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Lloyd D. The future of in-field sports biomechanics: wearables plus modelling compute real-time in vivo tissue loading to prevent and repair musculoskeletal injuries. Sports Biomech 2024; 23:1284-1312. [PMID: 34496728 DOI: 10.1080/14763141.2021.1959947] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Accepted: 07/20/2021] [Indexed: 01/13/2023]
Abstract
This paper explores the use of biomechanics in identifying the mechanistic causes of musculoskeletal tissue injury and degeneration. It appraises how biomechanics has been used to develop training programmes aiming to maintain or recover tissue health. Tissue health depends on the functional mechanical environment experienced by tissues during daily and rehabilitation activities. These environments are the result of the interactions between tissue motion, loading, biology, and morphology. Maintaining health of and/or repairing musculoskeletal tissues requires targeting the "ideal" in vivo tissue mechanics (i.e., loading and deformation), which may be enabled by appropriate real-time biofeedback. Recent research shows that biofeedback technologies may increase their quality and effectiveness by integrating a personalised neuromusculoskeletal modelling driven by real-time motion capture and medical imaging. Model personalisation is crucial in obtaining physically and physiologically valid predictions of tissue biomechanics. Model real-time execution is crucial and achieved by code optimisation and artificial intelligence methods. Furthermore, recent work has also shown that laboratory-based motion capture biomechanical measurements and modelling can be performed outside the laboratory with wearable sensors and artificial intelligence. The next stage is to combine these technologies into well-designed easy to use products to guide training to maintain or recover tissue health in the real-world.
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Affiliation(s)
- David Lloyd
- School of Health Sciences and Social Work, Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), in the Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Griffith University, Australia
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Cornish BM, Diamond LE, Saxby DJ, Xia Z, Pizzolato C. Real-Time Calibration-Free Musculotendon Kinematics for Neuromusculoskeletal Models. IEEE Trans Neural Syst Rehabil Eng 2024; 32:3486-3495. [PMID: 39240743 DOI: 10.1109/tnsre.2024.3455262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/08/2024]
Abstract
Neuromusculoskeletal (NMS) models enable non-invasive estimation of clinically important internal biomechanics. A critical part of NMS modelling is the estimation of musculotendon kinematics, which comprise musculotendon unit lengths, moment arms, and lines of action. Musculotendon kinematics, which are partially dependent on joint angles, define the non-linear mapping of muscle forces to joint moments and contact forces. Currently, real-time computation of musculotendon kinematics requires creation of a per-individual surrogate model. The computational speed and accuracy of these surrogates degrade with increasing number of coordinates. We developed a feed-forward neural network that completely encodes musculotendon kinematics of a target model across a wide anthropometric range, enabling accurate real-time estimates of musculotendon kinematics without need for a priori creation of a per-individual surrogate model. Compared to reference, the neural network had median normalized errors ~0.1% for musculotendon lengths, <0.4% for moment arms, and <0.10° for line of action orientations. The neural network was employed within an electromyogram-informed NMS model to calculate hip contact forces, demonstrating little difference (normalized root mean square error 1.23±0.15 %) compared to using reference musculotendon kinematics. Finally, execution time was <0.04 ms per frame and constant for increasing number of model coordinates. Our approach to musculoskeletal kinematics may facilitate deployment of complex real-time NMS modelling in computer vision or wearable sensors applications to realize biomechanics monitoring, rehabilitation, and disease management outside the research laboratory.
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Harrington MS, Di Leo SD, Hlady CA, Burkhart TA. Musculoskeletal modeling and movement simulation for structural hip disorder research: A scoping review of methods, validation, and applications. Heliyon 2024; 10:e35007. [PMID: 39157349 PMCID: PMC11328100 DOI: 10.1016/j.heliyon.2024.e35007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2024] [Accepted: 07/22/2024] [Indexed: 08/20/2024] Open
Abstract
Musculoskeletal modeling is a powerful tool to quantify biomechanical factors typically not feasible to measure in vivo, such as hip contact forces and deep muscle activations. While technological advancements in musculoskeletal modeling have increased accessibility, selecting the appropriate modeling approach for a specific research question, particularly when investigating pathological populations, has become more challenging. The purposes of this review were to summarize current modeling and simulation methods in structural hip disorder research, as well as evaluate model validation and study reproducibility. MEDLINE and Web of Science were searched to identify literature relating to the use of musculoskeletal models to investigate structural hip disorders (i.e., involving a bony abnormality of the pelvis, femur, or both). Forty-seven articles were included for analysis, which either compared multiple modeling methods or applied a single modeling workflow to answer a research question. Findings from studies comparing methods were summarized, such as the effect of generic versus patient-specific modeling techniques on model-estimated hip contact forces or muscle forces. The review also discussed limitations in validation practices, as only 11 of the included studies conducted a validation and used qualitative approaches only. Given the lack of information related to model validation, additional details regarding the development and validation of generic models were retrieved from references and modeling software documentation. To address the wide variability and under-reporting of data collection, data processing, and modeling methods highlighted in this review, we developed a template that researchers can complete and include as a table within the methodology section of their manuscripts. The use of this table will help increase transparency and reporting of essential details related to reproducibility and methods without being limited by word count restrictions. Overall, this review provides a comprehensive synthesis of modeling approaches that can help researchers make modeling decisions and evaluate existing literature.
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Affiliation(s)
- Margaret S. Harrington
- Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, ON, Canada
| | - Stefania D.F. Di Leo
- Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, ON, Canada
| | - Courtney A. Hlady
- Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, ON, Canada
- Department of Physical Therapy, University of Toronto, Toronto, ON, Canada
| | - Timothy A. Burkhart
- Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, ON, Canada
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Coburn SL, Crossley KM, Kemp JL, Gassert F, Luitjens J, Warden SJ, Culvenor AG, Scholes MJ, King MG, Lawrenson P, Link TM, Heerey JJ. Association between hip muscle strength/function and hip cartilage defects in sub-elite football players with hip/groin pain. Osteoarthritis Cartilage 2024; 32:943-951. [PMID: 38648877 DOI: 10.1016/j.joca.2024.03.121] [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: 09/19/2023] [Revised: 02/26/2024] [Accepted: 03/01/2024] [Indexed: 04/25/2024]
Abstract
OBJECTIVE To explore associations between hip muscle strength and cartilage defects (presence and severity) on magnetic resonance imaging (MRI) in young adults with hip/groin pain participating in sub-elite football. DESIGN Sub-elite football players with hip/groin pain (>6 months) completed assessments of isometric hip strength and functional task performance. Hip cartilage defects were assessed using the Scoring Hip Osteoarthritis with MRI tool. This exploratory, cross-sectional study used logistic and negative binomial models to assess the relationships between hip muscle strength or functional task performance and hip cartilage defects, controlling for body mass index, age, testing site and cam morphology, incorporating sex-specific interaction terms. RESULTS One hundred and eighty-two (37 women) sub-elite (soccer or Australian football) players with hip/groin pain (age 26 ± 7 years) were included. Greater hip extension strength was associated with higher cartilage total score (adjusted incidence rate ratio [aIRR] 1.01, 95%CI: 1.0 to 1.02, p = 0.013) and superolateral cartilage score (adjusted odds ratio (aOR) 1.03, 95% confidence interval (CI): 1.01 to 1.06, p < 0.01). In female sub-elite football players, greater hip external rotation strength was associated with lateral cartilage defects (aOR 1.61, 95%CI: 1.05 to 2.48, p = 0.03) and higher cartilage total score (aIRR 1.25, 95%CI: 1.01 to 1.66, p = 0.042). A one-repetition increase in one-leg rise performance was related to lower odds of superomedial cartilage defects (aOR 0.96, 95%CI: 0.94 to 0.99, p < 0.01). CONCLUSIONS Overall, there were few associations between peak isometric hip muscle strength and overall hip cartilage defects. It is possible that other factors may have relevance in sub-elite football players. Additional studies are needed to support or refute our findings that higher one leg rise performance was associated with reduced superomedial cartilage defect severity and greater hip extension strength was related to higher cartilage defect severity scores.
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Affiliation(s)
- S L Coburn
- La Trobe University Sport and Exercise Medicine Research Centre, School of Allied Health, Human Services and Sport, La Trobe University, Bundoora, Australia.
| | - K M Crossley
- La Trobe University Sport and Exercise Medicine Research Centre, School of Allied Health, Human Services and Sport, La Trobe University, Bundoora, Australia
| | - J L Kemp
- La Trobe University Sport and Exercise Medicine Research Centre, School of Allied Health, Human Services and Sport, La Trobe University, Bundoora, Australia
| | - F Gassert
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, CA, USA
| | - J Luitjens
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, CA, USA
| | - S J Warden
- La Trobe University Sport and Exercise Medicine Research Centre, School of Allied Health, Human Services and Sport, La Trobe University, Bundoora, Australia; Department of Physical Therapy, School of Health & Human Sciences, Indiana 15 University, Indianapolis, IN, USA
| | - A G Culvenor
- La Trobe University Sport and Exercise Medicine Research Centre, School of Allied Health, Human Services and Sport, La Trobe University, Bundoora, Australia
| | - M J Scholes
- La Trobe University Sport and Exercise Medicine Research Centre, School of Allied Health, Human Services and Sport, La Trobe University, Bundoora, Australia; Discipline of Physiotherapy, School of Allied Health, Human Services and Sport, La Trobe University, Bundoora, Australia
| | - M G King
- La Trobe University Sport and Exercise Medicine Research Centre, School of Allied Health, Human Services and Sport, La Trobe University, Bundoora, Australia; Discipline of Physiotherapy, School of Allied Health, Human Services and Sport, La Trobe University, Bundoora, Australia
| | - P Lawrenson
- School of Health and Rehabilitation Sciences, The University of Queensland, St. Lucia, Australia
| | - T M Link
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, CA, USA
| | - J J Heerey
- La Trobe University Sport and Exercise Medicine Research Centre, School of Allied Health, Human Services and Sport, La Trobe University, Bundoora, Australia
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Cornish BM, Pizzolato C, Saxby DJ, Xia Z, Devaprakash D, Diamond LE. Hip contact forces can be predicted with a neural network using only synthesised key points and electromyography in people with hip osteoarthritis. Osteoarthritis Cartilage 2024; 32:730-739. [PMID: 38442767 DOI: 10.1016/j.joca.2024.02.891] [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: 07/04/2023] [Revised: 01/23/2024] [Accepted: 02/13/2024] [Indexed: 03/07/2024]
Abstract
OBJECTIVE To develop and validate a neural network to estimate hip contact forces (HCF), and lower body kinematics and kinetics during walking in individuals with hip osteoarthritis (OA) using synthesised anatomical key points and electromyography. To assess the capability of the neural network to detect directional changes in HCF resulting from prescribed gait modifications. DESIGN A calibrated electromyography-informed neuromusculoskeletal model was used to compute lower body joint angles, moments, and HCF for 17 participants with mild-to-moderate hip OA. Anatomical key points (e.g., joint centres) were synthesised from marker trajectories and augmented with bias and noise expected from computer vision-based pose estimation systems. Temporal convolutional and long short-term memory neural networks (NN) were trained using leave-one-subject-out validation to predict neuromusculoskeletal modelling outputs from the synthesised key points and measured electromyography data from 5 hip-spanning muscles. RESULTS HCF was predicted with an average error of 13.4 ± 7.1% of peak force. Joint angles and moments were predicted with an average root-mean-square-error of 5.3 degrees and 0.10 Nm/kg, respectively. The NN could detect changes in peak HCF that occur due to gait modifications with good agreement with neuromusculoskeletal modelling (r2 = 0.72) and a minimum detectable change of 9.5%. CONCLUSION The developed neural network predicted HCF and lower body joint angles and moments in individuals with hip OA using noisy synthesised key point locations with acceptable errors. Changes in HCF magnitude due to gait modifications were predicted with high accuracy. These findings have important implications for implementation of load-modification based gait retraining interventions for people with hip OA in a natural environment (i.e., home, clinic).
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Affiliation(s)
- Bradley M Cornish
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Australia.
| | - Claudio Pizzolato
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Australia.
| | - David J Saxby
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Australia.
| | - Zhengliang Xia
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Australia.
| | - Daniel Devaprakash
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Australia; Vald Performance, Brisbane, Australia.
| | - Laura E Diamond
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Australia.
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Crossley CB, Diamond LE, Saxby DJ, de Sousa A, Lloyd DG, Che Fornusek, Pizzolato C. Joint contact forces during semi-recumbent seated cycling. J Biomech 2024; 168:112094. [PMID: 38640830 DOI: 10.1016/j.jbiomech.2024.112094] [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: 10/06/2023] [Revised: 03/07/2024] [Accepted: 04/14/2024] [Indexed: 04/21/2024]
Abstract
Semi-recumbent cycling performed from a wheelchair is a popular rehabilitation exercise following spinal cord injury (SCI) and is often paired with functional electrical stimulation. However, biomechanical assessment of this cycling modality is lacking, even in unimpaired populations, hindering the development of personalised and safe rehabilitation programs for those with SCI. This study developed a computational pipeline to determine lower limb kinematics, kinetics, and joint contact forces (JCF) in 11 unimpaired participants during voluntary semi-recumbent cycling using a rehabilitation ergometer. Two cadences (40 and 60 revolutions per minute) and three crank powers (15 W, 30 W, and 45 W) were assessed. A rigid body model of a rehabilitation ergometer was combined with a calibrated electromyogram-informed neuromusculoskeletal model to determine JCF at the hip, knee, and ankle. Joint excursions remained consistent across all cadence and powers, but joint moments and JCF differed between 40 and 60 revolutions per minute, with peak JCF force significantly greater at 40 compared to 60 revolutions per minute for all crank powers. Poor correlations were found between mean crank power and peak JCF across all joints. This study provides foundation data and computational methods to enable further evaluation and optimisation of semi-recumbent cycling for application in rehabilitation after SCI and other neurological disorders.
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Affiliation(s)
- Claire B Crossley
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Griffith University, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Laura E Diamond
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Griffith University, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - David J Saxby
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Griffith University, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Ana de Sousa
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Griffith University, Australia; Research Centre for Biomedical Engineering (CREB) at the Universitat Politècnica de Catalunya (UPC), Barcelona, Spain
| | - David G Lloyd
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Griffith University, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Che Fornusek
- Exercise & Sports Science, Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Australia
| | - Claudio Pizzolato
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Griffith University, Australia; School of Health Sciences and Social Work, Griffith University, Australia.
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Diamond LE, Grant T, Uhlrich SD. Osteoarthritis year in review 2023: Biomechanics. Osteoarthritis Cartilage 2024; 32:138-147. [PMID: 38043858 DOI: 10.1016/j.joca.2023.11.015] [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: 09/11/2023] [Revised: 11/23/2023] [Accepted: 11/27/2023] [Indexed: 12/05/2023]
Abstract
Biomechanics plays a significant yet complex role in osteoarthritis (OA) onset and progression. Identifying alterations in biomechanical factors and their complex interactions is critical for gaining new insights into OA pathophysiology and identification of clearly defined and modifiable mechanical treatment targets. This review synthesized biomechanics studies from March 2022 to April 2023, from which three themes relating to human gait emerged: (1) new insights into the pathogenesis of OA using computational modeling and machine learning, (2) technology-enhanced biomechanical interventions for OA, and (3) out-of-lab biomechanical assessments of OA. We further highlighted future-focused areas which may continue to advance the field of biomechanics in OA, with a particular emphasis on exploiting technology to understand and treat biomechanical mechanisms of OA outside the laboratory. The breadth of studies included in this review highlights the complex role of biomechanics in OA and showcase numerous innovative and outstanding contributions to the field. Exciting cross-disciplinary efforts integrating computational modeling, mobile sensors, and machine learning methods show great promise for streamlining in vivo multi-scale biomechanics workflows and are expected to underpin future breakthroughs in the understanding and treatment of biomechanics in OA.
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Affiliation(s)
- Laura E Diamond
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Australia.
| | - Tamara Grant
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Australia.
| | - Scott D Uhlrich
- Department of Bioengineering, Stanford University, Stanford, CA, USA.
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Steingrebe H, Spancken S, Sell S, Stein T. Effects of hip osteoarthritis on lower body joint kinematics during locomotion tasks: a systematic review and meta-analysis. Front Sports Act Living 2023; 5:1197883. [PMID: 38046934 PMCID: PMC10690786 DOI: 10.3389/fspor.2023.1197883] [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: 03/31/2023] [Accepted: 10/09/2023] [Indexed: 12/05/2023] Open
Abstract
Introduction Motion analysis can be used to gain information needed for disease diagnosis as well as for the design and evaluation of intervention strategies in patients with hip osteoarthritis (HOA). Thereby, joint kinematics might be of great interest due to their discriminative capacity and accessibility, especially with regard to the growing usage of wearable sensors for motion analysis. So far, no comprehensive literature review on lower limb joint kinematics of patients with HOA exists. Thus, the aim of this systematic review and meta-analysis was to synthesise existing literature on lower body joint kinematics of persons with HOA compared to those of healthy controls during locomotion tasks. Methods Three databases were searched for studies on pelvis, hip, knee and ankle kinematics in subjects with HOA compared to healthy controls during locomotion tasks. Standardised mean differences were calculated and pooled using a random-effects model. Where possible, subgroup analyses were conducted. Risk of bias was assessed with the Downs and Black checklist. Results and Discussion A total of 47 reports from 35 individual studies were included in this review. Most studies analysed walking and only a few studies analysed stair walking or turning while walking. Most group differences were found in ipsi- and contralateral three-dimensional hip and sagittal knee angles with reduced ranges of motion in HOA subjects. Differences between subjects with mild to moderate and severe HOA were found, with larger effects in severe HOA subjects. Additionally, stair walking and turning while walking might be promising extensions in clinical gait analysis due to their elevated requirements for joint mobility. Large between-study heterogeneity was observed, and future studies have to clarify the effects of OA severity, laterality, age, gender, study design and movement execution on lower limb joint kinematics. Systematic Review Registration PROSPERO (CRD42021238237).
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Affiliation(s)
- Hannah Steingrebe
- BioMotion Center, Institute of Sports and Sports Science, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
- Sports Orthopedics, Institute of Sports and Sports Science, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Sina Spancken
- BioMotion Center, Institute of Sports and Sports Science, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
| | - Stefan Sell
- Sports Orthopedics, Institute of Sports and Sports Science, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
- Joint Center Black Forest, Hospital Neuenbürg, Neuenbürg, Germany
| | - Thorsten Stein
- BioMotion Center, Institute of Sports and Sports Science, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
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Marriott KA, Birmingham TB. Fundamentals of osteoarthritis. Rehabilitation: Exercise, diet, biomechanics, and physical therapist-delivered interventions. Osteoarthritis Cartilage 2023; 31:1312-1326. [PMID: 37423596 DOI: 10.1016/j.joca.2023.06.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 06/02/2023] [Accepted: 06/05/2023] [Indexed: 07/11/2023]
Abstract
Insights related to the pathogenesis of osteoarthritis (OA) have informed rehabilitative treatments that aim to mitigate the influence of several known impairments and risk factors for OA, with the goal to improve pain, function, and quality of life. The purpose of this invited narrative review is to provide fundamental knowledge to non-specialists about exercise and education, diet, biomechanical interventions, and other physical therapist-delivered treatments. In addition to summarizing the rationale for common rehabilitative therapies, we provide a synthesis of current core recommendations. Robust evidence based on randomized clinical trials supports exercise with education and diet as core treatments for OA. Structured, supervised exercise therapy is advised. The mode of exercise may vary but should be individualized. The dose should be based on an initial assessment, the desired physiological changes, and progressed when appropriate. Diet combined with exercise is strongly recommended and studies demonstrate a dose-response relationship between the magnitude of weight loss and symptom improvement. Recent evidence suggests the use of technology to remotely deliver exercise, diet and education interventions is cost-effective. Although several studies support the mechanisms for biomechanical interventions (e.g., bracing, shoe inserts) and physical therapist-delivered (passive) treatments (e.g., manual therapy, electrotherapeutic modalities) fewer rigorous randomized trials support their clinical use; these therapies are sometimes recommended as adjuncts to core treatments. The mechanisms of action for all rehabilitative interventions include contextual factors such as attention and placebo effects. These effects can challenge our interpretation of treatment efficacy from clinical trials, yet also provide opportunities to maximize patient outcomes in clinical practice. When evaluating rehabilitative interventions, the field may benefit from increased emphasis on research that considers contextual factors while evaluating mechanistic, longer-term, clinically-important and policy-relevant outcome measures.
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Affiliation(s)
- Kendal A Marriott
- Department of Kinesiology, University of Waterloo, Waterloo, Ontario, Canada.
| | - Trevor B Birmingham
- School of Physical Therapy, Faculty of Health Sciences, Bone and Joint Institute, University of Western Ontario, London, Ontario, Canada.
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10
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Harrington MS, Burkhart TA. Validation of a musculoskeletal model to investigate hip joint mechanics in response to dynamic multiplanar tasks. J Biomech 2023; 158:111767. [PMID: 37604097 DOI: 10.1016/j.jbiomech.2023.111767] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 07/10/2023] [Accepted: 08/11/2023] [Indexed: 08/23/2023]
Abstract
Existing hip-focused musculoskeletal (MSK) models are limited by the hip range of motion, hip musculature detail, or have only been qualitatively validated. The purposes of this study were to: i) modify the existing 2396Hip MSK model to simulate dynamic tasks with multiplanar hip joint motion; and ii) validate the modified MSK model quantitatively against experimental data. Experimental data was collected from five healthy adults (age = 25 [6] years, two females) during eight movement tasks. The motion and ground reaction force data were input into the MSK modeling software OpenSim to calculate muscle activations and hip contact forces (HCFs). The HCFs were compared to experimental HCFs previously measured in total hip arthroplasty (THA) patients using instrumented hip prostheses. A gait simulation was performed using data from one THA patient to directly assess the model's accuracy in estimating HCFs. The young adults' modeled and experimental muscle activations for seven muscles were compared using a cross-correlation function. The model only overestimated the peak resultant HCFs by 0.06-0.08 N/BW compared to the experimentally measured HCFs of the THA patient. The young adults' HCFs were over two standard deviations higher than previously measured in the THA patients, which is likely a result of different movement patterns. The correlation coefficients indicated strong correlations between experimental and modeled muscle activations in 50 of the 56 comparisons. The results of this study suggest the new MSK model is an appropriate method to quantify HCFs and muscle activations in response to dynamic, multiplanar tasks among young, healthy adults.
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Affiliation(s)
- Margaret S Harrington
- Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, ON, Canada
| | - Timothy A Burkhart
- Faculty of Kinesiology and Physical Education, University of Toronto, Toronto, ON, Canada.
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11
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Higgs JP, Diamond LE, Saxby DJ, Barrett RS, Graham DF. Individual muscle contributions to the acceleration of the centre of mass during gait in people with mild-to-moderate hip osteoarthritis. Gait Posture 2023; 104:151-158. [PMID: 37421811 DOI: 10.1016/j.gaitpost.2023.06.018] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Revised: 05/29/2023] [Accepted: 06/26/2023] [Indexed: 07/10/2023]
Abstract
BACKGROUND People with mild-to-moderate hip osteoarthritis (OA) exhibit hip muscle weakness, alterations in hip kinematics and kinetics and hip contact forces during gait compared to healthy controls. However, it is unclear if those with hip OA use different motor control strategies to coordinate the motion of the centre of mass (COM) during gait. Such information could provide further critical assessment of conservative management strategies implemented for people with hip OA. RESEARCH QUESTION Do muscle contributions to the acceleration of the COM during walking differ between individuals with mild-to-moderate hip OA and controls? METHODS Eleven individuals with mild-to-moderate hip OA and 10 healthy controls walked at a self-selected speed while whole-body motion and ground reaction forces were measured. Muscle forces during gait were obtained using static optimisation and an induced acceleration analysis was performed to determine individual muscle contributions to the acceleration of the COM during single-leg stance (SLS). Between-group comparisons were made using independent t-tests via Statistical Parametric Modelling. RESULTS There were no between-group differences in spatial-temporal gait parameters or three-dimensional whole-body COM acceleration. The rectus femoris, biceps femoris, iliopsoas and gastrocnemius muscles in the hip OA group contributed less to the fore-aft accelerations of the COM (p < 0.05), and more to the vertical COM acceleration with the gluteus maximus (p < 0.05), during SLS, compared to the control group. SIGNIFICANCE Subtle differences exist in the way people with mild-to-moderate hip OA use their muscles to accelerate the whole-body centre of mass during the SLS phase of walking relative to healthy controls. These findings improve understanding of the complex functional consequences of hip OA and enhance our understanding of how to monitor the effectiveness of an intervention on biomechanical changes in gait in people with hip OA.
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Affiliation(s)
- Jeremy P Higgs
- Griffith University, Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Gold Coast, QLD 4222, Australia; Griffith University, School of Health Sciences and Social Work, Gold Coast, QLD 4222, Australia
| | - Laura E Diamond
- Griffith University, Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Gold Coast, QLD 4222, Australia; Griffith University, School of Health Sciences and Social Work, Gold Coast, QLD 4222, Australia
| | - David J Saxby
- Griffith University, Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Gold Coast, QLD 4222, Australia; Griffith University, School of Health Sciences and Social Work, Gold Coast, QLD 4222, Australia
| | - Rod S Barrett
- Griffith University, Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Gold Coast, QLD 4222, Australia; Griffith University, School of Health Sciences and Social Work, Gold Coast, QLD 4222, Australia
| | - David F Graham
- Griffith University, School of Health Sciences and Social Work, Gold Coast, QLD 4222, Australia; Montana State University, College of Education. Health & Human Development, Bozeman, MT 59717-2940, USA.
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12
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Lloyd DG, Saxby DJ, Pizzolato C, Worsey M, Diamond LE, Palipana D, Bourne M, de Sousa AC, Mannan MMN, Nasseri A, Perevoshchikova N, Maharaj J, Crossley C, Quinn A, Mulholland K, Collings T, Xia Z, Cornish B, Devaprakash D, Lenton G, Barrett RS. Maintaining soldier musculoskeletal health using personalised digital humans, wearables and/or computer vision. J Sci Med Sport 2023:S1440-2440(23)00070-1. [PMID: 37149408 DOI: 10.1016/j.jsams.2023.04.001] [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: 05/31/2022] [Revised: 03/27/2023] [Accepted: 04/05/2023] [Indexed: 05/08/2023]
Abstract
OBJECTIVES The physical demands of military service place soldiers at risk of musculoskeletal injuries and are major concerns for military capability. This paper outlines the development new training technologies to prevent and manage these injuries. DESIGN Narrative review. METHODS Technologies suitable for integration into next-generation training devices were examined. We considered the capability of technologies to target tissue level mechanics, provide appropriate real-time feedback, and their useability in-the-field. RESULTS Musculoskeletal tissues' health depends on their functional mechanical environment experienced in military activities, training and rehabilitation. These environments result from the interactions between tissue motion, loading, biology, and morphology. Maintaining health of and/or repairing joint tissues requires targeting the "ideal" in vivo tissue mechanics (i.e., loading and strain), which may be enabled by real-time biofeedback. Recent research has shown that these biofeedback technologies are possible by integrating a patient's personalised digital twin and wireless wearable devices. Personalised digital twins are personalised neuromusculoskeletal rigid body and finite element models that work in real-time by code optimisation and artificial intelligence. Model personalisation is crucial in obtaining physically and physiologically valid predictions. CONCLUSIONS Recent work has shown that laboratory-quality biomechanical measurements and modelling can be performed outside the laboratory with a small number of wearable sensors or computer vision methods. The next stage is to combine these technologies into well-designed easy to use products.
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Affiliation(s)
- David G Lloyd
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia.
| | - David J Saxby
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Claudio Pizzolato
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Matthew Worsey
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia
| | - Laura E Diamond
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Dinesh Palipana
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Medicine, Dentistry and Health, Griffith University, Australia
| | - Matthew Bourne
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Ana Cardoso de Sousa
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia
| | - Malik Muhammad Naeem Mannan
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia
| | - Azadeh Nasseri
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia
| | - Nataliya Perevoshchikova
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia
| | - Jayishni Maharaj
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Claire Crossley
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Alastair Quinn
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Kyle Mulholland
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia
| | - Tyler Collings
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Zhengliang Xia
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia
| | - Bradley Cornish
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
| | - Daniel Devaprakash
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; VALD Performance, Australia
| | | | - Rodney S Barrett
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Australia; School of Health Sciences and Social Work, Griffith University, Australia
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13
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The biomechanical fingerprint of hip and knee osteoarthritis patients during activities of daily living. Clin Biomech (Bristol, Avon) 2023; 101:105858. [PMID: 36525720 DOI: 10.1016/j.clinbiomech.2022.105858] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 12/07/2022] [Accepted: 12/07/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Osteoarthritis is a highly prevalent disease affecting the hip and knee joint and is characterized by load-mediated pain and decreased quality of life. Dependent on involved joint, patients present antalgic movement compensations, aiming to decrease loading on the involved joint. However, the associated alterations in mechanical loading of the ipsi- and contra-lateral lower limb joints, are less documented. Here, we documented the biomechanical fingerprint of end-stage hip and knee osteoarthritis patients in terms of ipsilateral and contralateral hip and knee loading during walking and stair ambulation. METHODS Three-dimensional motion-analysis was performed in 20 hip, 18 knee osteoarthritis patients and 12 controls during level walking and stair ambulation. Joint contact forces were calculated using a standard musculoskeletal modelling workflow in Opensim. Involved and contralateral hip and knee joint loading was compared against healthy controls using independent t-tests (p < 0.05). FINDINGS Both hip and knee cohorts significantly decreased loading of the involved joint during gait and stair ambulation. Hip osteoarthritis patients presented no signs of ipsilateral knee nor contralateral leg overloading, during walking and stair ascending. However, knee osteoarthritis patients significantly increased loading at the ipsilateral hip, and contralateral hip and knee joints during stair ambulation compared to controls. INTERPRETATION The biomechanical fingerprint in knee and hip osteoarthritis patients confirmed antalgic movement strategies to unload the involved leg during gait. Only during stair ambulation in knee osteoarthritis patients, movement adaptations were confirmed that induced unbalanced intra- and inter-limb loading conditions, which are known risk factors for secondary osteoarthritis.
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14
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Emmerzaal J, Van Rossom S, van der Straaten R, De Brabandere A, Corten K, De Baets L, Davis J, Jonkers I, Timmermans A, Vanwanseele B. Joint kinematics alone can distinguish hip or knee osteoarthritis patients from asymptomatic controls with high accuracy. J Orthop Res 2022; 40:2229-2239. [PMID: 35043466 DOI: 10.1002/jor.25269] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 08/17/2021] [Accepted: 01/06/2022] [Indexed: 02/04/2023]
Abstract
Osteoarthritis (OA) is one of the leading musculoskeletal disabilities worldwide, and several interventions intend to change the gait pattern in OA patients to more healthy patterns. However, an accessible way to follow up the biomechanical changes in a clinical setting is still missing. Therefore, this study aims to evaluate whether we can use biomechanical data collected from a specific activity of daily living to help distinguish hip OA patients from controls and knee OA patients from controls using features that potentially could be measured in a clinical setting. To achieve this goal, we considered three different classes of statistical models with different levels of data complexity. Class 1 is kinematics based only (clinically applicable), class 2 includes joint kinetics (semi-applicable under the condition of access to a force plate or prediction models), and class 3 uses data from advanced musculoskeletal modeling (not clinically applicable). We used a machine learning pipeline to determine which classification model was best. We found 100% classification accuracy for KneeOA-vs-Asymptomatic and 93.9% for HipOA-vs-Asymptomatic using seven features derived from the lumbar spine and hip kinematics collected during ascending stairs. These results indicate that kinematical data alone can distinguish hip or knee OA patients from asymptomatic controls. However, to enable clinical use, we need to validate if the classifier also works with sensor-based kinematical data and whether the probabilistic outcome of the logistic regression model can be used in the follow-up of patients with OA.
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Affiliation(s)
- Jill Emmerzaal
- Human Movement Biomechanics Research Group, Department of Movement Sciences, KU Leuven, Belgium.,REVAL Rehabilitation Research Centre, Faculty of Rehabilitation Sciences, Hasselt University, Hasselt, Belgium
| | - Sam Van Rossom
- Human Movement Biomechanics Research Group, Department of Movement Sciences, KU Leuven, Belgium
| | - Rob van der Straaten
- REVAL Rehabilitation Research Centre, Faculty of Rehabilitation Sciences, Hasselt University, Hasselt, Belgium
| | - Arne De Brabandere
- Declarative Languages and Artificial Intelligence Group, Department of Computer Science, KU Leuven, Belgium
| | - Kristoff Corten
- Department of Orthopaedics, Ziekenhuis Oost Limburg, Genk, Belgium
| | - Liesbet De Baets
- Pain in Motion Research Group (PAIN), Department of Physiotherapy, Human Physiology and Anatomy, Vrije Universiteit Brussel, Ixelles, Belgium
| | - Jesse Davis
- Declarative Languages and Artificial Intelligence Group, Department of Computer Science, KU Leuven, Belgium
| | - Ilse Jonkers
- Human Movement Biomechanics Research Group, Department of Movement Sciences, KU Leuven, Belgium
| | - Annick Timmermans
- REVAL Rehabilitation Research Centre, Faculty of Rehabilitation Sciences, Hasselt University, Hasselt, Belgium
| | - Benedicte Vanwanseele
- Human Movement Biomechanics Research Group, Department of Movement Sciences, KU Leuven, Belgium
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15
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Grant TM, Diamond LE, Pizzolato C, Savage TN, Bennell K, Dickenson EJ, Eyles J, Foster NE, Hall M, Hunter DJ, Lloyd DG, Molnar R, Murphy NJ, O'Donnell J, Singh P, Spiers L, Tran P, Saxby DJ. Comparison of Walking Biomechanics After Physical Therapist-Led Care or Hip Arthroscopy for Femoroacetabular Impingement Syndrome: A Secondary Analysis From a Randomized Controlled Trial. Am J Sports Med 2022; 50:3198-3209. [PMID: 36177759 DOI: 10.1177/03635465221120388] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
BACKGROUND Femoroacetabular impingement syndrome is characterized by chondrolabral damage and hip pain. The specific biomechanics used by people with femoroacetabular impingement syndrome during daily activities may exacerbate their symptoms. Femoroacetabular impingement syndrome can be treated nonoperatively or surgically; however, differential treatment effects on walking biomechanics have not been examined. PURPOSE To compare the 12-month effects of physical therapist-led care or arthroscopy on trunk, pelvis, and hip kinematics as well as hip moments during walking. STUDY DESIGN Secondary analysis of multi-centre, pragmatic, two-arm superiority randomized controlled trial subsample; Level of evidence, 1. METHODS A subsample of 43 participants from the Australian Full randomised controlled trial of Arthroscopic Surgery for Hip Impingement versus best cONventional (FASHIoN trial) underwent gait analysis and completed the International Hip Outcome Tool (iHOT-33) at both baseline and 12 months after random allocation to physical therapist-led care (personalized hip therapy; n = 22; mean age 35; 41% female) or arthroscopy (n = 21; mean age 36; 48% female). Changes in trunk, pelvis, and hip biomechanics were compared between treatment groups across the gait cycle using statistical parametric mapping. Associations between changes in iHOT-33 and changes in hip kinematics across 3 planes of motion were examined. RESULTS As compared with the arthroscopy group, the personalized hip therapy group increased its peak hip adduction moments (mean difference = 0.35 N·m/body weight·height [%] [95% CI, 0.05-0.65]; effect size = 0.72; P = .02). Hip adduction moments in the arthroscopy group were unchanged in response to treatment. No other between-group differences were detected. Improvements in iHOT-33 were not associated with changes in hip kinematics. CONCLUSION Peak hip adduction moments were increased in the personalized hip therapy group and unchanged in the arthroscopy group. No biomechanical changes favoring arthroscopy were detected, suggesting that personalized hip therapy elicits greater changes in hip moments during walking at 12-month follow-up. Twelve-month changes in hip-related quality of life were not associated with changes in hip kinematics.
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Affiliation(s)
| | | | - Claudio Pizzolato
- Griffith Centre of Biomedical and Rehabilitation Engineering, Griffith University, Gold Coast, Australia
| | - Trevor N Savage
- Griffith Centre of Biomedical and Rehabilitation Engineering, Griffith University, Gold Coast, Australia; and Sydney Musculoskeletal Health, Kolling Institute of Medical Research, The University of Sydney, Sydney, Australia
| | - Kim Bennell
- Centre for Health, Exercise and Sports Medicine, Department of Physiotherapy, University of Melbourne, Melbourne, Australia
| | - Edward J Dickenson
- University of Warwick, Coventry, UK, and University Hospitals of Coventry and Warwickshire NHS Trust, Coventry, UK
| | - Jillian Eyles
- Sydney Musculoskeletal Health, Kolling Institute of Medical Research, The University of Sydney, Sydney, Australia; and Department of Rheumatology, Royal North Shore Hospital, St Leonards, Australia
| | - Nadine E Foster
- Primary Care Centre Versus Arthritis, School of Medicine, Keele University, Keele, UK; and STARS Education and Research Alliance, Surgical, Treatment and Rehabilitation Service, The University of Queensland and Metro North Health, Queensland, Australia
| | - Michelle Hall
- Centre for Health, Exercise and Sports Medicine, Department of Physiotherapy, University of Melbourne, Melbourne, Australia
| | - David J Hunter
- Sydney Musculoskeletal Health, Kolling Institute of Medical Research, The University of Sydney, Sydney, Australia; and Department of Rheumatology, Royal North Shore Hospital, St Leonards, Australia
| | - David G Lloyd
- Griffith Centre of Biomedical and Rehabilitation Engineering, Griffith University, Gold Coast, Australia
| | - Robert Molnar
- Department of Orthopaedic Surgery, St George Hospital, Kogarah, Australia; and Sydney Orthopaedic and Reconstructive Surgery, Sydney, Australia
| | - Nicholas J Murphy
- Sydney Musculoskeletal Health, Kolling Institute of Medical Research, The University of Sydney, Sydney, Australia; and Department of Orthopaedic Surgery, John Hunter Hospital, Newcastle, Australia
| | - John O'Donnell
- Hip Arthroscopy Australia, Richmond, Australia; and School of Health Sciences, Swinburne University of Technology, Melbourne, Australia
| | - Parminder Singh
- Hip Arthroscopy Australia, Richmond, Australia; and Maroondah Hospital, Eastern Health, Melbourne, Australia
| | - Libby Spiers
- Centre for Health, Exercise and Sports Medicine, Department of Physiotherapy, University of Melbourne, Melbourne, Australia
| | - Phong Tran
- Department of Orthopaedic Surgery, Western Health, Melbourne, Australia; and Australian Institute for Musculoskeletal Science, University of Melbourne and Western Health, St Albans, Australia
| | - David J Saxby
- Griffith Centre of Biomedical and Rehabilitation Engineering, Griffith University, Gold Coast, Australia.,Investigation performed at Griffith University, Southport, Queensland, Australia
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16
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Meinders E, Pizzolato C, Gonçalves B, Lloyd DG, Saxby DJ, Diamond LE. Activation of the deep hip muscles can change the direction of loading at the hip. J Biomech 2022; 135:111019. [DOI: 10.1016/j.jbiomech.2022.111019] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 01/27/2022] [Accepted: 02/21/2022] [Indexed: 11/28/2022]
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17
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Diamond LE, Devaprakash D, Cornish B, Plinsinga ML, Hams A, Hall M, Hinman RS, Pizzolato C, Saxby DJ. Feasibility of personalised hip load modification using real-time biofeedback in hip osteoarthritis: A pilot study. OSTEOARTHRITIS AND CARTILAGE OPEN 2022; 4:100230. [DOI: 10.1016/j.ocarto.2021.100230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 11/30/2021] [Accepted: 12/20/2021] [Indexed: 11/29/2022] Open
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18
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Silvestros P, Pizzolato C, Lloyd DG, Preatoni E, Gill HS, Cazzola D. Electromyography-Assisted Neuromusculoskeletal Models Can Estimate Physiological Muscle Activations and Joint Moments Across the Neck Before Impacts. J Biomech Eng 2022; 144:1120603. [PMID: 34557891 DOI: 10.1115/1.4052555] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Indexed: 01/20/2023]
Abstract
Knowledge of neck muscle activation strategies before sporting impacts is crucial for investigating mechanisms of severe spinal injuries. However, measurement of muscle activations during impacts is experimentally challenging and computational estimations are not often guided by experimental measurements. We investigated neck muscle activations before impacts with the use of electromyography (EMG)-assisted neuromusculoskeletal models. Kinematics and EMG recordings from four major neck muscles of a rugby player were experimentally measured during rugby activities. A subject-specific musculoskeletal model was created with muscle parameters informed from MRI measurements. The model was used in the calibrated EMG-informed neuromusculoskeletal modeling toolbox and three neural solutions were compared: (i) static optimization (SO), (ii) EMG-assisted (EMGa), and (iii) MRI-informed EMG-assisted (EMGaMRI). EMGaMRI and EMGa significantly (p < 0.01) outperformed SO when tracking cervical spine net joint moments from inverse dynamics in flexion/extension (RMSE = 0.95, 1.14, and 2.32 N·m) but not in lateral bending (RMSE = 1.07, 2.07, and 0.84 N·m). EMG-assisted solutions generated physiological muscle activation patterns and maintained experimental cocontractions significantly (p < 0.01) outperforming SO, which was characterized by saturation and nonphysiological "on-off" patterns. This study showed for the first time that physiological neck muscle activations and cervical spine net joint moments can be estimated without assumed a priori objective criteria before impacts. Future studies could use this technique to provide detailed initial loading conditions for theoretical simulations of neck injury during impacts.
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Affiliation(s)
- Pavlos Silvestros
- Department for Health, Centre for Analysis of Motion and Entertainment Research and Application (CAMERA), University of Bath, Bath BA2 7AY, UK
| | - Claudio Pizzolato
- School of Allied Health Sciences, Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Griffith University, Gold Coast, Queensland 4222, Australia
| | - David G Lloyd
- School of Allied Health Sciences, Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Griffith University, Gold Coast, Queensland 4222, Australia
| | - Ezio Preatoni
- Department for Health, University of Bath, Bath BA2 7AY, UK
| | - Harinderjit S Gill
- Centre for Therapeutic Innovation, Department of Mechanical Engineering, University of Bath, Bath BA2 7AY, UK
| | - Dario Cazzola
- Department for Health, Centre for Analysis of Motion and Entertainment Research and Application (CAMERA), University of Bath, Bath BA2 7AY, UK
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19
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Hall M, van der Esch M, Hinman RS, Peat G, de Zwart A, Quicke JG, Runhaar J, Knoop J, van der Leeden M, de Rooij M, Meulenbelt I, Vliet Vlieland T, Lems WF, Holden MA, Foster NE, Bennell KL. How does hip osteoarthritis differ from knee osteoarthritis? Osteoarthritis Cartilage 2022; 30:32-41. [PMID: 34600121 DOI: 10.1016/j.joca.2021.09.010] [Citation(s) in RCA: 54] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 09/01/2021] [Accepted: 09/21/2021] [Indexed: 02/02/2023]
Abstract
Hip and knee osteoarthritis (OA) are leading causes of global disability. Most research to date has focused on the knee, with results often extrapolated to the hip, and this extends to treatment recommendations in clinical guidelines. Extrapolating results from research on knee OA may limit our understanding of disease characteristics specific to hip OA, thereby constraining development and implementation of effective treatments. This review highlights differences between hip and knee OA with respect to prevalence, prognosis, epigenetics, pathophysiology, anatomical and biomechanical factors, clinical presentation, pain and non-surgical treatment recommendations and management.
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Affiliation(s)
- M Hall
- Centre for Health Exercise and Sports Medicine, Department of Physiotherapy, School of Health Sciences, The University of Melbourne, Australia
| | - M van der Esch
- Reade, Center for Rehabilitation and Rheumatology, Amsterdam, the Netherlands; Center of Expertise Urban Vitality, University of Applied Sciences Amsterdam, the Netherlands
| | - R S Hinman
- Centre for Health Exercise and Sports Medicine, Department of Physiotherapy, School of Health Sciences, The University of Melbourne, Australia
| | - G Peat
- Primary Care Centre Versus Arthritis, School of Medicine, Keele University, UK
| | - A de Zwart
- Reade, Center for Rehabilitation and Rheumatology, Amsterdam, the Netherlands
| | - J G Quicke
- Primary Care Centre Versus Arthritis, School of Medicine, Keele University, UK
| | - J Runhaar
- Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - J Knoop
- Vrije Universiteit Amsterdam, the Netherlands
| | - M van der Leeden
- Reade, Center for Rehabilitation and Rheumatology, Amsterdam, the Netherlands; Amsterdam UMC, Location VUmc, Department of Rheumatology, Amsterdam, the Netherlands
| | - M de Rooij
- Reade, Center for Rehabilitation and Rheumatology, Amsterdam, the Netherlands
| | | | | | - W F Lems
- Reade, Center for Rehabilitation and Rheumatology, Amsterdam, the Netherlands; Amsterdam UMC, Location VUmc, Department of Rheumatology, Amsterdam, the Netherlands
| | - M A Holden
- Primary Care Centre Versus Arthritis, School of Medicine, Keele University, UK
| | - N E Foster
- Primary Care Centre Versus Arthritis, School of Medicine, Keele University, UK; STARS Research and Education Alliance, Surgical Treatment and Rehabilitation Service (STARS), The University of Queensland and Metro North Hospital and Health Service, Queensland, Australia
| | - K L Bennell
- Centre for Health Exercise and Sports Medicine, Department of Physiotherapy, School of Health Sciences, The University of Melbourne, Australia.
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20
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Diamond LE, Barrett RS, Modenese L, Anderson AE, Hall M. Editorial: Neuromechanics of Hip Osteoarthritis. Front Sports Act Living 2021; 3:788263. [PMID: 34859205 PMCID: PMC8631320 DOI: 10.3389/fspor.2021.788263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 10/20/2021] [Indexed: 11/17/2022] Open
Affiliation(s)
- Laura E Diamond
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia.,School of Health Sciences and Social Work, Griffith University, Gold Coast, QLD, Australia
| | - Rod S Barrett
- Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia.,School of Health Sciences and Social Work, Griffith University, Gold Coast, QLD, Australia
| | - Luca Modenese
- Department of Civil and Environmental Engineering, Imperial College London, London, United Kingdom
| | - Andrew E Anderson
- University of Utah Motion Capture Core Facility, University of Utah, Salt Lake City, UT, United States
| | - Michelle Hall
- Centre for Health, Exercise and Sports Medicine, The University of Melbourne, Melbourne, VIC, Australia
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21
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Rostron ZPJ, Green RA, Kingsley M, Zacharias A. Efficacy of Exercise-Based Rehabilitation Programs for Improving Muscle Function and Size in People with Hip Osteoarthritis: A Systematic Review with Meta-Analysis. BIOLOGY 2021; 10:biology10121251. [PMID: 34943166 PMCID: PMC8698712 DOI: 10.3390/biology10121251] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 11/25/2021] [Accepted: 11/29/2021] [Indexed: 11/16/2022]
Abstract
Objective: To determine the effect of exercise-based rehabilitation programs on hip and knee muscle function and size in people with hip osteoarthritis. Methods: Seven databases were systematically searched in order to identify studies that assessed muscle function (strength or power) and size in people with hip osteoarthritis after exercise-based rehabilitation programs. Studies were screened for eligibility and assessed for quality of evidence using the GRADE approach. Data were pooled, and meta-analyses was completed on 7 of the 11 included studies. Results: Six studies reported hip and/or knee function outcomes, and two reported muscle volumes that could be included in meta-analyses. Meta-analyses were conducted for four strength measures (hip abduction, hip extension, hip flexion, and knee extension) and muscle size (quadriceps femoris volume). For hip abduction, there was a low certainty of evidence with a small important effect (effect size = 0.28, 95% CI = 0.01, 0.54) favouring high-intensity resistance interventions compared to control. There were no other comparisons or overall meta-analyses that identified benefits for hip or knee muscle function or size. Conclusion: High-intensity resistance programs may increase hip abduction strength slightly when compared with a control group. No differences were identified in muscle function or size when comparing a high versus a low intensity group. It is unclear whether strength improvements identified in this review are associated with hypertrophy or other neuromuscular factors.
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Affiliation(s)
- Zachary P. J. Rostron
- Department of Pharmacy and Biomedical Sciences, College of Science, Health and Engineering, La Trobe University, Bendigo, VIC 3550, Australia; (R.A.G.); (A.Z.)
- Correspondence:
| | - Rodney A. Green
- Department of Pharmacy and Biomedical Sciences, College of Science, Health and Engineering, La Trobe University, Bendigo, VIC 3550, Australia; (R.A.G.); (A.Z.)
| | - Michael Kingsley
- Department of Exercise Sciences, Faculty of Science, University of Auckland, Auckland 1023, New Zealand;
- Holsworth Research Initiative, College of Science, Health and Engineering, La Trobe University, Bendigo, VIC 3550, Australia
| | - Anita Zacharias
- Department of Pharmacy and Biomedical Sciences, College of Science, Health and Engineering, La Trobe University, Bendigo, VIC 3550, Australia; (R.A.G.); (A.Z.)
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22
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Buehler C, Koller W, De Comtes F, Kainz H. Quantifying Muscle Forces and Joint Loading During Hip Exercises Performed With and Without an Elastic Resistance Band. Front Sports Act Living 2021; 3:695383. [PMID: 34497999 PMCID: PMC8419330 DOI: 10.3389/fspor.2021.695383] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 07/21/2021] [Indexed: 01/13/2023] Open
Abstract
An increase in hip joint contact forces (HJCFs) is one of the main contributing mechanical causes of hip joint pathologies, such as hip osteoarthritis, and its progression. The strengthening of the surrounding muscles of the joint is a way to increase joint stability, which results in the reduction of HJCF. Most of the exercise recommendations are based on expert opinions instead of evidence-based facts. This study aimed to quantify muscle forces and joint loading during rehabilitative exercises using an elastic resistance band (ERB). Hip exercise movements of 16 healthy volunteers were recorded using a three-dimensional motion capture system and two force plates. All exercises were performed without and with an ERB and two execution velocities. Hip joint kinematics, kinetics, muscle forces, and HJCF were calculated based on the musculoskeletal simulations in OpenSim. Time-normalized waveforms of the different exercise modalities were compared with each other and with reference values found during walking. The results showed that training with an ERB increases both target muscle forces and HJCF. Furthermore, the ERB reduced the hip joint range of motion during the exercises. The type of ERB used (soft vs. stiff ERB) and the execution velocity of the exercise had a minor impact on the peak muscle forces and HJCF. The velocity of exercise execution, however, had an influence on the total required muscle force. Performing hip exercises without an ERB resulted in similar or lower peak HJCF and lower muscle forces than those found during walking. Adding an ERB during hip exercises increased the peak muscle and HJCF but the values remained below those found during walking. Our workflow and findings can be used in conjunction with future studies to support exercise design.
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Affiliation(s)
- Callum Buehler
- Neuromechanics Research Group, Department of Biomechanics, Kinesiology and Computer Science in Sport, Centre for Sport Science and University Sports, University of Vienna, Vienna, Austria
| | - Willi Koller
- Neuromechanics Research Group, Department of Biomechanics, Kinesiology and Computer Science in Sport, Centre for Sport Science and University Sports, University of Vienna, Vienna, Austria
| | - Florentina De Comtes
- Neuromechanics Research Group, Department of Biomechanics, Kinesiology and Computer Science in Sport, Centre for Sport Science and University Sports, University of Vienna, Vienna, Austria
| | - Hans Kainz
- Neuromechanics Research Group, Department of Biomechanics, Kinesiology and Computer Science in Sport, Centre for Sport Science and University Sports, University of Vienna, Vienna, Austria
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Astephen Wilson JL, Kobsar D. Osteoarthritis year in review 2020: mechanics. Osteoarthritis Cartilage 2021; 29:161-169. [PMID: 33421562 DOI: 10.1016/j.joca.2020.12.009] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 12/02/2020] [Accepted: 12/21/2020] [Indexed: 02/06/2023]
Abstract
The mechanical environment of the joint during dynamic activity plays a significant role in osteoarthritis processes. Understanding how the magnitude, pattern and duration of joint-specific loading features contribute to osteoarthritis progression and response to treatment is a topic of on-going relevance. This narrative review synthesizes evidence from recent papers that have contributed to knowledge related to three identified emerging subthemes: 1) the role of the joint mechanical environment in osteoarthritis pathogenesis, 2) joint biomechanics as an outcome to arthroplasty treatment of osteoarthritis, and 3) methodological trends for advancing our knowledge of the role of biomechanics in osteoarthritis. Rather than provide an exhaustive review of a broad area of research, we have focused on evidence this year related to these subthemes. New research this year has indicated significant interest in using biomechanics investigations to understand structural vs clinical progression of osteoarthritis, the role and interaction in the three-dimensional loading environment of the joint, and the contribution of muscle activation and forces to osteoarthritis progression. There is ongoing interest in understanding how patient variability with respect to gait biomechanics influences arthroplasty surgery outcomes, and subgroup analyses have provided evidence for the potential utility in tailored treatment approaches. Finally, we are seeing a growing trend in the application of translational biomechanics tools such as wearable inertial measurement units for improved integration of biomechanics into clinical decision-making and outcomes assessment for osteoarthritis.
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Affiliation(s)
- J L Astephen Wilson
- Department of Surgery, McMaster University, 1280 Main St West, Hamilton, ON, Canada.
| | - D Kobsar
- Department of Kinesiology, McMaster University, 1280 Main St West, Hamilton, ON, Canada.
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Zacharias A, Pizzari T, Semciw AI, English DJ, Kapakoulakis T, Green RA. Gluteus medius and minimus activity during stepping tasks: Comparisons between people with hip osteoarthritis and matched control participants. Gait Posture 2020; 80:339-346. [PMID: 32603886 DOI: 10.1016/j.gaitpost.2020.06.012] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 06/02/2020] [Accepted: 06/09/2020] [Indexed: 02/02/2023]
Abstract
BACKGROUND Altered gluteus minimus (GMin) activity has been identified in people with hip osteoarthritis (OA) during gait with some evidence of altered gluteus medius (GMed) activity in patients with advanced OA. It is not known whether these muscles also exhibit altered activity during other functional tasks. RESEARCH QUESTION Does gluteal muscle activity during stepping tasks differ between people with hip OA and healthy older adults? METHODS Participants included 20 people with unilateral hip OA and 20 age-and sex-matched controls. Muscle activity in the three segments within GMed and two segments of GMin were examined using intramuscular electromyography during step-up, step-down and side-step tasks. RESULTS Participants in the OA group demonstrated reduced muscle activity early in the step-up task and a later time to peak activity in most muscle segments. Greater activity was identified in anterior GMin in people with hip OA during the side-step task. A delay in time to peak activity was identified in most muscle segments in people with OA during the side-step task. SIGNIFICANCE For participants with OA, reduced activity in most muscle segments and increased time spent in double limb stance during the step-up task could reflect the decreased strength and pain associated with single limb stance on the affected limb. This study provides further evidence of altered function of the deep gluteal muscles in people with hip OA and highlights the importance of addressing these muscles in rehabilitation.
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Affiliation(s)
- Anita Zacharias
- Department of Pharmacy and Biomedical Sciences, College of Science, Health and Engineering, La Trobe University, Victoria, Australia; Sport, Exercise and Rehabilitation Research Focus Area, La Trobe University, Victoria, Australia.
| | - Tania Pizzari
- Sport, Exercise and Rehabilitation Research Focus Area, La Trobe University, Victoria, Australia; La Trobe University Sports and Exercise Medicine Research Centre, Victoria, Australia
| | - Adam I Semciw
- Sport, Exercise and Rehabilitation Research Focus Area, La Trobe University, Victoria, Australia; La Trobe University Sports and Exercise Medicine Research Centre, Victoria, Australia
| | - Daniel J English
- Department of Pharmacy and Biomedical Sciences, College of Science, Health and Engineering, La Trobe University, Victoria, Australia; Fusion Physiotherapy, Bendigo, Victoria, Australia
| | | | - Rodney A Green
- Department of Pharmacy and Biomedical Sciences, College of Science, Health and Engineering, La Trobe University, Victoria, Australia; Sport, Exercise and Rehabilitation Research Focus Area, La Trobe University, Victoria, Australia
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