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A qualitative evaluation of acceptability of a clinical sensor-based movement feedback rehabilitation in patients following anterior cruciate ligament reconstruction

Nicholas, Kevin ORCID:, Al-Amri, Mohammad ORCID:, Davies, Jennifer ORCID:, Hamana, Katy ORCID:, Sparkes, Valerie ORCID: and Button, Kate ORCID: 2022. A qualitative evaluation of acceptability of a clinical sensor-based movement feedback rehabilitation in patients following anterior cruciate ligament reconstruction. Presented at: Osteoarthritis Research Society International Conference, Berlin, Germany, 7-10 April 2022. Osteoarthritis and Cartilage. , vol.30 (30 s1) Elsevier, S392- S392. 10.1016/j.joca.2022.02.527

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Purpose: The identification and assessment by physiotherapists of movement adaptations during functional tasks in people following knee injury is subjective, relying on observational skill to detect potential risk factors. It is a challenge to identify movement patterns in both lower limbs at three joints, each with six planes of movement whilst performing tasks. Technology now exists to improve the objective identification of compensation strategies through using wearable biomechanical sensors in the clinic. Therefore, an intervention is being developed that provides the treating physiotherapist and patient with a movement feedback report, based on the assessment using inertial sensors. In providing objectivity it has potential to improve confidence and reassurance in the understanding of biomechanics related to sub-optimal recovery and re-injury presented in a format that can be understood by the physiotherapist and patient. In doing so, personalised, and tailored treatment approaches can be developed to target the movement adaptations associated with this patient population. The physiotherapist acceptability and usability has been explored as part of the development of a new biomechanically informed movement feedback intervention. The aim of this study was to evaluate patient experience and acceptance of the sensor-based movement feedback during rehabilitation. Methods: A serial qualitative semi-structured interview methodology was used on a convenience sample of nine anterior cruciate ligament reconstruction (ACLR), 6-52 weeks following surgery and underwent sensor-based movement analysis in the clinic (16 interviews). Patients performed up to five functional tasks (typical of their usual care, stage of recovery and physical capabilities) whilst wearing seventeen MTw2 sensors, full-body set-up (Xsens technologies BV, Enschede, The Netherlands). Tasks included: gait, double leg squat, single leg squat, stairs, vertical jump. Biomechanical data (pelvis and lower limbs) were extracted using Xsens MVN Analyze and custom-written MATLAB toolkit used to generate the feedback report. The report contained; temporo-spatial and kinematic lower limb waveform data (average and consistency graphs) and avatars in the sagittal and frontal planes. Qualitative data was collected via semi-structured serial interviews in two stages. Stage 1: prior to sensor-based experience, semi-structured interviews explored views about rehabilitation and technology use, followed. This was followed by movement analysis data collection using the sensors. The physiotherapist and patient were provided digital copies of the movement feedback report. Stage 2: semi-structured serial interviews were completed on average two weeks after stage one. Interviews explored how the feedback was integrated into rehabilitation, its influence on their rehabilitation engagement, and opinions on feedback development for future use. Interviews were transcribed verbatim and 75% of the transcripts were dual coded achieving a high level of agreement. Data was uploaded to NVivo and analysed using inductive thematic analysis to develop codes, sub-themes, and key-themes. Results: Four key themes were identified from the pre-experience interviews, and three themes in the post-sensor feedback. The themes, codes and code descriptions are detailed in Tables 1 (pre-sensor-based feedback) and Table 2 (post sensor-based movement feedback). Conclusions: The participants were already using a variety of technology in their everyday lives including the technology to assist them with exercising. They were receptive to the use of wearable sensor technology alongside their physiotherapy to provide objective data that could inform treatment selection and monitor progress. The sensor-based biomechanical feedback was usable and acceptable to the ACLR patients. The sensor feedback has the potential to motivate and educate patients about their rehabilitation by providing quantifiable data presented in a visual digital format. There was variability in patient understanding of the feedback which depended on the volume of data presented and the biomechanical terminology used. The importance of the physiotherapist to interpret and apply the sensor-based feedback findings was identified to be crucial to patient engagement. A plan for integrating sensor-based movement feedback into rehabilitation, which defines who provides the feedback, the nature of the feedback, setting, frequency, amount, and tailoring is proposed and guided by the Template for Intervention.

Item Type: Conference or Workshop Item (Poster)
Date Type: Publication
Status: Published
Schools: Healthcare Sciences
Publisher: Elsevier
ISSN: 1063-4584
Date of First Compliant Deposit: 1 October 2022
Date of Acceptance: 28 March 2022
Last Modified: 24 Mar 2023 02:07

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