idiopathic dystonia attempts to frame the dysfunction with respect to what is known regarding motor control in patients and healthy individuals. We also highlight promising avenues for the future study of neuromotor control that may help to further elucidate dystonia etiology, pathology, and functional characteristics.
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Affiliation(s)
- Phillip Desrochers
- Dept. of Kinesiology, Michigan State University, East Lansing, MI 48824, USA.
| | - Alexander Brunfeldt
- Dept. of Kinesiology, Michigan State University, East Lansing, MI 48824, USA.
| | - Christos Sidiropoulos
- Dept. of Neurology and Ophthalmology, Michigan State University, East Lansing, MI 48824, USA.
| | - Florian Kagerer
- Dept. of Kinesiology, Michigan State University, East Lansing, MI 48824, USA.
- Neuroscience Program, Michigan State University, East Lansing, MI 48824, USA.
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Scano A, Chiavenna A, Malosio M, Molinari Tosatti L, Molteni F. Robotic Assistance for Upper Limbs May Induce Slight Changes in Motor Modules Compared With Free Movements in Stroke Survivors: A Cluster-Based Muscle Synergy Analysis. Front Hum Neurosci 2018; 12:290. [PMID: 30174596 PMCID: PMC6107841 DOI: 10.3389/fnhum.2018.00290] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Accepted: 06/29/2018] [Indexed: 11/13/2022] Open
Abstract
Background: The efficacy of robot-assisted rehabilitation as a technique for achieving motor recovery is still being debated. The effects of robotic assistance are generally measured using standard clinical assessments. Few studies have investigated the value of human-centered instrumental analysis, taking the modular organization of the human neuromotor system into account in assessing how stroke survivors interact with robotic set-ups. In this paper, muscle synergy analysis was coupled with clustering procedures to elucidate the effect of human-robot interaction on the spatial and temporal features, and directional tuning of motor modules during robot-assisted movements. Methods: Twenty-two stroke survivors completed a session comprising a series of hand-to-mouth movements with and without robotic assistance. Patients were assessed instrumentally, recording kinematic, and electromyographic data to extract spatial muscle synergies and their temporal components. Patients' spatial synergies were grouped by means of a cluster analysis, matched pairwise across conditions (free and robot-assisted movement), and compared in terms of their spatial and temporal features, and directional tuning, to examine how robotic assistance altered their motor modules. Results: Motor synergies were successfully extracted for all 22 patients in both conditions. Seven clusters (spatial synergies) could describe the original datasets, in both free and robot-assisted movements. Interacting with the robot slightly altered the spatial synergies' features (to a variable extent), as well as their temporal components and directional tuning. Conclusions: Slight differences were identified in the characteristics of spatial synergies, temporal components and directional tuning of the motor modules of stroke survivors engaging in free and robot-assisted movements. Such effects are worth investigating in the framework of a modular description of the neuromusculoskeletal system to shed more light on human-robot interaction, and the effects of robotic assistance and rehabilitation.
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Affiliation(s)
- Alessandro Scano
- Intelligent Industrial Systems and Technologies for Advanced Manufacturing, Italian National Research Council, Milan, Italy
| | - Andrea Chiavenna
- Intelligent Industrial Systems and Technologies for Advanced Manufacturing, Italian National Research Council, Milan, Italy
| | - Matteo Malosio
- Intelligent Industrial Systems and Technologies for Advanced Manufacturing, Italian National Research Council, Milan, Italy
| | - Lorenzo Molinari Tosatti
- Intelligent Industrial Systems and Technologies for Advanced Manufacturing, Italian National Research Council, Milan, Italy
| | - Franco Molteni
- Rehabilitation Presidium, Valduce Ospedale Villa Beretta, Costa Masnaga, Italy
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Comparison of Initialization Techniques for the Accurate Extraction of Muscle Synergies from Myoelectric Signals via Nonnegative Matrix Factorization. Appl Bionics Biomech 2018; 2018:3629347. [PMID: 29853993 PMCID: PMC5964491 DOI: 10.1155/2018/3629347] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2017] [Revised: 03/16/2018] [Accepted: 03/26/2018] [Indexed: 11/29/2022] Open
Abstract
The main goal of this work was to assess the performance of different initializations of matrix factorization algorithms for an accurate identification of muscle synergies. Currently, nonnegative matrix factorization (NNMF) is the most commonly used method to identify muscle synergies. However, it has been shown that NNMF performance might be affected by different kinds of initialization. The present study aims at optimizing the traditional NNMF initialization for data with partial or complete temporal dependencies. For this purpose, three different initializations are used: random, SVD-based, and sparse. NNMF was used to identify muscle synergies from simulated data as well as from experimental surface EMG signals. Simulated data were generated from synthetic independent and dependent synergy vectors (i.e., shared muscle components), whose activation coefficients were corrupted by simulating controlled degrees of correlation. Similarly, EMG data were artificially modified, making the extracted activation coefficients temporally dependent. By measuring the quality of identification of the original synergies underlying the data, it was possible to compare the performance of different initialization techniques. Simulation results demonstrate that sparse initialization performs significantly better than all other kinds of initialization in reconstructing muscle synergies, regardless of the correlation level in the data.
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A Systematic Review on Muscle Synergies: From Building Blocks of Motor Behavior to a Neurorehabilitation Tool. Appl Bionics Biomech 2018; 2018:3615368. [PMID: 29849756 PMCID: PMC5937559 DOI: 10.1155/2018/3615368] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Accepted: 01/29/2018] [Indexed: 12/20/2022] Open
Abstract
The central nervous system (CNS) is believed to utilize specific predefined modules, called muscle synergies (MS), to accomplish a motor task. Yet questions persist about how the CNS combines these primitives in different ways to suit the task conditions. The MS hypothesis has been a subject of debate as to whether they originate from neural origins or nonneural constraints. In this review article, we present three aspects related to the MS hypothesis: (1) the experimental and computational evidence in support of the existence of MS, (2) algorithmic approaches for extracting them from surface electromyography (EMG) signals, and (3) the possible role of MS as a neurorehabilitation tool. We note that recent advances in computational neuroscience have utilized the MS hypothesis in motor control and learning. Prospective advances in clinical, medical, and engineering sciences and in fields such as robotics and rehabilitation stand to benefit from a more thorough understanding of MS.
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Feasibility of Muscle Synergy Outcomes in Clinics, Robotics, and Sports: A Systematic Review. Appl Bionics Biomech 2018; 2018:3934698. [PMID: 29808098 PMCID: PMC5902115 DOI: 10.1155/2018/3934698] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2017] [Revised: 03/05/2018] [Accepted: 03/12/2018] [Indexed: 01/04/2023] Open
Abstract
In the last years, several studies have been focused on understanding how the central nervous system controls muscles to perform a specific motor task. Although it still remains an open question, muscle synergies have come to be an appealing theory to explain the modular organization of the central nervous system. Even though the neural encoding of muscle synergies remains controversial, a large number of papers demonstrated that muscle synergies are robust across different tested conditions, which are within a day, between days, within a single subject, and between subjects that have similar demographic characteristics. Thus, muscle synergy theory has been largely used in several research fields, such as clinics, robotics, and sports. The present systematical review aims at providing an overview on the applications of muscle synergy theory in clinics, robotics, and sports; in particular, the review is focused on the papers that provide tangible information for (i) diagnosis or pathology assessment in clinics, (ii) robot-control design in robotics, and (iii) athletes' performance assessment or training guidelines in sports.
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Sadnicka A, Stevenson A, Bhatia KP, Rothwell JC, Edwards MJ, Galea JM. High motor variability in DYT1 dystonia is associated with impaired visuomotor adaptation. Sci Rep 2018; 8:3653. [PMID: 29483592 PMCID: PMC5826938 DOI: 10.1038/s41598-018-21545-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2017] [Accepted: 02/06/2018] [Indexed: 11/29/2022] Open
Abstract
For the healthy motor control system, an essential regulatory role is maintaining the equilibrium between keeping unwanted motor variability in check whilst allowing informative elements of motor variability. Kinematic studies in children with generalised dystonia (due to mixed aetiologies) show that movements are characterised by increased motor variability. In this study, the mechanisms by which high motor variability may influence movement generation in dystonia were investigated. Reaching movements in the symptomatic arm of 10 patients with DYT1 dystonia and 12 age-matched controls were captured using a robotic manipulandum and features of motor variability were extracted. Given that task-relevant variability and sensorimotor adaptation are related in health, markers of variability were then examined for any co-variance with performance indicators during an error-based learning visuomotor adaptation task. First, we confirmed that motor variability on a trial-by-trial basis was selectively increased in the homogenous and prototypical dystonic disorder DYT1 dystonia. Second, high baseline variability predicted poor performance in the subsequent visuomotor adaptation task offering insight into the rules which appear to govern dystonic motor control. The potential mechanisms behind increased motor variability and its corresponding implications for the rehabilitation of patients with DYT1 dystonia are highlighted.
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Affiliation(s)
- Anna Sadnicka
- Sobell Department for Motor Neuroscience and Movement Disorders, Institute of Neurology, University College London, 33 Queen Square, London, WC1N 3BG, UK. .,Motor Control and Movement Disorder Group, Institute of Molecular and Clinical Sciences, St George's University of London, Cranmer Terrace, Tooting, London, SW17 0RE, UK.
| | - Anna Stevenson
- Sobell Department for Motor Neuroscience and Movement Disorders, Institute of Neurology, University College London, 33 Queen Square, London, WC1N 3BG, UK
| | - Kailash P Bhatia
- Sobell Department for Motor Neuroscience and Movement Disorders, Institute of Neurology, University College London, 33 Queen Square, London, WC1N 3BG, UK
| | - John C Rothwell
- Sobell Department for Motor Neuroscience and Movement Disorders, Institute of Neurology, University College London, 33 Queen Square, London, WC1N 3BG, UK
| | - Mark J Edwards
- Motor Control and Movement Disorder Group, Institute of Molecular and Clinical Sciences, St George's University of London, Cranmer Terrace, Tooting, London, SW17 0RE, UK
| | - Joseph M Galea
- Galea Lab, School of Psychology, University of Birmingham, Birmingham, B15 2TT, UK
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Scano A, Chiavenna A, Malosio M, Molinari Tosatti L, Molteni F. Muscle Synergies-Based Characterization and Clustering of Poststroke Patients in Reaching Movements. Front Bioeng Biotechnol 2017; 5:62. [PMID: 29082227 PMCID: PMC5645509 DOI: 10.3389/fbioe.2017.00062] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2017] [Accepted: 09/26/2017] [Indexed: 11/13/2022] Open
Abstract
Background A deep characterization of neurological patients is a crucial step for a detailed knowledge of the pathology and maximal exploitation and customization of the rehabilitation therapy. The muscle synergies analysis was designed to investigate how muscles coactivate and how their eliciting commands change in time during movement production. Few studies investigated the value of muscle synergies for the characterization of neurological patients before rehabilitation therapies. In this article, the synergy analysis was used to characterize a group of chronic poststroke hemiplegic patients. Methods Twenty-two poststroke patients performed a session composed of a sequence of 3D reaching movements. They were assessed through an instrumental assessment, by recording kinematics and electromyography to extract muscle synergies and their activation commands. Patients’ motor synergies were grouped by the means of cluster analysis. Consistency and characterization of each cluster was assessed and clinically profiled by comparison with standard motor assessments. Results Motor synergies were successfully extracted on all 22 patients. Five basic clusters were identified as a trade-off between clustering precision and synthesis power, representing: healthy-like activations, two shoulder compensatory strategies, two elbow predominance patterns. Each cluster was provided with a deep characterization and correlation with clinical scales, range of motion, and smoothness. Conclusion The clustering of muscle synergies enabled a pretherapy characterization of patients. Such technique may affect several aspects of the therapy: prediction of outcomes, evaluation of the treatments, customization of doses, and therapies.
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Affiliation(s)
- Alessandro Scano
- Institute of Industrial Technologies and Automation (ITIA), Italian National Research Council (CNR), Milan, Italy
| | - Andrea Chiavenna
- Institute of Industrial Technologies and Automation (ITIA), Italian National Research Council (CNR), Milan, Italy
| | - Matteo Malosio
- Institute of Industrial Technologies and Automation (ITIA), Italian National Research Council (CNR), Milan, Italy
| | - Lorenzo Molinari Tosatti
- Institute of Industrial Technologies and Automation (ITIA), Italian National Research Council (CNR), Milan, Italy
| | - Franco Molteni
- Rehabilitation Presidium of Valduce Ospedale Villa Beretta, Lecco, Italy
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