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Pollard RS, Bass SM, Schall MC, Zabala ME. Evaluating the Performance of Joint Angle Estimation Algorithms on an Exoskeleton Mock-Up via a Modular Testing Approach. SENSORS (BASEL, SWITZERLAND) 2024; 24:5673. [PMID: 39275584 PMCID: PMC11397979 DOI: 10.3390/s24175673] [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: 07/24/2024] [Revised: 08/28/2024] [Accepted: 08/29/2024] [Indexed: 09/16/2024]
Abstract
A common challenge for exoskeleton control is discerning operator intent to provide seamless actuation of the device with the operator. One way to accomplish this is with joint angle estimation algorithms and multiple sensors on the human-machine system. However, the question remains of what can be accomplished with just one sensor. The objective of this study was to deploy a modular testing approach to test the performance of two joint angle estimation models-a kinematic extrapolation algorithm and a Random Forest machine learning algorithm-when each was informed solely with kinematic gait data from a single potentiometer on an ankle exoskeleton mock-up. This study demonstrates (i) the feasibility of implementing a modular approach to exoskeleton mock-up evaluation to promote continuity between testing configurations and (ii) that a Random Forest algorithm yielded lower realized errors of estimated joint angles and a decreased actuation time than the kinematic model when deployed on the physical device.
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Affiliation(s)
- Ryan S Pollard
- Department of Mechanical Engineering, Auburn University, Auburn, AL 36849, USA
| | - Sarah M Bass
- Department of Mechanical Engineering, Auburn University, Auburn, AL 36849, USA
| | - Mark C Schall
- Department of Industrial and Systems Engineering, Auburn University, Auburn, AL 36849, USA
| | - Michael E Zabala
- Department of Mechanical Engineering, Auburn University, Auburn, AL 36849, USA
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2
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Dong R, Zhang X, Li H, Lu Z, Li C, Zhu A. Cross-domain prediction approach of human lower limb voluntary movement intention for exoskeleton robot based on EEG signals. Front Bioeng Biotechnol 2024; 12:1448903. [PMID: 39246298 PMCID: PMC11377221 DOI: 10.3389/fbioe.2024.1448903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Accepted: 07/29/2024] [Indexed: 09/10/2024] Open
Abstract
Background and Objective Exoskeleton robot control should ideally be based on human voluntary movement intention. The readiness potential (RP) component of the motion-related cortical potential is observed before movement in the electroencephalogram and can be used for intention prediction. However, its single-trial features are weak and highly variable, and existing methods cannot achieve high cross-temporal and cross-subject accuracies in practical online applications. Therefore, this work aimed to combine a deep convolutional neural network (CNN) framework with a transfer learning (TL) strategy to predict the lower limb voluntary movement intention, thereby improving the accuracy while enhancing the model generalization capability; this would also provide sufficient processing time for the response of the exoskeleton robotic system and help realize robot control based on the intention of the human body. Methods The signal characteristics of the RP for lower limb movement were analyzed, and a parameter TL strategy based on CNN was proposed to predict the intention of voluntary lower limb movements. We recruited 10 subjects for offline and online experiments. Multivariate empirical-mode decomposition was used to remove the artifacts, and the moment of onset of voluntary movement was labeled using lower limb electromyography signals during network training. Results The RP features can be observed from multiple data overlays before the onset of voluntary lower limb movements, and these features have long latency periods. The offline experimental results showed that the average movement intention prediction accuracy was 95.23% ± 1.25% for the right leg and 91.21% ± 1.48% for the left leg, which showed good cross-temporal and cross-subject generalization while greatly reducing the training time. Online movement intention prediction can predict results about 483.9 ± 11.9 ms before movement onset with an average accuracy of 82.75%. Conclusion The proposed method has a higher prediction accuracy with a lower training time, has good generalization performance for cross-temporal and cross-subject aspects, and is well-prioritized in terms of the temporal responses; these features are expected to lay the foundation for further investigations on exoskeleton robot control.
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Affiliation(s)
- Runlin Dong
- School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Xiaodong Zhang
- School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
- Shaanxi Key Laboratory of Intelligent Robots, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Hanzhe Li
- School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Zhufeng Lu
- School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Cunxin Li
- School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Aibin Zhu
- School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
- Shaanxi Key Laboratory of Intelligent Robots, Xi'an Jiaotong University, Xi'an, Shaanxi, China
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3
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Schirinzi E, Bochicchio MA, Lochmüller H, Vissing J, Jordie-Diaz-Manerae, Evangelista T, Plançon JP, Fanucci L, Marini M, Tonacci A, Mancuso M, Segovia-Kueny S, Toscano A, Angelini C, Schoser B, Sacconi S, Siciliano G. E-Health & Innovation to Overcome Barriers in Neuromuscular Diseases. Report from the 3rd eNMD Congress: Pisa, Italy, 29-30 October 2021. J Neuromuscul Dis 2024:JND230091. [PMID: 38728200 DOI: 10.3233/jnd-230091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2024]
Abstract
Neuromuscular diseases (NMDs), in their phenotypic heterogeneity, share quite invariably common issues that involve several clinical and socio-economical aspects, needing a deep critical analysis to develop better management strategies. From diagnosis to treatment and follow-up, the development of technological solutions can improve the detection of several critical aspects related to the diseases, addressing both the met and unmet needs of clinicians and patients. Among several aspects of the digital transformation of health and care, this congress expands what has been learned from previous congresses editions on applicability and usefulness of technological solutions in NMDs. In particular the focus on new solutions for remote monitoring provide valuable insights to increase disease-specific knowledge and trigger prompt decision-making. In doing that, several perspectives from different areas of expertise were shared and discussed, pointing out strengths and weaknesses on the current state of the art on topic, suggesting new research lines to advance technology in this specific clinical field.
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Affiliation(s)
- Erika Schirinzi
- Department of Clinical and Experimental Medicine, Neurological Clinic, University of Pisa, Pisa, Italy
| | | | - Hanns Lochmüller
- Department of Medicine, Children's Hospital of Eastern Ontario Research Institute, Division of Neurology, The Ottawa Hospital, and Brain and Mind Research Institute, University of Ottawa, Ottawa, Canada
| | - John Vissing
- Copenhagen Neuromuscular Center, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Jordie-Diaz-Manerae
- The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
- Neurology Department, Neuromuscular Disorders Unit, Hospital de la Santa Creu I Sant Pau, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Raras (CIBERER), Madrid, Spain
| | - Teresinha Evangelista
- AP-HP, H. Pitié-Salpêtrière, Institut de Myologie, Unité de Morphologie Neuromusculaire, Paris, France
- AP-HP, H. Pitié-Salpêtrière, Centre de référence des maladies neuromusculaires Nord/Est/Ile de France, Paris, France
- Sorbonne Université, INSERM, Institut de Myologie, Centre de Recherche en Myologie, France
| | - Jean-Philippe Plançon
- European Patient Organisation for Dysimmune and Inflammatory Neuropathies (EPODIN) and EURO-NMD Educational board, Paris, France
| | - Luca Fanucci
- Department of Information Engineering, University of Pisa, Pisa, Italy
| | - Marco Marini
- Department of Information Engineering, University of Pisa, Pisa, Italy
| | - Alessandro Tonacci
- Institute of Clinical Physiology, National Research Council - CNR, Pisa, Italy
| | - Michelangelo Mancuso
- Department of Clinical and Experimental Medicine, Neurological Clinic, University of Pisa, Pisa, Italy
| | | | - Antonio Toscano
- Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy
| | - Corrado Angelini
- Department Neurosciences, Padova University School of Medicine, Padova, Italy
| | - Benedikt Schoser
- Department of Neurology, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Sabrina Sacconi
- Peripheral Nervous System and Muscle Department, Université Cúte d'Azur (UCA), Centre Hospitalier Universitaire de Nice, Rare Neuromuscular Disease Reference Center, ERN-Euro-NMD, Nice, France
| | - Gabriele Siciliano
- Department of Clinical and Experimental Medicine, Neurological Clinic, University of Pisa, Pisa, Italy
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Sosa Méndez D, García Cena CE, Bedolla-Martínez D, Martín González A. Innovative Metaheuristic Optimization Approach with a Bi-Triad for Rehabilitation Exoskeletons. SENSORS (BASEL, SWITZERLAND) 2024; 24:2231. [PMID: 38610443 PMCID: PMC11014224 DOI: 10.3390/s24072231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 02/23/2024] [Accepted: 03/25/2024] [Indexed: 04/14/2024]
Abstract
The present work proposes a comprehensive metaheuristic methodology for the development of a medical robot for the upper limb rehabilitation, which includes the topological optimization of the device, kinematic models (5 DOF), human-robot interface, control and experimental tests. This methodology applies two cutting-edge triads: (1) the three points of view in engineering design (client, designer and community) and (2) the triad formed by three pillars of Industry 4.0 (autonomous machines and systems, additive manufacturing and simulation of virtual environments). By applying the proposed procedure, a robotic mechanism was obtained with a reduction of more than 40% of its initial weight and a human-robot interface with three modes of operation and a biomechanically viable kinematic model for humans. The digital twin instance and its evaluation through therapeutic routines with and without disturbances was assessed; the average RMSEs obtained were 0.08 rad and 0.11 rad, respectively. The proposed methodology is applicable to any medical robot, providing a versatile and effective solution for optimizing the design and development of healthcare devices. It adopts an innovative and scalable approach to enhance their processes.
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Affiliation(s)
- Deira Sosa Méndez
- Escuela Técnica Superior de Ingeniería y Diseño Industrial, Center for Automation and Robotics, UPM-CSIC, Universidad Politécnica de Madrid, Ronda de Valencia, 3, 28012 Madrid, Spain;
| | - Cecilia E. García Cena
- Escuela Técnica Superior de Ingeniería y Diseño Industrial, Center for Automation and Robotics, UPM-CSIC, Universidad Politécnica de Madrid, Ronda de Valencia, 3, 28012 Madrid, Spain;
| | - David Bedolla-Martínez
- Electrical Engineering, École de Technologie Supérieure, 1100 Notre-Dame St. W, Montreal, QC H3C 1K3, Canada;
| | - Antonio Martín González
- Unidad de Tecnologías Avanzadas en Diseño e Impresión 3D, Hospital Universitario 12 de Octubre, Av. de Córdoba, s/n, 28041 Madrid, Spain;
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5
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Pană CF, Popescu D, Rădulescu VM. Patent Review of Lower Limb Rehabilitation Robotic Systems by Sensors and Actuation Systems Used. SENSORS (BASEL, SWITZERLAND) 2023; 23:6237. [PMID: 37448084 PMCID: PMC10346545 DOI: 10.3390/s23136237] [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: 06/07/2023] [Revised: 06/24/2023] [Accepted: 06/27/2023] [Indexed: 07/15/2023]
Abstract
Robotic systems for lower limb rehabilitation are essential for improving patients' physical conditions in lower limb rehabilitation and assisting patients with various locomotor dysfunctions. These robotic systems mainly integrate sensors, actuation, and control systems and combine features from bionics, robotics, control, medicine, and other interdisciplinary fields. Several lower limb robotic systems have been proposed in the patent literature; some are commercially available. This review is an in-depth study of the patents related to robotic rehabilitation systems for lower limbs from the point of view of the sensors and actuation systems used. The patents awarded and published between 2013 and 2023 were investigated, and the temporal distribution of these patents is presented. Our results were obtained by examining the analyzed information from the three public patent databases. The patents were selected so that there were no duplicates after several filters were used in this review. For each patent database, the patents were analyzed according to the category of sensors and the number of sensors used. Additionally, for the main categories of sensors, an analysis was conducted depending on the type of sensors used. Afterwards, the actuation solutions for robotic rehabilitation systems for upper limbs described in the patents were analyzed, highlighting the main trends in their use. The results are presented with a schematic approach so that any user can easily find patents that use a specific type of sensor or a particular type of actuation system, and the sensors or actuation systems recommended to be used in some instances are highlighted.
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Affiliation(s)
- Cristina Floriana Pană
- Department of Mechatronics and Robotics, University of Craiova, 200440 Craiova, Romania;
| | - Dorin Popescu
- Department of Mechatronics and Robotics, University of Craiova, 200440 Craiova, Romania;
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6
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Su D, Hu Z, Wu J, Shang P, Luo Z. Review of adaptive control for stroke lower limb exoskeleton rehabilitation robot based on motion intention recognition. Front Neurorobot 2023; 17:1186175. [PMID: 37465413 PMCID: PMC10350518 DOI: 10.3389/fnbot.2023.1186175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 06/13/2023] [Indexed: 07/20/2023] Open
Abstract
Stroke is a significant cause of disability worldwide, and stroke survivors often experience severe motor impairments. Lower limb rehabilitation exoskeleton robots provide support and balance for stroke survivors and assist them in performing rehabilitation training tasks, which can effectively improve their quality of life during the later stages of stroke recovery. Lower limb rehabilitation exoskeleton robots have become a hot topic in rehabilitation therapy research. This review introduces traditional rehabilitation assessment methods, explores the possibility of lower limb exoskeleton robots combining sensors and electrophysiological signals to assess stroke survivors' rehabilitation objectively, summarizes standard human-robot coupling models of lower limb rehabilitation exoskeleton robots in recent years, and critically introduces adaptive control models based on motion intent recognition for lower limb exoskeleton robots. This provides new design ideas for the future combination of lower limb rehabilitation exoskeleton robots with rehabilitation assessment, motion assistance, rehabilitation treatment, and adaptive control, making the rehabilitation assessment process more objective and addressing the shortage of rehabilitation therapists to some extent. Finally, the article discusses the current limitations of adaptive control of lower limb rehabilitation exoskeleton robots for stroke survivors and proposes new research directions.
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Affiliation(s)
- Dongnan Su
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Zhigang Hu
- School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China
- Henan Intelligent Rehabilitation Medical Robot Engineering Research Center, Henan University of Science and Technology, Luoyang, China
| | - Jipeng Wu
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Peng Shang
- Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Zhaohui Luo
- State-Owned Changhong Machinery Factory, Guilin, China
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7
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Hsain Z, Akbari M, Prasanna A, Jiang Z, Akbarzadeh M, Pikul JH. Electrochemical Healing of Fractured Metals. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2211242. [PMID: 36933269 DOI: 10.1002/adma.202211242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 03/10/2023] [Indexed: 06/16/2023]
Abstract
Repairing fractured metals to extend their useful lifetimes advances sustainability and mitigates carbon emissions from metal mining and processing. While high-temperature techniques are being used to repair metals, the increasing ubiquity of digital manufacturing and "unweldable" alloys, as well as the integration of metals with polymers and electronics, call for radically different repair approaches. Herein, a framework for effective room-temperature repair of fractured metals using an area-selective nickel electrodeposition process refered to as electrochemical healing is presented. Based on a model that links geometric, mechanical, and electrochemical parameters to the recovery of tensile strength, this framework enables 100% recovery of tensile strength in nickel, low-carbon steel, two "unweldable" aluminum alloys, and a 3D-printed difficult-to-weld shellular structure using a single common electrolyte. Through a distinct energy-dissipation mechanism, this framework also enables up to 136% recovery of toughness in an aluminum alloy. To facilitate practical adoption, this work reveals scaling laws for the energetic, financial, and time costs of healing, and demonstrates the restoration of a functional level of strength in a fractured standard steel wrench. Empowered with this framework, room-temperature electrochemical healing can open exciting possibilities for the effective, scalable repair of metals in diverse applications.
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Affiliation(s)
- Zakaria Hsain
- Department of Mechanical Engineering and Applied Mechanics, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
| | - Mostafa Akbari
- Department of Architecture, Weitzman School of Design, University of Pennsylvania, Philadelphia, PA, USA
| | - Adhokshid Prasanna
- Department of Mechanical Engineering and Applied Mechanics, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
| | - Zhimin Jiang
- Department of Mechanical Engineering and Applied Mechanics, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
| | - Masoud Akbarzadeh
- Department of Architecture, Weitzman School of Design, University of Pennsylvania, Philadelphia, PA, USA
| | - James H Pikul
- Department of Mechanical Engineering and Applied Mechanics, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
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8
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Lee YH, Ko LW, Hsu CY, Cheng YY. Therapeutic Effects of Robotic-Exoskeleton-Assisted Gait Rehabilitation and Predictive Factors of Significant Improvements in Stroke Patients: A Randomized Controlled Trial. Bioengineering (Basel) 2023; 10:bioengineering10050585. [PMID: 37237654 DOI: 10.3390/bioengineering10050585] [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: 04/24/2023] [Revised: 05/06/2023] [Accepted: 05/10/2023] [Indexed: 05/28/2023] Open
Abstract
Robotic-exoskeleton-assisted gait rehabilitation improves lower limb strength and functions in post-stroke patients. However, the predicting factors of significant improvement are unclear. We recruited 38 post-stroke hemiparetic patients whose stroke onsets were <6 months. They were randomly assigned to two groups: a control group receiving a regular rehabilitation program, and an experimental group receiving in addition a robotic exoskeletal rehabilitation component. After 4 weeks of training, both groups showed significant improvement in the strength and functions of their lower limbs, as well as health-related quality of life. However, the experimental group showed significantly better improvement in the following aspects: knee flexion torque at 60°/s, 6 min walk test distance, and the mental subdomain and the total score on a 12-item Short Form Survey (SF-12). Further logistic regression analyses showed that robotic training was the best predictor of a greater improvement in both the 6 min walk test and the total score on the SF-12. In conclusion, robotic-exoskeleton-assisted gait rehabilitation improved lower limb strength, motor performance, walking speed, and quality of life in these stroke patients.
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Affiliation(s)
- Yi-Heng Lee
- Department of Physical Medicine and Rehabilitation, Taichung Veterans General Hospital, Taichung City 40705, Taiwan
| | - Li-Wei Ko
- Department of Electronics and Electrical Engineering, Institute of Electrical and Control Engineering, Center for Intelligent Drug Systems and Smart Bio-devices (IDS2B) in College of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
| | - Chiann-Yi Hsu
- Biostatistics Task Force, Taichung Veterans General Hospital, Taichung City 40705, Taiwan
| | - Yuan-Yang Cheng
- Department of Physical Medicine and Rehabilitation, Taichung Veterans General Hospital, Taichung City 40705, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei 11221, Taiwan
- Intelligent Long Term Medical Care Research Center, Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung City 40227, Taiwan
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9
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Imani B, Najafi F. Dynamic analysis and control of a hybrid lower limb rehabilitation robot to reduce human-robot interaction forces. Proc Inst Mech Eng H 2023; 237:336-347. [PMID: 36727965 DOI: 10.1177/09544119221146243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
This study presents a model of cooperation between two planar manipulators including an orthosis and a programmable plate in form of a hybrid lower limb rehabilitation robot, which was designed and built at the University of Guilan. The aims of cooperation are to distribute the power required to move between the cooperative manipulators and also reduce the interaction forces between orthosis and leg. The cooperation is performed with two modes using the adjustment of the plate forces, a constant force in the vertical direction (CFV) and variant force proportional to orthosis torque (VFPOT). Kinematic and dynamic analysis of the hybrid lower limb rehabilitation robot and its control are also discussed in this study. The performance and effectiveness of the proposed hybrid robot are demonstrated on a healthy person in real-time. Each walking trial lasted 60 s and repeated 20 times for every mode. The walking speed was considered to be 1.5 km/h and weight compensator was adjusted with a constant weight unloading level of 70%. The results show that the VFPOT mode leads to a 45% reduction in the driving torque of the hip and knee joints compared to orthosis-only. This reduction is expected to reduce interaction force at the connection straps. So, it provides more patient comfort and safety, which can be effective in improving the time and process of rehabilitation.
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Affiliation(s)
- Babak Imani
- Faculty of Mechanical Engineering, University of Guilan, Rasht, Guilan, Iran
| | - Farid Najafi
- Faculty of Mechanical Engineering, University of Guilan, Rasht, Guilan, Iran
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10
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Neťuková S, Bejtic M, Malá C, Horáková L, Kutílek P, Kauler J, Krupička R. Lower Limb Exoskeleton Sensors: State-of-the-Art. SENSORS (BASEL, SWITZERLAND) 2022; 22:9091. [PMID: 36501804 PMCID: PMC9738474 DOI: 10.3390/s22239091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 11/08/2022] [Accepted: 11/17/2022] [Indexed: 06/17/2023]
Abstract
Due to the ever-increasing proportion of older people in the total population and the growing awareness of the importance of protecting workers against physical overload during long-time hard work, the idea of supporting exoskeletons progressed from high-tech fiction to almost commercialized products within the last six decades. Sensors, as part of the perception layer, play a crucial role in enhancing the functionality of exoskeletons by providing as accurate real-time data as possible to generate reliable input data for the control layer. The result of the processed sensor data is the information about current limb position, movement intension, and needed support. With the help of this review article, we want to clarify which criteria for sensors used in exoskeletons are important and how standard sensor types, such as kinematic and kinetic sensors, are used in lower limb exoskeletons. We also want to outline the possibilities and limitations of special medical signal sensors detecting, e.g., brain or muscle signals to improve data perception at the human-machine interface. A topic-based literature and product research was done to gain the best possible overview of the newest developments, research results, and products in the field. The paper provides an extensive overview of sensor criteria that need to be considered for the use of sensors in exoskeletons, as well as a collection of sensors and their placement used in current exoskeleton products. Additionally, the article points out several types of sensors detecting physiological or environmental signals that might be beneficial for future exoskeleton developments.
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Liang J, Zhang Q, Liu Y, Wang T, Wan G. A review of the design of load-carrying exoskeletons. SCIENCE CHINA. TECHNOLOGICAL SCIENCES 2022; 65:2051-2067. [PMID: 36032505 PMCID: PMC9392988 DOI: 10.1007/s11431-022-2145-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 07/07/2022] [Indexed: 06/15/2023]
Abstract
The increasing necessity of load-carrying activities has led to greater human musculoskeletal damage and an increased metabolic cost. With the rise of exoskeleton technology, researchers have begun exploring different approaches to developing wearable robots to augment human load-carrying ability. However, there is a lack of systematic discussion on biomechanics, mechanical designs, and augmentation performance. To achieve this, extensive studies have been reviewed and 108 references are selected mainly from 2013 to 2022 to address the most recent development. Other earlier 20 studies are selected to present the origin of different design principles. In terms of the way to achieve load-carrying augmentation, the exoskeletons reviewed in this paper are sorted by four categories based on the design principles, namely load-suspended backpacks, lower-limb exoskeletons providing joint torques, exoskeletons transferring load to the ground and exoskeletons transferring load between body segments. Specifically, the driving modes of active and passive, the structure of rigid and flexible, the conflict between assistive performance and the mass penalty of the exoskeleton, and the autonomy are discussed in detail in each section to illustrate the advances, challenges, and future trends of exoskeletons designed to carry loads.
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Affiliation(s)
- JieJunYi Liang
- State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074 China
| | - QinHao Zhang
- State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074 China
| | - Yang Liu
- State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074 China
| | - Tao Wang
- State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074 China
| | - GuangFu Wan
- State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, 430074 China
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12
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Electrically Driven Lower Limb Exoskeleton Rehabilitation Robot Based on Anthropomorphic Design. MACHINES 2022. [DOI: 10.3390/machines10040266] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
To help people with impairment of lower extremity movement regain the ability to stand and walk, and to enhance limb function, this study proposes an anthropomorphic design of an electrically driven, lower-limb exoskeleton rehabilitation robot. The angular range of the robot’s motion was determined according to the characteristics of the targeted lower-limb joints; the robot was given an active–passive anthropomorphic design with 12 degrees of freedom. The multi-degree-of-freedom hip exoskeleton, bionic artificial knee exoskeleton and passive rigid-flexible coupling ankle exoskeleton can assist patients in rehabilitation exercises with better wear comfort and exercise flexibility. A kinetic model of the seven-rod lower-limb exoskeleton rehabilitation robot was built, and data analysis of the dynamically captured motion trajectory was conducted. These provided a theoretical basis for gait planning and the control system of the lower-limb exoskeleton rehabilitation robot. The results show that the lower-limb exoskeleton rehabilitation robot system possesses sound wearing comfort and movement flexibility, and the degree of freedom of movement of the exoskeleton robot matches well with that of human movement. The robot can thus provide effective assistance to patients’ standing and walking rehabilitation training.
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Wang Z, Yang C, Ding Z, Yang T, Guo H, Jiang F, Tian B. Study on the Control Method of Knee Joint Human-Exoskeleton Interactive System. SENSORS 2022; 22:s22031040. [PMID: 35161792 PMCID: PMC8839318 DOI: 10.3390/s22031040] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 01/25/2022] [Accepted: 01/27/2022] [Indexed: 02/04/2023]
Abstract
The advantages of exoskeletons based on the Bowden cable include being lightweight and flexible, thus being convenient in assisting humans. However, the performance of an exoskeleton is limited by the structure and human–exoskeleton interaction, which is analyzed from the established mathematical model of the human–exoskeleton system. In order to improve the auxiliary accuracy, corresponding control methods are proposed. The disturbance observer is designed to compensate for disturbances and parameter perturbations in the inner loop. The human–exoskeleton interaction feedforward model is integrated into the admittance control, which overcomes the limitation of the force loading caused by the friction of the Bowden cable and the change in stiffness of the human–exoskeleton interaction. Furthermore, an angle prediction method using the encoder as the signal source is designed to reduce the disturbance of the force loading caused by human motion. Finally, the effectiveness of the design method proposed in this paper is verified through experiments.
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Affiliation(s)
- Zhipeng Wang
- School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China; (Z.W.); (C.Y.); (Z.D.); (T.Y.)
| | - Chifu Yang
- School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China; (Z.W.); (C.Y.); (Z.D.); (T.Y.)
| | - Zhen Ding
- School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China; (Z.W.); (C.Y.); (Z.D.); (T.Y.)
| | - Tao Yang
- School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China; (Z.W.); (C.Y.); (Z.D.); (T.Y.)
| | - Hao Guo
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China;
| | - Feng Jiang
- School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China;
- Correspondence:
| | - Bowen Tian
- School of Business Administration, Zhongnan University of Economics and Law, Wuhan 430000, China;
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14
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A Review on the Rehabilitation Exoskeletons for the Lower Limbs of the Elderly and the Disabled. ELECTRONICS 2022. [DOI: 10.3390/electronics11030388] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Research on the lower limb exoskeleton for rehabilitation have developed rapidly to meet the need of the aging population. The rehabilitation exoskeleton system is a wearable man–machine integrated mechanical device. In recent years, the vigorous development of exoskeletal technology has brought new ideas to the rehabilitation and medical treatment of patients with motion dysfunction, which is expected to help such people complete their daily physiological activities or even reshape their motion function. The rehabilitation exoskeletons conduct assistance based on detecting intention, control algorithm, and high-performance actuators. In this paper, we review rehabilitation exoskeletons from the aspects of the overall design, driving unit, intention perception, compliant control, and efficiency validation. We discussed the complexity and coupling of the man–machine integration system, and we hope to provide a guideline when designing a rehabilitation exoskeleton system for the lower limbs of elderly and disabled patients.
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15
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Tiboni M, Borboni A, Vérité F, Bregoli C, Amici C. Sensors and Actuation Technologies in Exoskeletons: A Review. SENSORS (BASEL, SWITZERLAND) 2022; 22:884. [PMID: 35161629 PMCID: PMC8839165 DOI: 10.3390/s22030884] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 01/16/2022] [Accepted: 01/19/2022] [Indexed: 02/06/2023]
Abstract
Exoskeletons are robots that closely interact with humans and that are increasingly used for different purposes, such as rehabilitation, assistance in the activities of daily living (ADLs), performance augmentation or as haptic devices. In the last few decades, the research activity on these robots has grown exponentially, and sensors and actuation technologies are two fundamental research themes for their development. In this review, an in-depth study of the works related to exoskeletons and specifically to these two main aspects is carried out. A preliminary phase investigates the temporal distribution of scientific publications to capture the interest in studying and developing novel ideas, methods or solutions for exoskeleton design, actuation and sensors. The distribution of the works is also analyzed with respect to the device purpose, body part to which the device is dedicated, operation mode and design methods. Subsequently, actuation and sensing solutions for the exoskeletons described by the studies in literature are analyzed in detail, highlighting the main trends in their development and spread. The results are presented with a schematic approach, and cross analyses among taxonomies are also proposed to emphasize emerging peculiarities.
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Affiliation(s)
- Monica Tiboni
- Department of Mechanical and Industrial Engineering, University of Brescia, Via Branze, 38, 25123 Brescia, Italy; (M.T.); (C.A.)
| | - Alberto Borboni
- Department of Mechanical and Industrial Engineering, University of Brescia, Via Branze, 38, 25123 Brescia, Italy; (M.T.); (C.A.)
| | - Fabien Vérité
- Agathe Group INSERM U 1150, UMR 7222 CNRS, ISIR (Institute of Intelligent Systems and Robotics), Sorbonne Université, 75005 Paris, France;
| | - Chiara Bregoli
- Institute of Condensed Matter Chemistry and Technologies for Energy (ICMATE), National Research Council (CNR), Via Previati 1/E, 23900 Lecco, Italy;
| | - Cinzia Amici
- Department of Mechanical and Industrial Engineering, University of Brescia, Via Branze, 38, 25123 Brescia, Italy; (M.T.); (C.A.)
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