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Yassin MM, Saad MN, Khalifa AM, Said AM. Advancing clinical understanding of surface electromyography biofeedback: bridging research, teaching, and commercial applications. Expert Rev Med Devices 2024. [PMID: 38967375 DOI: 10.1080/17434440.2024.2376699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2024] [Accepted: 07/02/2024] [Indexed: 07/06/2024]
Abstract
INTRODUCTION Expanding the use of surface electromyography-biofeedback (EMG-BF) devices in different therapeutic settings highlights the gradually evolving role of visualizing muscle activity in the rehabilitation process. This review evaluates their concepts, uses, and trends, combining evidence-based research. AREAS COVERED This review dissects the anatomy of EMG-BF systems, emphasizing their transformative integration with machine-learning (ML) and deep-learning (DL) paradigms. Advances such as the application of sophisticated DL architectures for high-density EMG data interpretation, optimization techniques for heightened DL model performance, and the fusion of EMG with electroencephalogram (EEG) signals have been spotlighted for enhancing biomechanical analyses in rehabilitation. The literature survey also categorizes EMG-BF devices based on functionality and clinical usage, supported by insights from commercial sectors. EXPERT OPINION The current landscape of EMG-BF is rapidly evolving, chiefly propelled by innovations in artificial intelligence (AI). The incorporation of ML and DL into EMG-BF systems augments their accuracy, reliability, and scope, marking a leap in patient care. Despite challenges in model interpretability and signal noise, ongoing research promises to address these complexities, refining biofeedback modalities. The integration of AI not only predicts patient-specific recovery timelines but also tailors therapeutic interventions, heralding a new era of personalized medicine in rehabilitation and emotional detection.
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Affiliation(s)
- Mazen M Yassin
- Shcool of Biomedical Engineering, Shenzhen University, Shenzhen, China
- Biomedical Engineering Department, Minia University, Minia, Egypt
- Department of Biomedical Engineering, Helwan University, Cairo, Egypt
| | - Mohamed N Saad
- Shcool of Biomedical Engineering, Shenzhen University, Shenzhen, China
| | - Ayman M Khalifa
- Biomedical Engineering Department, Minia University, Minia, Egypt
| | - Ashraf M Said
- Biomedical Engineering Department, Benha University, Al Qalyubiyah, Egypt
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Lee DH, Woo BS, Park YH, Lee JH. General Treatments Promoting Independent Living in Parkinson's Patients and Physical Therapy Approaches for Improving Gait-A Comprehensive Review. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:711. [PMID: 38792894 PMCID: PMC11123276 DOI: 10.3390/medicina60050711] [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: 03/28/2024] [Revised: 04/18/2024] [Accepted: 04/24/2024] [Indexed: 05/26/2024]
Abstract
This study delves into the multifaceted approaches to treating Parkinson's disease (PD), a neurodegenerative disorder primarily affecting motor function but also manifesting in a variety of symptoms that vary greatly among individuals. The complexity of PD symptoms necessitates a comprehensive treatment strategy that integrates surgical interventions, pharmacotherapy, and physical therapy to tailor to the unique needs of each patient. Surgical options, such as deep brain stimulation (DBS), have been pivotal for patients not responding adequately to medication, offering significant symptom relief. Pharmacotherapy remains a cornerstone of PD management, utilizing drugs like levodopa, dopamine agonists, and others to manage symptoms and, in some cases, slow down disease progression. However, these treatments often lead to complications over time, such as motor fluctuations and dyskinesias, highlighting the need for precise dosage adjustments and sometimes combination therapies to optimize patient outcomes. Physical therapy plays a critical role in addressing the motor symptoms of PD, including bradykinesia, muscle rigidity, tremors, postural instability, and akinesia. PT techniques are tailored to improve mobility, balance, strength, and overall quality of life. Strategies such as gait and balance training, strengthening exercises, stretching, and functional training are employed to mitigate symptoms and enhance functional independence. Specialized approaches like proprioceptive neuromuscular facilitation (PNF), the Bobath concept, and the use of assistive devices are also integral to the rehabilitation process, aimed at improving patients' ability to perform daily activities and reducing the risk of falls. Innovations in technology have introduced robotic-assisted gait training (RAGT) and other assistive devices, offering new possibilities for patient care. These tools provide targeted support and feedback, allowing for more intensive and personalized rehabilitation sessions. Despite these advancements, high costs and accessibility issues remain challenges that need addressing. The inclusion of exercise and activity beyond structured PT sessions is encouraged, with evidence suggesting that regular physical activity can have neuroprotective effects, potentially slowing disease progression. Activities such as treadmill walking, cycling, and aquatic exercises not only improve physical symptoms but also contribute to emotional well-being and social interactions. In conclusion, treating PD requires a holistic approach that combines medical, surgical, and therapeutic strategies. While there is no cure, the goal is to maximize patients' functional abilities and quality of life through personalized treatment plans. This integrated approach, along with ongoing research and development of new therapies, offers hope for improving the management of PD and the lives of those affected by this challenging disease.
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Affiliation(s)
- Dae-Hwan Lee
- IM Rehabilitation Hospital, 2140, Cheongnam-ro, Seowon-gu, Cheongju-si 28702, Chungcheongbuk-do, Republic of Korea; (D.-H.L.); (B.-S.W.); (Y.-H.P.)
| | - Bong-Sik Woo
- IM Rehabilitation Hospital, 2140, Cheongnam-ro, Seowon-gu, Cheongju-si 28702, Chungcheongbuk-do, Republic of Korea; (D.-H.L.); (B.-S.W.); (Y.-H.P.)
| | - Yong-Hwa Park
- IM Rehabilitation Hospital, 2140, Cheongnam-ro, Seowon-gu, Cheongju-si 28702, Chungcheongbuk-do, Republic of Korea; (D.-H.L.); (B.-S.W.); (Y.-H.P.)
| | - Jung-Ho Lee
- Department of Physical Therapy, University of Kyungdong, 815, Gyeonhwon-ro, Munmak-eup, Wonju-si 26495, Gangwon-do, Republic of Korea
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Lorenz EA, Su X, Skjæret-Maroni N. A review of combined functional neuroimaging and motion capture for motor rehabilitation. J Neuroeng Rehabil 2024; 21:3. [PMID: 38172799 PMCID: PMC10765727 DOI: 10.1186/s12984-023-01294-6] [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: 06/23/2023] [Accepted: 12/11/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Technological advancements in functional neuroimaging and motion capture have led to the development of novel methods that facilitate the diagnosis and rehabilitation of motor deficits. These advancements allow for the synchronous acquisition and analysis of complex signal streams of neurophysiological data (e.g., EEG, fNIRS) and behavioral data (e.g., motion capture). The fusion of those data streams has the potential to provide new insights into cortical mechanisms during movement, guide the development of rehabilitation practices, and become a tool for assessment and therapy in neurorehabilitation. RESEARCH OBJECTIVE This paper aims to review the existing literature on the combined use of motion capture and functional neuroimaging in motor rehabilitation. The objective is to understand the diversity and maturity of technological solutions employed and explore the clinical advantages of this multimodal approach. METHODS This paper reviews literature related to the combined use of functional neuroimaging and motion capture for motor rehabilitation following the PRISMA guidelines. Besides study and participant characteristics, technological aspects of the used systems, signal processing methods, and the nature of multimodal feature synchronization and fusion were extracted. RESULTS Out of 908 publications, 19 were included in the final review. Basic or translation studies were mainly represented and based predominantly on healthy participants or stroke patients. EEG and mechanical motion capture technologies were most used for biomechanical data acquisition, and their subsequent processing is based mainly on traditional methods. The system synchronization techniques at large were underreported. The fusion of multimodal features mainly supported the identification of movement-related cortical activity, and statistical methods were occasionally employed to examine cortico-kinematic relationships. CONCLUSION The fusion of motion capture and functional neuroimaging might offer advantages for motor rehabilitation in the future. Besides facilitating the assessment of cognitive processes in real-world settings, it could also improve rehabilitative devices' usability in clinical environments. Further, by better understanding cortico-peripheral coupling, new neuro-rehabilitation methods can be developed, such as personalized proprioceptive training. However, further research is needed to advance our knowledge of cortical-peripheral coupling, evaluate the validity and reliability of multimodal parameters, and enhance user-friendly technologies for clinical adaptation.
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Affiliation(s)
- Emanuel A Lorenz
- Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway.
| | - Xiaomeng Su
- Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Nina Skjæret-Maroni
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
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Scano A, Guanziroli E, Brambilla C, Amendola C, Pirovano I, Gasperini G, Molteni F, Spinelli L, Molinari Tosatti L, Rizzo G, Re R, Mastropietro A. A Narrative Review on Multi-Domain Instrumental Approaches to Evaluate Neuromotor Function in Rehabilitation. Healthcare (Basel) 2023; 11:2282. [PMID: 37628480 PMCID: PMC10454517 DOI: 10.3390/healthcare11162282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 08/02/2023] [Accepted: 08/10/2023] [Indexed: 08/27/2023] Open
Abstract
In clinical scenarios, the use of biomedical sensors, devices and multi-parameter assessments is fundamental to provide a comprehensive portrait of patients' state, in order to adapt and personalize rehabilitation interventions and support clinical decision-making. However, there is a huge gap between the potential of the multidomain techniques available and the limited practical use that is made in the clinical scenario. This paper reviews the current state-of-the-art and provides insights into future directions of multi-domain instrumental approaches in the clinical assessment of patients involved in neuromotor rehabilitation. We also summarize the main achievements and challenges of using multi-domain approaches in the assessment of rehabilitation for various neurological disorders affecting motor functions. Our results showed that multi-domain approaches combine information and measurements from different tools and biological signals, such as kinematics, electromyography (EMG), electroencephalography (EEG), near-infrared spectroscopy (NIRS), and clinical scales, to provide a comprehensive and objective evaluation of patients' state and recovery. This multi-domain approach permits the progress of research in clinical and rehabilitative practice and the understanding of the pathophysiological changes occurring during and after rehabilitation. We discuss the potential benefits and limitations of multi-domain approaches for clinical decision-making, personalized therapy, and prognosis. We conclude by highlighting the need for more standardized methods, validation studies, and the integration of multi-domain approaches in clinical practice and research.
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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), Via A. Corti 12, 20133 Milan, Italy; (C.B.); (L.M.T.)
| | - Eleonora Guanziroli
- Villa Beretta Rehabilitation Center, Via N. Sauro 17, 23845 Costa Masnaga, Italy; (E.G.); (G.G.); (F.M.)
| | - Cristina Brambilla
- Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (STIIMA), Italian Council of National Research (CNR), Via A. Corti 12, 20133 Milan, Italy; (C.B.); (L.M.T.)
| | - Caterina Amendola
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy; (C.A.); (R.R.)
| | - Ileana Pirovano
- Institute of Biomedical Technologies (ITB), Italian National Research Council (CNR), Via Fratelli Cervi 93, 20054 Segrate, Italy; (I.P.); (G.R.); (A.M.)
| | - Giulio Gasperini
- Villa Beretta Rehabilitation Center, Via N. Sauro 17, 23845 Costa Masnaga, Italy; (E.G.); (G.G.); (F.M.)
| | - Franco Molteni
- Villa Beretta Rehabilitation Center, Via N. Sauro 17, 23845 Costa Masnaga, Italy; (E.G.); (G.G.); (F.M.)
| | - Lorenzo Spinelli
- Institute for Photonics and Nanotechnology (IFN), Italian National Research Council (CNR), Piazza Leonardo da Vinci 32, 20133 Milan, Italy;
| | - Lorenzo Molinari Tosatti
- Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (STIIMA), Italian Council of National Research (CNR), Via A. Corti 12, 20133 Milan, Italy; (C.B.); (L.M.T.)
| | - Giovanna Rizzo
- Institute of Biomedical Technologies (ITB), Italian National Research Council (CNR), Via Fratelli Cervi 93, 20054 Segrate, Italy; (I.P.); (G.R.); (A.M.)
| | - Rebecca Re
- Dipartimento di Fisica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy; (C.A.); (R.R.)
- Institute for Photonics and Nanotechnology (IFN), Italian National Research Council (CNR), Piazza Leonardo da Vinci 32, 20133 Milan, Italy;
| | - Alfonso Mastropietro
- Institute of Biomedical Technologies (ITB), Italian National Research Council (CNR), Via Fratelli Cervi 93, 20054 Segrate, Italy; (I.P.); (G.R.); (A.M.)
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Mastropietro A, Rivolta MW, Scano A. Biomedical Sensors for Functional Mapping: Techniques, Methods, Experimental and Medical Applications. SENSORS (BASEL, SWITZERLAND) 2023; 23:7063. [PMID: 37631600 PMCID: PMC10458848 DOI: 10.3390/s23167063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 08/07/2023] [Indexed: 08/27/2023]
Abstract
The rapid advancement of biomedical sensor technology has revolutionized the field of functional mapping in medicine, offering novel and powerful tools for diagnosis, clinical assessment, and rehabilitation [...].
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Affiliation(s)
- Alfonso Mastropietro
- Istituto di Tecnologie Biomediche, Consiglio Nazionale delle Ricerche, 20054 Segrate, Italy
| | | | - Alessandro Scano
- Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato, Consiglio Nazionale delle Ricerche, 20133 Milan, Italy;
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Garro F, Fenoglio E, Forsiuk I, Canepa M, Mozzon M, De Michieli L, Buccelli S, Chiappalone M, Semprini M. NeBULA: A Standardized Protocol for the Benchmarking of Robotic-based Upper Limb Neurorehabilitation. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083145 DOI: 10.1109/embc40787.2023.10340242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
The use of robotic technologies in neurorehabilitation is growing, because they allow highly repeatable exercise protocols and patient-tailored therapies. However, there is a lack of objective methods for assessing these technologies, which makes it difficult to determine their value in rehabilitation settings. While there exist many outcome measurements for motor assessment from a clinical standpoint (such as the Fugl-Meyer scale), the evaluation of performance and clinical benefits of technology for rehabilitation still lacks a standardized approach from a technical standpoint.In this work, we describe NeBULA (Neuromechanical Biomarkers for Upper Limb Assessment), a benchmarking platform for evaluating robotic technology for upper limb neurorehabilitation. By utilizing standardized neuromechanical biomarkers, NeBULA aims at providing a groundwork for assessing and comparing neurorehabilitation robots. We describe its implementation and preliminary results assessing a novel upper limb exoskeleton.Clinical Relevance- Standardized evaluation of neurorehabilitation robots can lead to better patient outcomes, optimizing resources by identifying the most effective technology and by boosting their use in clinical practice. This would provide quantitative and objective information to complement clinical motor evaluation - preventing suboptimal treatments and ensuring that patients receive personalized care. It can also facilitate the transfer of technologyto clinics, identifying the most promising ones for further investment and research.
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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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Brambilla C, Lavit Nicora M, Storm F, Reni G, Malosio M, Scano A. Biomechanical Assessments of the Upper Limb for Determining Fatigue, Strain and Effort from the Laboratory to the Industrial Working Place: A Systematic Review. Bioengineering (Basel) 2023; 10:bioengineering10040445. [PMID: 37106632 PMCID: PMC10135542 DOI: 10.3390/bioengineering10040445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 03/24/2023] [Accepted: 04/03/2023] [Indexed: 04/08/2023] Open
Abstract
Recent human-centered developments in the industrial field (Industry 5.0) lead companies and stakeholders to ensure the wellbeing of their workers with assessments of upper limb performance in the workplace, with the aim of reducing work-related diseases and improving awareness of the physical status of workers, by assessing motor performance, fatigue, strain and effort. Such approaches are usually developed in laboratories and only at times they are translated to on-field applications; few studies summarized common practices for the assessments. Therefore, our aim is to review the current state-of-the-art approaches used for the assessment of fatigue, strain and effort in working scenarios and to analyze in detail the differences between studies that take place in the laboratory and in the workplace, in order to give insights on future trends and directions. A systematic review of the studies aimed at evaluating the motor performance, fatigue, strain and effort of the upper limb targeting working scenarios is presented. A total of 1375 articles were found in scientific databases and 288 were analyzed. About half of the scientific articles are focused on laboratory pilot studies investigating effort and fatigue in laboratories, while the other half are set in working places. Our results showed that assessing upper limb biomechanics is quite common in the field, but it is mostly performed with instrumental assessments in laboratory studies, while questionnaires and scales are preferred in working places. Future directions may be oriented towards multi-domain approaches able to exploit the potential of combined analyses, exploitation of instrumental approaches in workplace, targeting a wider range of people and implementing more structured trials to translate pilot studies to real practice.
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Affiliation(s)
- Cristina Brambilla
- Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato (STIIMA), Consiglio Nazionale delle Ricerche (CNR), Via Previati 1/E, 23900 Lecco, Italy
| | - Matteo Lavit Nicora
- Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato (STIIMA), Consiglio Nazionale delle Ricerche (CNR), Via Previati 1/E, 23900 Lecco, Italy
- Industrial Engineering Department, University of Bologna, 40126 Bologna, Italy
| | - Fabio Storm
- Bioengineering Laboratory, Scientific Institute, IRCCS “Eugenio Medea”, 23842 Bosisio Parini, Italy
| | - Gianluigi Reni
- Informatics Department, Autonomous Province of Bolzano, 39100 Bolzano, Italy
| | - Matteo Malosio
- Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato (STIIMA), Consiglio Nazionale delle Ricerche (CNR), Via Previati 1/E, 23900 Lecco, Italy
| | - Alessandro Scano
- Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato (STIIMA), Consiglio Nazionale delle Ricerche (CNR), Via Previati 1/E, 23900 Lecco, Italy
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Xu J, Xu L, Ji A, Cao K. Learning robotic motion with mirror therapy framework for hemiparesis rehabilitation. Inf Process Manag 2023. [DOI: 10.1016/j.ipm.2022.103244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
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Merletti R, Temporiti F, Gatti R, Gupta S, Sandrini G, Serrao M. Translation of surface electromyography to clinical and motor rehabilitation applications: The need for new clinical figures. Transl Neurosci 2023; 14:20220279. [PMID: 36941919 PMCID: PMC10024349 DOI: 10.1515/tnsci-2022-0279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 02/19/2023] [Accepted: 02/20/2023] [Indexed: 03/16/2023] Open
Abstract
Advanced sensors/electrodes and signal processing techniques provide powerful tools to analyze surface electromyographic signals (sEMG) and their features, to decompose sEMG into the constituent motor unit action potential trains, and to identify synergies, neural muscle drive, and EEG-sEMG coherence. However, despite thousands of articles, dozens of textbooks, tutorials, consensus papers, and European and International efforts, the translation of this knowledge into clinical activities and assessment procedures has been very slow, likely because of lack of clinical studies and competent operators in the field. Understanding and using sEMG-based hardware and software tools requires a level of knowledge of signal processing and interpretation concepts that is multidisciplinary and is not provided by most academic curricula in physiotherapy, movement sciences, neurophysiology, rehabilitation, sport, and occupational medicine. The chasm existing between the available knowledge and its clinical applications in this field is discussed as well as the need for new clinical figures. The need for updating the training of physiotherapists, neurophysiology technicians, and clinical technologists is discussed as well as the required competences of trainers and trainees. Indications and examples are suggested and provide a basis for addressing the problem. Two teaching examples are provided in the Supplementary Material.
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Affiliation(s)
- Roberto Merletti
- LISiN, Department of Electronics andTelecommunications, Politecnico di Torino, Torino, 10138, Italy
| | - Federico Temporiti
- Physiotherapy Unit, Humanitas Clinical and Research Center - IRCCS, Rozzano, Milano, 20089, Italy
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milano, 20090, Italy
| | - Roberto Gatti
- Physiotherapy Unit, Humanitas Clinical and Research Center - IRCCS, Rozzano, Milano, 20089, Italy
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milano, 20090, Italy
| | - Sanjeev Gupta
- Faculty of Allied Health Sciences, Manav Rachna International Institute of Research and Studies, Faridabad, Haryana, 121004, India
| | - Giorgio Sandrini
- Department of Brain and Behavior Sciences, University of Pavia, Pavia, 27100, Italy
| | - Mariano Serrao
- Department of Medical and Surgical Sciences and Biotechnologies, Sapienza University of Rome, Latina, 04100, Italy
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Jang Y, Moon JH, Lee C, Lee SM, Kim H, Song GH, Spinks GM, Wallace GG, Kim SJ. A Coiled Carbon Nanotube Yarn-Integrated Surface Electromyography System To Monitor Isotonic and Isometric Movements. ACS APPLIED MATERIALS & INTERFACES 2022; 14:45149-45155. [PMID: 36169191 DOI: 10.1021/acsami.2c11811] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
A surface electromyogram (sEMG) electrode collects electrical currents generated by neuromuscular activity by a noninvasive technique on the skin. It is particularly attractive for wearable systems for various human activities and health care monitoring. However, it remains challenging to discriminate EMG signals from isotonic (concentric/eccentric) and isometric movements. By applying nanotechnology, we provide a coiled carbon nanotube (CNT) yarn-integrated sEMG device to overcome sEMG-based motion recognition. When the arm was contracted at different angles, the sEMG-derived root mean square amplitude signals were constant regardless of the angle of the moving arm. However, the coiled CNT yarn-derived open circuit voltage (OCV) signals proportionally increased when the arm's angle increased, and presented negative and positive values depending on the moving direction of the arm. Moreover, isometric contraction is characterized by the onset of EMG signals without an OCV signal, and isotonic contraction is determined by both EMG signals and OCV signals. Taken together, the integration of EMG and coiled CNT yarn electrodes provides complementary information, including the strength, direction, and degree of muscle movement. Therefore, we suggest that our system has high potential as a wearable system to monitor human motions in industrial and human system applications.
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Affiliation(s)
- Yongwoo Jang
- Center for Self-Powered Actuation, Department of Biomedical Engineering, Hanyang University, Seoul 04763, South Korea
- Department of Pharmacology, College of Medicine, Hanyang University, Seoul 04736, Korea
| | - Ji Hwan Moon
- Center for Self-Powered Actuation, Department of Electronic Engineering, Hanyang University, Seoul 04763, South Korea
| | - Chanho Lee
- Center for Self-Powered Actuation, Department of Biomedical Engineering, Hanyang University, Seoul 04763, South Korea
| | - Sung Min Lee
- Center for Self-Powered Actuation, Department of Biomedical Engineering, Hanyang University, Seoul 04763, South Korea
| | - Heesoo Kim
- Center for Self-Powered Actuation, Department of Biomedical Engineering, Hanyang University, Seoul 04763, South Korea
| | - Gyu Hyeon Song
- Center for Self-Powered Actuation, Department of Electronic Engineering, Hanyang University, Seoul 04763, South Korea
| | - Geoffrey M Spinks
- Intelligent Polymer Research Institute, ARC Centre of Excellence for Electro Materials Science, AIIM Facility, Innovation Campus, University of Wollongong, North Wollongong, NSW 2522, Australia
| | - Gordon G Wallace
- Intelligent Polymer Research Institute, ARC Centre of Excellence for Electro Materials Science, AIIM Facility, Innovation Campus, University of Wollongong, North Wollongong, NSW 2522, Australia
| | - Seon Jeong Kim
- Center for Self-Powered Actuation, Department of Biomedical Engineering, Hanyang University, Seoul 04763, South Korea
- Center for Self-Powered Actuation, Department of Electronic Engineering, Hanyang University, Seoul 04763, South Korea
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Automatic Assessment of Abdominal Exercises for the Treatment of Diastasis Recti Abdominis Using Electromyography and Machine Learning. Symmetry (Basel) 2022. [DOI: 10.3390/sym14081654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Diastasis Recti Abdominis (DRA) is a medical condition in which the two sides of the rectus abdominis muscle are separated by at least 2.7 cm. This happens when the collagen sheath that exists between the rectus muscles stretches beyond a certain limit. The recti muscles generally separate and move apart in pregnant women due to the development of fetus in the womb. In some cases, this intramuscular gap will not be closed on its own, leading to DRA. The primary treatment procedures of DRA involve different therapeutic exercises to reduce the inter-recti distance. However, it is tedious for the physiotherapists to constantly monitor the patients and ensure that the exercises are being done correctly. The objective of this research is to analyze the correctness of such performed exercises using electromyogram (EMG) signals and machine learning. To the best of our knowledge, this is the first work reporting the objective evaluation of rehabilitation exercises for DRA. Experimental studies indicate that the surface EMG signals were effective in classifying the correctly and incorrectly performed movements. An extensive analysis was carried out with different machine learning models for classification. It was inferred that the RUSBoosted Ensembled classifier was effective in differentiating these movements with an accuracy of 92.3%.
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13
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Virtual/Augmented Reality for Rehabilitation Applications Using Electromyography as Control/Biofeedback: Systematic Literature Review. ELECTRONICS 2022. [DOI: 10.3390/electronics11142271] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Virtual reality (VR) and augmented reality (AR) are engaging interfaces that can be of benefit for rehabilitation therapy. However, they are still not widely used, and the use of surface electromyography (sEMG) signals is not established for them. Our goal is to explore whether there is a standardized protocol towards therapeutic applications since there are not many methodological reviews that focus on sEMG control/feedback. A systematic literature review using the PRISMA (preferred reporting items for systematic reviews and meta-analyses) methodology is conducted. A Boolean search in databases was performed applying inclusion/exclusion criteria; articles older than 5 years and repeated were excluded. A total of 393 articles were selected for screening, of which 66.15% were excluded, 131 records were eligible, 69.46% use neither VR/AR interfaces nor sEMG control; 40 articles remained. Categories are, application: neurological motor rehabilitation (70%), prosthesis training (30%); processing algorithm: artificial intelligence (40%), direct control (20%); hardware: Myo Armband (22.5%), Delsys (10%), proprietary (17.5%); VR/AR interface: training scene model (25%), videogame (47.5%), first-person (20%). Finally, applications are focused on motor neurorehabilitation after stroke/amputation; however, there is no consensus regarding signal processing or classification criteria. Future work should deal with proposing guidelines to standardize these technologies for their adoption in clinical practice.
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Validation of Continuous Monitoring System for Epileptic Users in Outpatient Settings. SENSORS 2022; 22:s22082900. [PMID: 35458883 PMCID: PMC9025176 DOI: 10.3390/s22082900] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 03/30/2022] [Accepted: 04/06/2022] [Indexed: 12/24/2022]
Abstract
Epilepsy is a chronic disease with a significant social impact, given that the patients and their families often live conditioned by the possibility of an epileptic seizure and its possible consequences, such as accidents, injuries, or even sudden unexplained death. In this context, ambulatory monitoring allows the collection of biomedical data about the patients’ health, thus gaining more knowledge about the physiological state and daily activities of each patient in a more personalized manner. For this reason, this article proposes a novel monitoring system composed of different sensors capable of synchronously recording electrocardiogram (ECG), photoplethysmogram (PPG), and ear electroencephalogram (EEG) signals and storing them for further processing and analysis in a microSD card. This system can be used in a static and/or ambulatory way, providing information about the health state through features extracted from the ear EEG signal and the calculation of the heart rate variability (HRV) and pulse travel time (PTT). The different applied processing techniques to improve the quality of these signals are described in this work. A novel algorithm used to compute HRV and PTT robustly and accurately in ambulatory settings is also described. The developed device has also been validated and compared with other commercial systems obtaining similar results. In this way, based on the quality of the obtained signals and the low variability of the computed parameters, even in ambulatory conditions, the developed device can potentially serve as a support tool for clinical decision-taking stages.
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Scano A, Mira RM, Gabbrielli G, Molteni F, Terekhov V. Whole-Body Adaptive Functional Electrical Stimulation Kinesitherapy Can Promote the Restoring of Physiological Muscle Synergies for Neurological Patients. SENSORS 2022; 22:s22041443. [PMID: 35214345 PMCID: PMC8877830 DOI: 10.3390/s22041443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 01/28/2022] [Accepted: 02/11/2022] [Indexed: 12/03/2022]
Abstract
Background: Neurological diseases and traumas are major factors that may reduce motor functionality. Functional electrical stimulation is a technique that helps regain motor function, assisting patients in daily life activities and in rehabilitation practices. In this study, we evaluated the efficacy of a treatment based on whole-body Adaptive Functional Electrical Stimulation Kinesitherapy (AFESK™) with the use of muscle synergies, a well-established method for evaluation of motor coordination. The evaluation is performed on retrospectively gathered data of neurological patients executing whole-body movements before and after AFESK-based treatments. Methods: Twenty-four chronic neurologic patients and 9 healthy subjects were recruited in this study. The patient group was further subdivided in 3 subgroups: hemiplegic, tetraplegic and paraplegic. All patients underwent two acquisition sessions: before treatment and after a FES based rehabilitation treatment at the VIKTOR Physio Lab. Patients followed whole-body exercise protocols tailored to their needs. The control group of healthy subjects performed all movements in a single session and provided reference data for evaluating patients’ performance. sEMG was recorded on relevant muscles and muscle synergies were extracted for each patient’s EMG data and then compared to the ones extracted from the healthy volunteers. To evaluate the effect of the treatment, the motricity index was measured and patients’ extracted synergies were compared to the control group before and after treatment. Results: After the treatment, patients’ motricity index increased for many of the screened body segments. Muscle synergies were more similar to those of healthy people. Globally, the normalized synergy similarity in respect to the control group was 0.50 before the treatment and 0.60 after (p < 0.001), with improvements for each subgroup of patients. Conclusions: AFESK treatment induced favorable changes in muscle activation patterns in chronic neurologic patients, partially restoring muscular patterns similar to healthy people. The evaluation of the synergic relationships of muscle activity when performing test exercises allows to assess the results of rehabilitation measures in patients with impaired locomotor functions.
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Affiliation(s)
- Alessandro Scano
- UOS STIIMA Lecco—Human-Centered, Smart & Safe, Living Environment, Italian National Research Council (CNR), Via Previati 1/E, 23900 Lecco, Italy;
- Correspondence: (A.S.); (V.T.)
| | - Robert Mihai Mira
- UOS STIIMA Lecco—Human-Centered, Smart & Safe, Living Environment, Italian National Research Council (CNR), Via Previati 1/E, 23900 Lecco, Italy;
| | | | - Franco Molteni
- Villa Beretta Rehabilitation Center, Ospedale Valduce, Via N. Sauro 17, 23845 Costa Masnaga, Italy;
| | - Viktor Terekhov
- VIKTOR S.r.l.—Via Pasubio, 5, 24044 Dalmine (BG), Italy;
- Correspondence: (A.S.); (V.T.)
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