The effectiveness of a 6-week biofeedback gait retraining programme in people with knee osteoarthritis: protocol for a randomised controlled trial

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Background

Gait retraining is a common therapeutic intervention that can alter gait characteristics to reduce knee loading in knee osteoarthritis populations. It can be enhanced when combined with biofeedback that provides real-time information about the users’ gait, either directly (i.e. knee moment feedback) or indirectly (i.e. gait pattern feedback). However, it is unknown which types of biofeedback are more effective at reducing knee loading, and also how the changes in gait affect pain during different activities of daily living. Therefore, this study aims to evaluate the acute (6 weeks of training) and chronic (1 month post training) effects of biofeedback based on personalised gait patterns to reduce knee loading and pain in people with knee osteoarthritis, as well as examine if more than one session of knee moment feedback is needed to optimise the gait patterns.

Methods

This is a parallel group, randomised controlled trial in a symptomatic knee osteoarthritis population in which participants will be randomised into either a knee moment biofeedback group ( n = 20), a gait pattern biofeedback group ( n = 20) or a control group ( n = 10). Supervised training sessions will be carried out weekly for six continuous weeks, with real-time biofeedback provided using marker-based motion capture and an instrumented treadmill. Baseline, post-intervention and 1-month follow-up assessments will be performed to measure knee loading parameters, gait pattern parameters, muscle activation, knee pain and functional ability.

Discussion

This study will identify the optimal gait patterns for participants’ gait retraining and compare the effectiveness of gait pattern biofeedback to a control group in reducing knee loading and index knee pain. Additionally, this study will explore how many sessions are needed to identify the optimal gait pattern with knee moment feedback. Results will be disseminated in future peer-reviewed journal articles, conference presentations and internet media to a wide audience of clinicians, physiotherapists, researchers and individuals with knee osteoarthritis.

Trial registration

This study was retrospectively registered under the International Standard Randomised Controlled Trial Number registry on 7th March 2023 (ISRCTN28045513).

Related collections

Most cited references 33

Record: found
Abstract: found
Article: not found

The global burden of hip and knee osteoarthritis: estimates from the global burden of disease 2010 study.

Marita Cross, Emma Smith, Damian Hoy … (2014)

To estimate the global burden of hip and knee osteoarthritis (OA) as part of the Global Burden of Disease 2010 study and to explore how the burden of hip and knee OA compares with other conditions. Systematic reviews were conducted to source age-specific and sex-specific epidemiological data for hip and knee OA prevalence, incidence and mortality risk. The prevalence and incidence of symptomatic, radiographic and self-reported hip or knee OA were included. Three levels of severity were defined to derive disability weights (DWs) and severity distribution (proportion with mild, moderate and severe OA). The prevalence by country and region was multiplied by the severity distribution and the appropriate disability weight to calculate years of life lived with disability (YLDs). As there are no deaths directly attributed to OA, YLDs equate disability-adjusted life years (DALYs). Globally, of the 291 conditions, hip and knee OA was ranked as the 11th highest contributor to global disability and 38th highest in DALYs. The global age-standardised prevalence of knee OA was 3.8% (95% uncertainty interval (UI) 3.6% to 4.1%) and hip OA was 0.85% (95% UI 0.74% to 1.02%), with no discernible change from 1990 to 2010. Prevalence was higher in females than males. YLDs for hip and knee OA increased from 10.5 million in 1990 (0.42% of total DALYs) to 17.1 million in 2010 (0.69% of total DALYs). Hip and knee OA is one of the leading causes of global disability. Methodological issues within this study make it highly likely that the real burden of OA has been underestimated. With the aging and increasing obesity of the world's population, health professions need to prepare for a large increase in the demand for health services to treat hip and knee OA. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

0 comments Cited 681 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

GGIR: A Research Community–Driven Open Source R Package for Generating Physical Activity and Sleep Outcomes From Multi-Day Raw Accelerometer Data

Jairo H Migueles, Alex V Rowlands, Florian Huber … (2019)

Recent technological advances have transformed the research on physical activity initially based on questionnaire data to the most recent objective data from accelerometers. The shift to availability of raw accelerations has increased measurement accuracy, transparency, and the potential for data harmonization. However, it has also shifted the need for considerable processing expertise to the researcher. Many users do not have this expertise. The R package GGIR has been made available to all as a tool to convermulti-day high resolution raw accelerometer data from wearable movement sensors into meaningful evidence-based outcomes and insightful reports for the study of human daily physical activity and sleep. This paper aims to provide a one-stop overview of GGIR package, the papers underpinning the theory of GGIR, and how research contributes to the continued growth of the GGIR package. The package includes a range of literature-supported methods to clean the data and provide day-by-day, as well as full recording, weekly, weekend, and weekday estimates of physical activity and sleep parameters. In addition, the package also comes with a shell function that enables the user to process a set of input files and produce csv summary reports with a single function call, ideal for users less proficient in R. GGIR has been used in over 90 peer-reviewed scientific publications to date. The evolution of GGIR over time and widespread use across a range of research areas highlights the importance of open source software development for the research community and advancing methods in physical behavior research.

0 comments Cited 235 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Agreement between methods of measurement with multiple observations per individual.

J Bland, Douglas G. Altman (2007)

Limits of agreement provide a straightforward and intuitive approach to agreement between different methods for measuring the same quantity. When pairs of observations using the two methods are independent, i.e., on different subjects, the calculations are very simple and straightforward. Some authors collect repeated data, either as repeated pairs of measurements on the same subject, whose true value of the measured quantity may be changing, or more than one measurement by one or both methods of an unchanging underlying quantity. In this paper we describe methods for analysing such clustered observations, both when the underlying quantity is assumed to be changing and when it is not.

0 comments Cited 211 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Yi Wan: yw2984@bath.ac.uk

Journal

Journal ID (nlm-ta): BMC Musculoskelet Disord

Journal ID (iso-abbrev): BMC Musculoskelet Disord

Title: BMC Musculoskeletal Disorders

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2474

Publication date (Electronic): 19 December 2023

Publication date PMC-release: 19 December 2023

Publication date Collection: 2023

Volume: 24

Electronic Location Identifier: 984

Affiliations

[1 ]Department for Health, University of Bath, ( https://ror.org/002h8g185) Bath, UK

[2 ]Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA), University of Bath, ( https://ror.org/002h8g185) Bath, UK

[3 ]Centre for Sport Exercise and Osteoarthritis Research Versus Arthritis, University of Bath, ( https://ror.org/002h8g185) Bath, UK

Article

Publisher ID: 7098

DOI: 10.1186/s12891-023-07098-y

PMC ID: 10729376

PubMed ID: 38114980

SO-VID: 87417158-da10-49aa-9880-b87202e08bc5

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 23 May 2023

Date accepted : 6 December 2023

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100000266, Engineering and Physical Sciences Research Council;

Award ID: EP/T014865/1

Funded by: FundRef http://dx.doi.org/10.13039/501100004543, China Scholarship Council;

Custom metadata

ScienceOpen disciplines: Orthopedics

Keywords: knee osteoarthritis,knee loading,gait retraining,biofeedback,biomechanics,stair,sit-to-stand

Data availability:

ScienceOpen disciplines: Orthopedics

Keywords: knee osteoarthritis, knee loading, gait retraining, biofeedback, biomechanics, stair, sit-to-stand

The effectiveness of a 6-week biofeedback gait retraining programme in people with knee osteoarthritis: protocol for a randomised controlled trial

Read this article at

Abstract

Background

Methods

Discussion

Trial registration

Related collections

Orthopedics

Most cited references 33

The global burden of hip and knee osteoarthritis: estimates from the global burden of disease 2010 study.

GGIR: A Research Community–Driven Open Source R Package for Generating Physical Activity and Sleep Outcomes From Multi-Day Raw Accelerometer Data

Agreement between methods of measurement with multiple observations per individual.

Author and article information

Contributors

Journal

Affiliations

Article

History

Funding

Categories

Custom metadata

Comments

Comment on this article

Similar content 626

Most referenced authors 279