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Troisi Lopez E, Liparoti M, Minino R, Romano A, Polverino A, Carotenuto A, Tafuri D, Sorrentino G, Sorrentino P. Kinematic network of joint motion provides insight on gait coordination: An observational study on Parkinson's disease. Heliyon 2024; 10:e35751. [PMID: 39170156 PMCID: PMC11337059 DOI: 10.1016/j.heliyon.2024.e35751] [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: 01/11/2024] [Revised: 08/01/2024] [Accepted: 08/02/2024] [Indexed: 08/23/2024] Open
Abstract
The analysis of gait kinematics requires to encode and collapse multidimensional information from multiple anatomical elements. In this study, we address this issue by analyzing the joints' coordination during gait, borrowing from the framework of network theory. We recruited twenty-three patients with Parkinson's disease and twenty-three matched controls that were recorded during linear gait using a stereophotogrammetric motion analysis system. The three-dimensional angular velocity of the joints was used to build a kinematic network for each participant, and both global (average whole-body synchronization) and nodal (individual joint synchronization, i.e., nodal strength) were extracted. By comparing the two groups, the results showed lower coordination in patients, both at global and nodal levels (neck, shoulders, elbows, and hips). Furthermore, the nodal strength of the left elbow and right hip in the patients, as well as the average joints' nodal strength were significantly correlated with the clinical motor condition and were predictive of it. Our study highlights the importance of integrating whole-body information in kinematic analyses and the advantages of using network theory. Finally, the identification of altered network properties of specific joints, and their relationship with the motor impairment in the patients, suggests a potential clinical relevance for our approach.
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Affiliation(s)
- Emahnuel Troisi Lopez
- Institute of Applied Sciences and Intelligent Systems, National Research Council, Pozzuoli, Italy
| | - Marianna Liparoti
- Department of Philosophical, Pedagogical and Quantitative-Economics Sciences, University of Studies G. D'Annunzio, Chieti-Pescara, Italy
| | - Roberta Minino
- Department of Medical, Human Movement and Well-being Sciences, University of Naples “Parthenope”, Naples, Italy
| | - Antonella Romano
- Department of Medical, Human Movement and Well-being Sciences, University of Naples “Parthenope”, Naples, Italy
| | | | | | - Domenico Tafuri
- Department of Medical, Human Movement and Well-being Sciences, University of Naples “Parthenope”, Naples, Italy
| | - Giuseppe Sorrentino
- Institute of Applied Sciences and Intelligent Systems, National Research Council, Pozzuoli, Italy
- Department of Economics, Law, Cybersecurity and Sport Sciences, University of Naples “Parthenope”, Nola, Italy
| | - Pierpaolo Sorrentino
- Institute of Applied Sciences and Intelligent Systems, National Research Council, Pozzuoli, Italy
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
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Borzelli D, De Marchis C, Quercia A, De Pasquale P, Casile A, Quartarone A, Calabrò RS, d’Avella A. Muscle Synergy Analysis as a Tool for Assessing the Effectiveness of Gait Rehabilitation Therapies: A Methodological Review and Perspective. Bioengineering (Basel) 2024; 11:793. [PMID: 39199751 PMCID: PMC11351442 DOI: 10.3390/bioengineering11080793] [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: 06/25/2024] [Revised: 07/19/2024] [Accepted: 07/29/2024] [Indexed: 09/01/2024] Open
Abstract
According to the modular hypothesis for the control of movement, muscles are recruited in synergies, which capture muscle coordination in space, time, or both. In the last two decades, muscle synergy analysis has become a well-established framework in the motor control field and for the characterization of motor impairments in neurological patients. Altered modular control during a locomotion task has been often proposed as a potential quantitative metric for characterizing pathological conditions. Therefore, the purpose of this systematic review is to analyze the recent literature that used a muscle synergy analysis of neurological patients' locomotion as an indicator of motor rehabilitation therapy effectiveness, encompassing the key methodological elements to date. Searches for the relevant literature were made in Web of Science, PubMed, and Scopus. Most of the 15 full-text articles which were retrieved and included in this review identified an effect of the rehabilitation intervention on muscle synergies. However, the used experimental and methodological approaches varied across studies. Despite the scarcity of studies that investigated the effect of rehabilitation on muscle synergies, this review supports the utility of muscle synergies as a marker of the effectiveness of rehabilitative therapy and highlights the challenges and open issues that future works need to address to introduce the muscle synergies in the clinical practice and decisional process.
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Affiliation(s)
- Daniele Borzelli
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, 98125 Messina, Italy; (A.Q.); (A.C.)
- Laboratory of Neuromotor Physiology, IRCCS Fondazione Santa Lucia, 00179 Rome, Italy;
| | | | - Angelica Quercia
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, 98125 Messina, Italy; (A.Q.); (A.C.)
| | - Paolo De Pasquale
- IRCCS Centro Neurolesi “Bonino Pulejo”, 98124 Messina, Italy; (P.D.P.); (A.Q.); (R.S.C.)
| | - Antonino Casile
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, 98125 Messina, Italy; (A.Q.); (A.C.)
| | - Angelo Quartarone
- IRCCS Centro Neurolesi “Bonino Pulejo”, 98124 Messina, Italy; (P.D.P.); (A.Q.); (R.S.C.)
| | | | - Andrea d’Avella
- Laboratory of Neuromotor Physiology, IRCCS Fondazione Santa Lucia, 00179 Rome, Italy;
- Department of Biology, University of Rome Tor Vergata, 00133 Rome, Italy
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Scano A, Lanzani V, Brambilla C, d’Avella A. Transferring Sensor-Based Assessments to Clinical Practice: The Case of Muscle Synergies. SENSORS (BASEL, SWITZERLAND) 2024; 24:3934. [PMID: 38931719 PMCID: PMC11207859 DOI: 10.3390/s24123934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Revised: 06/10/2024] [Accepted: 06/15/2024] [Indexed: 06/28/2024]
Abstract
Sensor-based assessments in medical practice and rehabilitation include the measurement of physiological signals such as EEG, EMG, ECG, heart rate, and NIRS, and the recording of movement kinematics and interaction forces. Such measurements are commonly employed in clinics with the aim of assessing patients' pathologies, but so far some of them have found full exploitation mainly for research purposes. In fact, even though the data they allow to gather may shed light on physiopathology and mechanisms underlying motor recovery in rehabilitation, their practical use in the clinical environment is mainly devoted to research studies, with a very reduced impact on clinical practice. This is especially the case for muscle synergies, a well-known method for the evaluation of motor control in neuroscience based on multichannel EMG recordings. In this paper, considering neuromotor rehabilitation as one of the most important scenarios for exploiting novel methods to assess motor control, the main challenges and future perspectives for the standard clinical adoption of muscle synergy analysis are reported and critically discussed.
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Affiliation(s)
- Alessandro Scano
- Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (STIIMA), Italian Council of National Research (CNR), 20133 Milan, Italy; (V.L.); (C.B.)
| | - Valentina Lanzani
- Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (STIIMA), Italian Council of National Research (CNR), 20133 Milan, Italy; (V.L.); (C.B.)
| | - Cristina Brambilla
- Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (STIIMA), Italian Council of National Research (CNR), 20133 Milan, Italy; (V.L.); (C.B.)
| | - Andrea d’Avella
- Laboratory of Neuromotor Physiology, IRCCS Fondazione Santa Lucia, Via Ardeatina 306-354, 00179 Rome, Italy;
- Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica, 00133 Rome, Italy
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Takiyama K, Kubota K, Yokoyama H, Kanemura N. Speed-dependent modulations of muscle modules in the gait of people with radiographical and asymptomatic knee osteoarthritis and elderly controls: Case-control pilot study. J Biomech 2024; 171:112194. [PMID: 38901294 DOI: 10.1016/j.jbiomech.2024.112194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 06/04/2024] [Accepted: 06/10/2024] [Indexed: 06/22/2024]
Abstract
This study investigates the muscle modules involved in the increase of walking speed in radiographical and asymptomatic knee osteoarthritis (KOA) patients using tensor decomposition. The human body possesses redundancy, which is the property to achieve desired movements with more degrees of freedom than necessary. The muscle module hypothesis is a proposed solution to this redundancy. While previous studies have examined the pathological muscle activity modulations in musculoskeletal diseases such as KOA, they have focused on single muscles rather than muscle modules. Moreover, most studies have only examined the gait of KOA patients at a single speed, leaving the way in which gait speed affects gait parameters in KOA patients unclear. Assessing this influence is crucial for determining appropriate gait speed and understanding why preferred gait speed decreases in KOA patients. In this study, we apply tensor decomposition to muscle activity data to extract muscle modules in KOA patients and elderly controls during walking at different speeds. We found a muscle module comprising hip adductors and back muscles that activate bimodally in a gait cycle, specific to KOA patients when they increase their walking speed. These findings may provide valuable insights for rehabilitation for KOA patients.
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Affiliation(s)
- Ken Takiyama
- Tokyo University of Agriculture and Technology, Department of Electrical Engineering and Computer Science, Nakacho, Koganei, Tokyo, Japan.
| | - Keisuke Kubota
- Research Development Center, Saitama Prefectural University, Saitama, Japan
| | - Hikaru Yokoyama
- Tokyo University of Agriculture and Technology, Division of Advanced Health Science, Nakacho, Koganei, Tokyo, Japan
| | - Naohiko Kanemura
- Graduate Course of Health and Social Services, Saitama Prefectural University, Saitama, Japan
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Huang S, Guo X, Xie JJ, Lau KYS, Liu R, Mak ADP, Cheung VCK, Chan RHM. Rectified Latent Variable Model-Based EMG Factorization of Inhibitory Muscle Synergy Components Related to Aging, Expertise and Force-Tempo Variations. SENSORS (BASEL, SWITZERLAND) 2024; 24:2820. [PMID: 38732926 PMCID: PMC11086352 DOI: 10.3390/s24092820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 04/12/2024] [Accepted: 04/20/2024] [Indexed: 05/13/2024]
Abstract
Muscle synergy has been widely acknowledged as a possible strategy of neuromotor control, but current research has ignored the potential inhibitory components in muscle synergies. Our study aims to identify and characterize the inhibitory components within motor modules derived from electromyography (EMG), investigate the impact of aging and motor expertise on these components, and better understand the nervous system's adaptions to varying task demands. We utilized a rectified latent variable model (RLVM) to factorize motor modules with inhibitory components from EMG signals recorded from ten expert pianists when they played scales and pieces at different tempo-force combinations. We found that older participants showed a higher proportion of inhibitory components compared with the younger group. Senior experts had a higher proportion of inhibitory components on the left hand, and most inhibitory components became less negative with increased tempo or decreased force. Our results demonstrated that the inhibitory components in muscle synergies could be shaped by aging and expertise, and also took part in motor control for adapting to different conditions in complex tasks.
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Affiliation(s)
- Subing Huang
- Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China; (S.H.); (X.G.); (R.L.)
| | - Xiaoyu Guo
- Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China; (S.H.); (X.G.); (R.L.)
| | - Jodie J. Xie
- School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, China; (J.J.X.); (K.Y.S.L.); (V.C.K.C.)
- Gerald Choa Neuroscience Institute, The Chinese University of Hong Kong, Hong Kong, China
| | - Kelvin Y. S. Lau
- School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, China; (J.J.X.); (K.Y.S.L.); (V.C.K.C.)
- Gerald Choa Neuroscience Institute, The Chinese University of Hong Kong, Hong Kong, China
| | - Richard Liu
- Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China; (S.H.); (X.G.); (R.L.)
| | - Arthur D. P. Mak
- Department of Psychiatry, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China;
- Cambridgeshire and Peterborough NHS Foundation Trust, Fulbourn Hospital, Cambridge CB21 5EF, UK
| | - Vincent C. K. Cheung
- School of Biomedical Sciences, The Chinese University of Hong Kong, Hong Kong, China; (J.J.X.); (K.Y.S.L.); (V.C.K.C.)
- Gerald Choa Neuroscience Institute, The Chinese University of Hong Kong, Hong Kong, China
| | - Rosa H. M. Chan
- Department of Electrical Engineering, City University of Hong Kong, Hong Kong, China; (S.H.); (X.G.); (R.L.)
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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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Ghislieri M, Lanotte M, Knaflitz M, Rizzi L, Agostini V. Muscle synergies in Parkinson's disease before and after the deep brain stimulation of the bilateral subthalamic nucleus. Sci Rep 2023; 13:6997. [PMID: 37117317 PMCID: PMC10147693 DOI: 10.1038/s41598-023-34151-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 04/25/2023] [Indexed: 04/30/2023] Open
Abstract
The aim of this study is to quantitatively assess motor control changes in Parkinson's disease (PD) patients after bilateral deep brain stimulation of the subthalamic nucleus (STN-DBS), based on a novel muscle synergy evaluation approach. A group of 20 PD patients evaluated at baseline (before surgery, T0), at 3 months (T1), and at 12 months (T2) after STN-DBS surgery, as well as a group of 20 age-matched healthy control subjects, underwent an instrumented gait analysis, including surface electromyography recordings from 12 muscles. A smaller number of muscle synergies was found in PD patients (4 muscle synergies, at each time point) compared to control subjects (5 muscle synergies). The neuromuscular robustness of PD patients-that at T0 was smaller with respect to controls (PD T0: 69.3 ± 2.2% vs. Controls: 77.6 ± 1.8%, p = 0.004)-increased at T1 (75.8 ± 1.8%), becoming not different from that of controls at T2 (77.5 ± 1.9%). The muscle synergies analysis may offer clinicians new knowledge on the neuromuscular structure underlying PD motor types of behavior and how they can improve after electroceutical STN-DBS therapy.
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Affiliation(s)
- Marco Ghislieri
- Department of Electronics and Telecommunications, Politecnico di Torino, 10129, Turin, Italy.
- PolitoBIOMed Lab, Politecnico di Torino, 10129, Turin, Italy.
| | - Michele Lanotte
- Department of Neuroscience "Rita Levi Montalcini", University of Turin, 10126, Turin, Italy
- AOU Città della Salute e della Scienza di Torino, 10126, Turin, Italy
| | - Marco Knaflitz
- Department of Electronics and Telecommunications, Politecnico di Torino, 10129, Turin, Italy
- PolitoBIOMed Lab, Politecnico di Torino, 10129, Turin, Italy
| | - Laura Rizzi
- Department of Neuroscience "Rita Levi Montalcini", University of Turin, 10126, Turin, Italy
- AOU Città della Salute e della Scienza di Torino, 10126, Turin, Italy
| | - Valentina Agostini
- Department of Electronics and Telecommunications, Politecnico di Torino, 10129, Turin, Italy
- PolitoBIOMed Lab, Politecnico di Torino, 10129, Turin, Italy
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Zielinska T, Coba G. The Measure of Motion Similarity for Robotics Application. SENSORS (BASEL, SWITZERLAND) 2023; 23:1643. [PMID: 36772683 PMCID: PMC9919200 DOI: 10.3390/s23031643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 01/22/2023] [Accepted: 01/31/2023] [Indexed: 06/18/2023]
Abstract
A new measure of motion similarity has been proposed. The formulation of this measure is presented and its logical basis is described. Unlike in most of other methods, the measure enables easy determination of the instantaneous synergies of the motion of body parts. To demonstrate how to use the measure, the data describing human movement is used. The movement is recorded using a professional motion capture system. Two different cases of non-periodic movements are discussed: stepping forward and backward, and returning to a stable posture after an unexpected thrust to the side (hands free or tied). This choice enables the identification of synergies in slow dynamics (stepping) and in fast dynamics (push recovery). The trajectories of motion similarity measures are obtained for point masses of the human body. The interpretation of these trajectories in relation to motion events is discussed. In addition, ordinary motion trajectories and footprints are shown in order to better illustrate the specificity of the discussed examples. The article ends with a discussion and conclusions.
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Affiliation(s)
- Teresa Zielinska
- Faculty of Power And Aeronautical Engineering, Warsaw University of Technology, 00-665 Warsaw, Poland
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Ferraris C, Ronga I, Pratola R, Coppo G, Bosso T, Falco S, Amprimo G, Pettiti G, Lo Priore S, Priano L, Mauro A, Desideri D. Usability of the REHOME Solution for the Telerehabilitation in Neurological Diseases: Preliminary Results on Motor and Cognitive Platforms. SENSORS (BASEL, SWITZERLAND) 2022; 22:9467. [PMID: 36502170 PMCID: PMC9740672 DOI: 10.3390/s22239467] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 11/30/2022] [Accepted: 12/01/2022] [Indexed: 06/17/2023]
Abstract
The progressive aging of the population and the consequent growth of individuals with neurological diseases and related chronic disabilities, will lead to a general increase in the costs and resources needed to ensure treatment and care services. In this scenario, telemedicine and e-health solutions, including remote monitoring and rehabilitation, are attracting increasing interest as tools to ensure the sustainability of the healthcare system or, at least, to support the burden for health care facilities. Technological advances in recent decades have fostered the development of dedicated and innovative Information and Communication Technology (ICT) based solutions, with the aim of complementing traditional care and treatment services through telemedicine applications that support new patient and disease management strategies. This is the background for the REHOME project, whose technological solution, presented in this paper, integrates innovative methodologies and devices for remote monitoring and rehabilitation of cognitive, motor, and sleep disorders associated with neurological diseases. One of the primary goals of the project is to meet the needs of patients and clinicians, by ensuring continuity of treatment from healthcare facilities to the patient's home. To this end, it is important to ensure the usability of the solution by elderly and pathological individuals. Preliminary results of usability and user experience questionnaires on 70 subjects recruited in three experimental trials are presented here.
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Affiliation(s)
- Claudia Ferraris
- Institute of Electronics, Computer and Telecommunication Engineering, National Research Council, 10129 Turin, Italy
| | - Irene Ronga
- BraIn Plasticity and Behaviour Changes Research Group, Department of Psychology, University of Turin, 10124 Turin, Italy
| | - Roberto Pratola
- Engineering Ingegneria Informatica S.p.A., 00144 Rome, Italy
| | - Guido Coppo
- Synarea Consultants s.r.l., 10153 Turin, Italy
| | - Tea Bosso
- BraIn Plasticity and Behaviour Changes Research Group, Department of Psychology, University of Turin, 10124 Turin, Italy
- Geriatrics Unit, Città della Salute e della Scienza Hospital, 10126 Turin, Italy
| | - Sara Falco
- BraIn Plasticity and Behaviour Changes Research Group, Department of Psychology, University of Turin, 10124 Turin, Italy
- Clinical Pyschology Unit, Città della Salute e della Scienza Hospital, 10126 Turin, Italy
| | - Gianluca Amprimo
- Institute of Electronics, Computer and Telecommunication Engineering, National Research Council, 10129 Turin, Italy
- Department of Control and Computer Engineering, Politecnico di Torino, 10129 Turin, Italy
| | - Giuseppe Pettiti
- Institute of Electronics, Computer and Telecommunication Engineering, National Research Council, 10129 Turin, Italy
| | | | - Lorenzo Priano
- Istituto Auxologico Italiano, IRCCS, Department of Neurology and Neurorehabilitation, S. Giuseppe Hospital, 20123 Milan, Italy
- Department of Neurosciences, University of Turin, 10126 Turin, Italy
| | - Alessandro Mauro
- Istituto Auxologico Italiano, IRCCS, Department of Neurology and Neurorehabilitation, S. Giuseppe Hospital, 20123 Milan, Italy
- Department of Neurosciences, University of Turin, 10126 Turin, Italy
| | - Debora Desideri
- Engineering Ingegneria Informatica S.p.A., 00144 Rome, Italy
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Wang R, An Q, Yang N, Kogami H, Yoshida K, Yamakawa H, Hamada H, Shimoda S, Yamasaki HR, Yokoyama M, Alnajjar F, Hattori N, Takahashi K, Fujii T, Otomune H, Miyai I, Yamashita A, Asama H. Clarify Sit-to-Stand Muscle Synergy and Tension Changes in Subacute Stroke Rehabilitation by Musculoskeletal Modeling. Front Syst Neurosci 2022; 16:785143. [PMID: 35359620 PMCID: PMC8963921 DOI: 10.3389/fnsys.2022.785143] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 02/15/2022] [Indexed: 12/01/2022] Open
Abstract
Post-stroke patients exhibit distinct muscle activation electromyography (EMG) features in sit-to-stand (STS) due to motor deficiency. Muscle activation amplitude, related to muscle tension and muscle synergy activation levels, is one of the defining EMG features that reflects post-stroke motor functioning and motor impairment. Although some qualitative findings are available, it is not clear if and how muscle activation amplitude-related biomechanical attributes may quantitatively reflect during subacute stroke rehabilitation. To better enable a longitudinal investigation into a patient's muscle activation changes during rehabilitation or an inter-subject comparison, EMG normalization is usually applied. However, current normalization methods using maximum voluntary contraction (MVC) or within-task peak/mean EMG may not be feasible when MVC cannot be obtained from stroke survivors due to motor paralysis and the subject of comparison is EMG amplitude. Here, focusing on the paretic side, we first propose a novel, joint torque-based normalization method that incorporates musculoskeletal modeling, forward dynamics simulation, and mathematical optimization. Next, upon method validation, we apply it to quantify changes in muscle tension and muscle synergy activation levels in STS motor control units for patients in subacute stroke rehabilitation. The novel method was validated against MVC-normalized EMG data from eight healthy participants, and it retained muscle activation amplitude differences for inter- and intra-subject comparisons. The proposed joint torque-based method was also compared with the common static optimization based on squared muscle activation and showed higher simulation accuracy overall. Serial STS measurements were conducted with four post-stroke patients during their subacute rehabilitation stay (137 ± 22 days) in the hospital. Quantitative results of patients suggest that maximum muscle tension and activation level of muscle synergy temporal patterns may reflect the effectiveness of subacute stroke rehabilitation. A quality comparison between muscle synergies computed with the conventional within-task peak/mean EMG normalization and our proposed method showed that the conventional was prone to activation amplitude overestimation and underestimation. The contributed method and findings help recapitulate and understand the post-stroke motor recovery process, which may facilitate developing more effective rehabilitation strategies for future stroke survivors.
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Affiliation(s)
- Ruoxi Wang
- Department of Precision Engineering, The University of Tokyo, Tokyo, Japan
| | - Qi An
- Department of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan
- *Correspondence: Qi An
| | | | - Hiroki Kogami
- Department of Precision Engineering, The University of Tokyo, Tokyo, Japan
| | - Kazunori Yoshida
- Department of Precision Engineering, The University of Tokyo, Tokyo, Japan
| | - Hiroshi Yamakawa
- Department of Precision Engineering, The University of Tokyo, Tokyo, Japan
| | - Hiroyuki Hamada
- Department of Precision Engineering, The University of Tokyo, Tokyo, Japan
| | | | - Hiroshi R. Yamasaki
- Department of Physical Therapy, Saitama Prefectural University, Saitama, Japan
| | | | - Fady Alnajjar
- RIKEN Center for Brain Science, Aichi, Japan
- College of Information Technology, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Noriaki Hattori
- Department of Rehabilitation, University of Toyama, Toyama, Japan
| | | | | | | | | | - Atsushi Yamashita
- Department of Precision Engineering, The University of Tokyo, Tokyo, Japan
| | - Hajime Asama
- Department of Precision Engineering, The University of Tokyo, Tokyo, Japan
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11
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Zampogna A, Mileti I, Martelli F, Paoloni M, Del Prete Z, Palermo E, Suppa A. Early balance impairment in Parkinson's Disease: Evidence from Robot-assisted axial rotations. Clin Neurophysiol 2021; 132:2422-2430. [PMID: 34454269 DOI: 10.1016/j.clinph.2021.06.023] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 05/27/2021] [Accepted: 06/06/2021] [Indexed: 12/20/2022]
Abstract
OBJECTIVE Early postural instability (PI) is a red flag for the diagnosis of Parkinson's disease (PD). Several patients, however, fall within the first three years of disease, particularly when turning. We investigated whether PD patients, without clinically overt PI, manifest abnormal reactive postural responses to ecological perturbations resembling turning. METHODS Fifteen healthy subjects and 20 patients without clinically overt PI, under and not under L-Dopa, underwent dynamic posturography during axial rotations around the longitudinal axis, provided by a robotic mechatronic platform. We measured reactive postural responses, including body displacement and reciprocal movements of the head, trunk, and pelvis, by using a network of three wearable inertial sensors. RESULTS Patients showed higher body displacement of the head, trunk and pelvis, and lower joint movements at the lumbo-sacral junction than controls. Conversely, movements at the cranio-cervical junction were normal in PD. L-Dopa left reactive postural responses unchanged. CONCLUSIONS Patients with PD without clinically overt PI manifest abnormal reactive postural responses to axial rotations, unresponsive to L-Dopa. The biomechanical model resulting from our experimental approach supports novel pathophysiological hypotheses of abnormal axial rotations in PD. SIGNIFICANCE PD patients without clinically overt PI present subclinical balance impairment during axial rotations, unresponsive to L-Dopa.
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Affiliation(s)
- Alessandro Zampogna
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | - Ilaria Mileti
- Mechanical Measurements and Microelectronics (M3Lab) Lab, Engineering Department, University Niccolò Cusano, 00166 Rome, Italy
| | - Francesca Martelli
- Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy
| | - Marco Paoloni
- Department of Physical Medicine and Rehabilitation, Sapienza University of Rome, 00161 Rome, Italy
| | - Zaccaria Del Prete
- Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy
| | - Eduardo Palermo
- Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy
| | - Antonio Suppa
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy; IRCCS Neuromed, 86077 Pozzilli, IS, Italy.
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12
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Bonnet CT, Delval A, Singh T, Defebvre L. Parkinson's disease-related changes in the behavioural synergy between eye movements and postural movements. Eur J Neurosci 2021; 54:5161-5172. [PMID: 34128272 DOI: 10.1111/ejn.15351] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 06/04/2021] [Accepted: 06/04/2021] [Indexed: 12/01/2022]
Abstract
Patients with Parkinson's disease (PD patients) have been shown to exhibit abnormally low levels of synergy in their posture control. The goal of this study was to determine how synergic interactions between vision and posture are affected in PD patients. These synergic interactions were expected to be impaired because PD affects the basal ganglia, which are involved in the modulation of both types of movement. Twenty patients (mean age: 60) on levodopa and 20 age-matched-controls (mean age: 61) performed a precise visual task (searching for targets in an image) and an unprecise control task (randomly looking at an image) in which images were projected onto a large panoramic display. Lower back, upper back, head and eye movements were recorded simultaneously. To test behavioural synergies, Pearson correlations between eye and postural movements were analysed. The relationships between eye movements and upper and lower back movements were impaired in the patients. The age-matched controls did not show any significant correlations between eye and postural movements. Overall, our results showed that the PD patients failed to adjust and control their postural stability for success in the visual task. The impaired synergy between eye and postural movements was not related to clinical variables-probably because our patients had early-stage PD. Our results showed that impairments in synergy can occur very early in PD. Hence, the analysis of this synergy might provide a better understanding of postural instability, visual task performance in the upright stance, and perhaps the risk of falls in PD patients.
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Affiliation(s)
- Cédrick T Bonnet
- Univ. Lille, CNRS, UMR 9193 - SCALab - Sciences Cognitives et Sciences Affectives, Lille, France
| | - Arnaud Delval
- Univ. Lille, Unité INSERM 1172, CHU Lille, Lille, France
| | - Tarkeshwar Singh
- Department of Kinesiology, The Pennsylvania State University, University Park, PA, USA
| | - Luc Defebvre
- Univ. Lille, Unité INSERM 1172, CHU Lille, Lille, France
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13
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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.
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14
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Laine CM, Cohn BA, Valero-Cuevas FJ. Temporal control of muscle synergies is linked with alpha-band neural drive. J Physiol 2021; 599:3385-3402. [PMID: 33963545 DOI: 10.1113/jp281232] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 04/21/2021] [Indexed: 12/19/2022] Open
Abstract
KEY POINTS It is theorized that the nervous system controls groups of muscles together as functional units, or 'synergies', resulting in correlated electromyographic (EMG) signals among muscles. However, such correlation does not necessarily imply group-level neural control. Oscillatory synchronization (coherence) among EMG signals implies neural coupling, but it is not clear how this relates to control of muscle synergies. EMG was recorded from seven arm muscles of 10 adult participants rotating an upper limb ergometer, and EMG-EMG coherence, EMG amplitude correlations and their relationship with each other were characterized. A novel method to derive multi-muscle synergies from EMG-EMG coherence is presented and these are compared with classically defined synergies. Coherent alpha-band (8-16 Hz) drive was strongest among muscles whose gross activity levels are well correlated within a given task. The cross-muscle distribution and temporal modulation of coherent alpha-band drive suggests a possible role in the neural coordination/monitoring of synergies. ABSTRACT During movement, groups of muscles may be controlled together by the nervous system as an adaptable functional entity, or 'synergy'. The rules governing when (or if) this occurs during voluntary behaviour in humans are not well understood, at least in part because synergies are usually defined by correlated patterns of muscle activity without regard for the underlying structure of their neural control. In this study, we investigated the extent to which comodulation of muscle output (i.e. correlation of electromyographic (EMG) amplitudes) implies that muscles share intermuscular neural input (assessed via EMG-EMG coherence analysis). We first examined this relationship among pairs of upper limb muscles engaged in an arm cycling task. We then applied a novel multidimensional EMG-EMG coherence analysis allowing synergies to be characterized on the basis of shared neural drive. We found that alpha-band coherence (8-16 Hz) is related to the degree to which overall muscle activity levels correlate over time. The extension of this coherence analysis to describe the cross-muscle distribution and temporal modulation of alpha-band drive revealed a close match to the temporal and structural features of traditionally defined muscle synergies. Interestingly, the coherence-derived neural drive was inversely associated with, and preceded, changes in EMG amplitudes by ∼200 ms. Our novel characterization of how alpha-band neural drive is dynamically distributed among muscles is a fundamental step forward in understanding the neural origins and correlates of muscle synergies.
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Affiliation(s)
- Christopher M Laine
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, USA
| | - Brian A Cohn
- Department of Computer Science, University of Southern California, Los Angeles, CA, USA
| | - Francisco J Valero-Cuevas
- Department of Computer Science, University of Southern California, Los Angeles, CA, USA.,Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA.,Division of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, CA, USA
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15
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Ballarini R, Ghislieri M, Knaflitz M, Agostini V. An Algorithm for Choosing the Optimal Number of Muscle Synergies during Walking. SENSORS 2021; 21:s21103311. [PMID: 34064615 PMCID: PMC8151057 DOI: 10.3390/s21103311] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 04/29/2021] [Accepted: 05/07/2021] [Indexed: 11/16/2022]
Abstract
In motor control studies, the 90% thresholding of variance accounted for (VAF) is the classical way of selecting the number of muscle synergies expressed during a motor task. However, the adoption of an arbitrary cut-off has evident drawbacks. The aim of this work is to describe and validate an algorithm for choosing the optimal number of muscle synergies (ChoOSyn), which can overcome the limitations of VAF-based methods. The proposed algorithm is built considering the following principles: (1) muscle synergies should be highly consistent during the various motor task epochs (i.e., remaining stable in time), (2) muscle synergies should constitute a base with low intra-level similarity (i.e., to obtain information-rich synergies, avoiding redundancy). The algorithm performances were evaluated against traditional approaches (threshold-VAF at 90% and 95%, elbow-VAF and plateau-VAF), using both a simulated dataset and a real dataset of 20 subjects. The performance evaluation was carried out by analyzing muscle synergies extracted from surface electromyographic (sEMG) signals collected during walking tasks lasting 5 min. On the simulated dataset, ChoOSyn showed comparable performances compared to VAF-based methods, while, in the real dataset, it clearly outperformed the other methods, in terms of the fraction of correct classifications, mean error (ME), and root mean square error (RMSE). The proposed approach may be beneficial to standardize the selection of the number of muscle synergies between different research laboratories, independent of arbitrary thresholds.
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Affiliation(s)
- Riccardo Ballarini
- Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy; (R.B.); (M.G.); (M.K.)
| | - Marco Ghislieri
- Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy; (R.B.); (M.G.); (M.K.)
- PoliToMed Lab, Politecnico di Torino, 10129 Turin, Italy
| | - Marco Knaflitz
- Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy; (R.B.); (M.G.); (M.K.)
- PoliToMed Lab, Politecnico di Torino, 10129 Turin, Italy
| | - Valentina Agostini
- Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy; (R.B.); (M.G.); (M.K.)
- PoliToMed Lab, Politecnico di Torino, 10129 Turin, Italy
- Correspondence: ; Tel.: +39-011-0904136
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16
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Estimation of Human Center of Mass Position through the Inertial Sensors-Based Methods in Postural Tasks: An Accuracy Evaluation. SENSORS 2021; 21:s21020601. [PMID: 33467072 PMCID: PMC7830449 DOI: 10.3390/s21020601] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 01/13/2021] [Accepted: 01/14/2021] [Indexed: 02/06/2023]
Abstract
The estimation of the body’s center of mass (CoM) trajectory is typically obtained using force platforms, or optoelectronic systems (OS), bounding the assessment inside a laboratory setting. The use of magneto-inertial measurement units (MIMUs) allows for more ecological evaluations, and previous studies proposed methods based on either a single sensor or a sensors’ network. In this study, we compared the accuracy of two methods based on MIMUs. Body CoM was estimated during six postural tasks performed by 15 healthy subjects, using data collected by a single sensor on the pelvis (Strapdown Integration Method, SDI), and seven sensors on the pelvis and lower limbs (Biomechanical Model, BM). The accuracy of the two methods was compared in terms of RMSE and estimation of posturographic parameters, using an OS as reference. The RMSE of the SDI was lower in tasks with little or no oscillations, while the BM outperformed in tasks with greater CoM displacement. Moreover, higher correlation coefficients were obtained between the posturographic parameters obtained with the BM and the OS. Our findings showed that the estimation of CoM displacement based on MIMU was reasonably accurate, and the use of the inertial sensors network methods should be preferred to estimate the kinematic parameters.
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17
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Relationship between Muscular Activity and Postural Control Changes after Proprioceptive Focal Stimulation (Equistasi ®) in Middle-Moderate Parkinson's Disease Patients: An Explorative Study. SENSORS 2021; 21:s21020560. [PMID: 33466838 PMCID: PMC7830724 DOI: 10.3390/s21020560] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Revised: 01/09/2021] [Accepted: 01/11/2021] [Indexed: 12/28/2022]
Abstract
The aim of this study was to investigate the effects of Equistasi®, a wearable device, on the relationship between muscular activity and postural control changes in a sample of 25 Parkinson’s disease (PD) subjects. Gait analysis was carried out through a six-cameras stereophotogrammetric system synchronized with two force plates, an eight-channel surface electromyographic system, recording the activity of four muscles bilaterally: Rectus femoris, tibialis anterior (TA), biceps femoris, and gastrocnemius lateralis (GL). The peak of the envelope (PoE) and its occurrence within the gait cycle (position of the peak of the envelope, PPoE) were calculated. Frequency-domain posturographic parameters were extracted while standing still on a force plate in eyes open and closed conditions for 60 s. After the treatment with Equistasi®, the mid-low (0.5–0.75) Hz and mid-high (0.75–1 Hz) components associated with the vestibular and somatosensory systems, PoE and PPoE, displayed a shift toward the values registered on the controls. Furthermore, a correlation was found between changes in proprioception (power spectrum frequencies during the Romberg Test) and the activity of GL, BF (PoE), and TA (PPoE). Results of this study could provide a quantitative estimation of the effects of a neurorehabilitation device on the peripheral and central nervous system in PD.
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18
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Agostini V, Ghislieri M, Rosati S, Balestra G, Knaflitz M. Surface Electromyography Applied to Gait Analysis: How to Improve Its Impact in Clinics? Front Neurol 2020; 11:994. [PMID: 33013656 PMCID: PMC7502709 DOI: 10.3389/fneur.2020.00994] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 07/29/2020] [Indexed: 12/22/2022] Open
Abstract
Surface electromyography (sEMG) is the main non-invasive tool used to record the electrical activity of muscles during dynamic tasks. In clinical gait analysis, a number of techniques have been developed to obtain and interpret the muscle activation patterns of patients showing altered locomotion. However, the body of knowledge described in these studies is very seldom translated into routine clinical practice. The aim of this work is to analyze critically the key factors limiting the extensive use of these powerful techniques among clinicians. A thorough understanding of these limiting factors will provide an important opportunity to overcome limitations through specific actions, and advance toward an evidence-based approach to rehabilitation based on objective findings and measurements.
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Affiliation(s)
- Valentina Agostini
- PoliToBIOMedLab, Politecnico di Torino, Turin, Italy.,Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy
| | - Marco Ghislieri
- PoliToBIOMedLab, Politecnico di Torino, Turin, Italy.,Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy
| | - Samanta Rosati
- PoliToBIOMedLab, Politecnico di Torino, Turin, Italy.,Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy
| | - Gabriella Balestra
- PoliToBIOMedLab, Politecnico di Torino, Turin, Italy.,Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy
| | - Marco Knaflitz
- PoliToBIOMedLab, Politecnico di Torino, Turin, Italy.,Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy
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