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Armand S, Sawacha Z, Goudriaan M, Horsak B, van der Krogt M, Huenaerts C, Daly C, Kranzl A, Boehm H, Petrarca M, Guiotto A, Merlo A, Spolaor F, Campanini I, Cosma M, Hallemans A, Horemans H, Gasq D, Moissenet F, Assi A, Sangeux M. Current practices in clinical gait analysis in Europe: A comprehensive survey-based study from the European society for movement analysis in adults and children (ESMAC) standard initiative. Gait Posture 2024; 111:65-74. [PMID: 38653178 DOI: 10.1016/j.gaitpost.2024.04.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 04/09/2024] [Accepted: 04/11/2024] [Indexed: 04/25/2024]
Abstract
BACKGROUND Clinical gait analysis (CGA) is a systematic approach to comprehensively evaluate gait patterns, quantify impairments, plan targeted interventions, and evaluate the impact of interventions. However, international standards for CGA are currently lacking, resulting in various national initiatives. Standards are important to ensure safe and effective healthcare practices and to enable evidence-based clinical decision-making, facilitating interoperability, and reimbursement under national healthcare policies. Collaborative clinical and research work between European countries would benefit from common standards. RESEARCH OBJECTIVE This study aimed to review the current laboratory practices for CGA in Europe. METHODS A comprehensive survey was conducted by the European Society for Movement Analysis in Adults and Children (ESMAC), in close collaboration with the European national societies. The survey involved 97 gait laboratories across 16 countries. The survey assessed several aspects related to CGA, including equipment used, data collection, processing, and reporting methods. RESULTS There was a consensus between laboratories concerning the data collected during CGA. The Conventional Gait Model (CGM) was the most used biomechanical model for calculating kinematics and kinetics. Respondents also reported the use of video recording, 3D motion capture systems, force plates, and surface electromyography. While there was a consensus on the reporting of CGA data, variations were reported in training, documentation, data preprocessing and equipment maintenance practices. SIGNIFICANCE The findings of this study will serve as a foundation for the development of standardized guidelines for CGA in Europe.
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Affiliation(s)
- Stéphane Armand
- Kinesiology Laboratory, Geneva University Hospitals and University of Geneva, Geneva, Switzerland.
| | - Zimi Sawacha
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Marije Goudriaan
- Utrecht University, University Corporate Offices, Student and Academic Affairs Office, Utrecht, the Netherlands; Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Rehabilitation Medicine, Amsterdam, the Netherlands
| | - Brian Horsak
- Center for Digital Health and Social Innovation, St. Pölten University of Applied Sciences, St. Pölten, Austria
| | - Marjolein van der Krogt
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Rehabilitation Medicine, Amsterdam, the Netherlands; Amsterdam Movement Sciences, Rehabilitation & Development, Amsterdam, the Netherlands
| | - Catherine Huenaerts
- Clinical Motion Analysis Laboratory, University Hospital Leuven, Leuven, Belgium
| | - Colm Daly
- National Centre for Movement Analysis, Central Remedial Clinic, Dublin, Ireland; CP-Life Research Centre, Royal College of Surgeons, Dublin, Ireland
| | - Andreas Kranzl
- Laboratory for Gait and Movement Analysis, Orthopaedic Hospital Speising, Vienna, Austria
| | - Harald Boehm
- Orthopaedic Hospital for Children, Aschau im Chiemgau, Germany
| | - Maurizio Petrarca
- Movement Analysis and Robotics Laboratory, "Bambino Gesù" Children's Hospital - IRCCS, Rome, Italy
| | - Anna Guiotto
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Andrea Merlo
- Gait & Motion Analysis Laboratory, Sol et Salus Hospital, Rimini, Italy; LAM - Motion Analysis Laboratory, Neuromotor and Rehabilitation Department, Azienda USL-IRCCS di Reggio Emilia, San Sebastiano Hospital, Correggio, Italy
| | - Fabiola Spolaor
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Isabella Campanini
- LAM - Motion Analysis Laboratory, Neuromotor and Rehabilitation Department, Azienda USL-IRCCS di Reggio Emilia, San Sebastiano Hospital, Correggio, Italy
| | - Michela Cosma
- Motion Analysis Laboratory, Neuroscience and Rehabilitation Department, University Hospital of Ferrara, Italy
| | - Ann Hallemans
- Research Group MOVANT, Department of Rehabilitation Sciences and Physiotherapy (REVAKI), University of Antwerp, Wilrijk, Belgium
| | - Herwin Horemans
- Department of Rehabilitation, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - David Gasq
- Department of Functional Physiological Explorations, University Hospital of Toulouse, Hôpital de Rangueil, Toulouse, France; ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, Université Paul Sabatier, Toulouse, France
| | - Florent Moissenet
- Kinesiology Laboratory, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Ayman Assi
- Faculty of Medicine, Saint Joseph University of Beirut, Beirut, Lebanon
| | - Morgan Sangeux
- University Children's Hospital Basel, Basel, Switzerland
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El Fezazi M, Achmamad A, Jbari A, Jilbab A. A convenient approach for knee kinematics assessment using wearable inertial sensors during home-based rehabilitation: Validation with an optoelectronic system. SCIENTIFIC AFRICAN 2023; 20:e01676. [PMID: 37122479 PMCID: PMC10122771 DOI: 10.1016/j.sciaf.2023.e01676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 02/23/2023] [Accepted: 04/22/2023] [Indexed: 05/02/2023] Open
Abstract
Rehabilitation services are among the most severely impacted by the COVID-19 pandemic. This has increased the number of people not receiving the needed rehabilitation care. Home-based rehabilitation becomes alternative support to face this greater need. However, monitoring kinematics parameters during rehabilitation exercises is critical for an effective recovery. This work proposes a detailed framework to estimate knee kinematics using a wearable Magnetic and Inertial Measurement Unit (MIMU). That allows at-home monitoring for knee rehabilitation progress. Two MIMU sensors were attached to the shank and thigh segments respectively. First, the absolute orientation of each sensor was estimated using a sensor fusion algorithm. Second, these sensor orientations were transformed to segments orientations using a functional sensor-to-segment (STS) alignment. Third, the relative orientation between segments, i.e., knee joint angle, was computed and the relevant kinematics parameters were extracted. Then, the validity of our approach was evaluated with a gold-standard optoelectronic system. Seven participants completed three to five Timed-Up-and-Go (TUG) tests. The estimated knee angle was compared to the reference angle. Root-mean-square error (RMSE), correlation coefficient, and Bland-Altman analysis were considered as evaluation metrics. Our results showed reasonable accuracy (RMSE < 8°), strong to very-strong correlation (correlation coefficient > 0.86), a mean difference within 1.1°, and agreement limits from -16° to 14°. In addition, no significant difference was found (p-value > 0.05) in extracted kinematics parameters between both systems. The proposed approach might represent a suitable alternative for the assessment of knee rehabilitation progress in a home context.
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Affiliation(s)
- Mohamed El Fezazi
- Electronic Systems Sensors and Nano-Biotechnologies, National Graduate School of Arts and Crafts (ENSAM), Mohammed V University in Rabat, Morocco
| | - Abdelouahad Achmamad
- Electronic Systems Sensors and Nano-Biotechnologies, National Graduate School of Arts and Crafts (ENSAM), Mohammed V University in Rabat, Morocco
| | - Atman Jbari
- Electronic Systems Sensors and Nano-Biotechnologies, National Graduate School of Arts and Crafts (ENSAM), Mohammed V University in Rabat, Morocco
| | - Abdelilah Jilbab
- Electronic Systems Sensors and Nano-Biotechnologies, National Graduate School of Arts and Crafts (ENSAM), Mohammed V University in Rabat, Morocco
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Grouvel G, Carcreff L, Moissenet F, Armand S. A dataset of asymptomatic human gait and movements obtained from markers, IMUs, insoles and force plates. Sci Data 2023; 10:180. [PMID: 36997555 PMCID: PMC10063557 DOI: 10.1038/s41597-023-02077-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 03/16/2023] [Indexed: 04/03/2023] Open
Abstract
Human motion capture and analysis could be made easier through the use of wearable devices such as inertial sensors and/or pressure insoles. However, many steps are still needed to reach the performance of optoelectronic systems to compute kinematic parameters. The proposed dataset has been established on 10 asymptomatic adults. Participants were asked to walk at different speeds on a 10-meters walkway in a laboratory and to perform different movements such as squats or knee flexion/extension tasks. Three-dimensional trajectories of 69 reflective markers placed according to a conventional full body markerset, acceleration and angular velocity signals of 8 inertial sensors, pressure signals of 2 insoles, 3D ground reaction forces and moments obtained from 3 force plates were simultaneously recorded. Eight calculated virtual markers related to joint centers were also added to the dataset. This dataset contains a total of 337 trials including static and dynamic tasks for each participant. Its purpose is to enable comparisons between various motion capture systems and stimulate the development of new methods for gait analysis.
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Affiliation(s)
- Gautier Grouvel
- Kinesiology Laboratory, Geneva University Hospitals and University of Geneva, Geneva, Switzerland.
| | - Lena Carcreff
- Kinesiology Laboratory, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Florent Moissenet
- Kinesiology Laboratory, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
- Biomechanics Laboratory, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Stéphane Armand
- Kinesiology Laboratory, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
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Rattanakoch J, Samala M, Limroongreungrat W, Guerra G, Tharawadeepimuk K, Nanbancha A, Niamsang W, Kerdsomnuek P, Suwanmana S. Validity and Reliability of Inertial Measurement Unit (IMU)-Derived 3D Joint Kinematics in Persons Wearing Transtibial Prosthesis. SENSORS (BASEL, SWITZERLAND) 2023; 23:1738. [PMID: 36772783 PMCID: PMC9920655 DOI: 10.3390/s23031738] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 01/27/2023] [Accepted: 01/29/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND A validity and reliability assessment of inertial measurement unit (IMU)-derived joint angular kinematics during walking is a necessary step for motion analysis in the lower extremity prosthesis user population. This study aimed to assess the accuracy and reliability of an inertial measurement unit (IMU) system compared to an optical motion capture (OMC) system in transtibial prosthesis (TTP) users. METHODS Thirty TTP users were recruited and underwent simultaneous motion capture from IMU and OMC systems during walking. Reliability and validity were assessed using intra- and inter-subject variability with standard deviation (S.D.), average S.D., and intraclass correlation coefficient (ICC). RESULTS The intra-subject S.D. for all rotations of the lower limb joints were less than 1° for both systems. The IMU system had a lower mean S.D. (o), as seen in inter-subject variability. The ICC revealed good to excellent agreement between the two systems for all sagittal kinematic parameters. CONCLUSION All joint angular kinematic comparisons supported the IMU system's results as comparable to OMC. The IMU was capable of precise sagittal plane motion data and demonstrated validity and reliability to OMC. These findings evidence that when compared to OMC, an IMU system may serve well in evaluating the gait of lower limb prosthesis users.
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Affiliation(s)
- Jutima Rattanakoch
- Sirindhorn School of Prosthetics and Orthotics, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Manunchaya Samala
- Sirindhorn School of Prosthetics and Orthotics, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | | | - Gary Guerra
- Exercise and Sport Science Department, St. Mary’s University, San Antonio, TX 78228, USA
| | | | - Ampika Nanbancha
- College of Sports Science and Technology, Mahidol University, Nakhon Pathom 73170, Thailand
| | - Wisavaporn Niamsang
- Sirindhorn School of Prosthetics and Orthotics, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Pichitpol Kerdsomnuek
- Department of Orthopaedic Surgery, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Sarit Suwanmana
- College of Sports Science and Technology, Mahidol University, Nakhon Pathom 73170, Thailand
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Laidig D, Weygers I, Seel T. Self-Calibrating Magnetometer-Free Inertial Motion Tracking of 2-DoF Joints. SENSORS (BASEL, SWITZERLAND) 2022; 22:9850. [PMID: 36560219 PMCID: PMC9785932 DOI: 10.3390/s22249850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/05/2022] [Accepted: 12/12/2022] [Indexed: 06/17/2023]
Abstract
Human motion analysis using inertial measurement units (IMUs) has recently been shown to provide accuracy similar to the gold standard, optical motion capture, but at lower costs and while being less restrictive and time-consuming. However, IMU-based motion analysis requires precise knowledge of the orientations in which the sensors are attached to the body segments. This knowledge is commonly obtained via time-consuming and error-prone anatomical calibration based on precisely defined poses or motions. In the present work, we propose a self-calibrating approach for magnetometer-free joint angle tracking that is suitable for joints with two degrees of freedom (DoF), such as the elbow, ankle, and metacarpophalangeal finger joints. The proposed methods exploit kinematic constraints in the angular rates and the relative orientations to simultaneously identify the joint axes and the heading offset. The experimental evaluation shows that the proposed methods are able to estimate plausible and consistent joint axes from just ten seconds of arbitrary elbow joint motion. Comparison with optical motion capture shows that the proposed methods yield joint angles with similar accuracy as a conventional IMU-based method while being much less restrictive. Therefore, the proposed methods improve the practical usability of IMU-based motion tracking in many clinical and biomedical applications.
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Affiliation(s)
- Daniel Laidig
- Control Systems Group, Technische Universität Berlin, 10623 Berlin, Germany
| | - Ive Weygers
- Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91052 Erlangen, Germany
| | - Thomas Seel
- Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91052 Erlangen, Germany
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