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Background: Exercise-based approaches have been a cornerstone of physiotherapy management of knee osteoarthritis for many years. However, clinical effects are considered small to modest and the need for continued adherence identified as a barrier to clinical efficacy. While exercise-based approaches focus on muscle strengthening, biomechanical research has identified that people with knee osteoarthritis over activate their muscles during functional tasks. Therefore, we aimed to create a new behavioural intervention, which integrated psychologically informed practice with biofeedback training to reduce muscle overactivity, and which was suitable for delivery by a physiotherapist., Methods: Through literature review, we created a framework linking theory from pain science with emerging biomechanical concepts related to overactivity of the knee muscles. Using recognised behaviour change theory, we then mapped a set of intervention components which were iteratively developed through ongoing testing and consultation with patients and physiotherapists., Results: The underlying framework incorporated ideas related to central sensitisation, motor responses to pain and also focused on the idea that increased knee muscle overactivity could result from postural compensation. Building on these ideas, we created an intervention with five components: making sense of pain, general relaxation, postural deconstruction, responding differently to pain and functional muscle retraining. The intervention incorporated a range of animated instructional videos to communicate concepts related to pain and biomechanical theory and also used EMG biofeedback to facilitate visualization of muscle patterns. User feedback was positive with patients describing the intervention as enabling them to "create a new normal" and to be "in control of their own treatment." Furthermore, large reductions in pain were observed from 11 patients who received a prototype version of the intervention., Conclusion: We have created a new intervention for knee osteoarthritis, designed to empower individuals with capability and motivation to change muscle activation patterns and beliefs associated with pain. We refer to this intervention as Cognitive Muscular Therapy. Preliminary feedback and clinical indications are positive, motivating future large-scale trials to understand potential efficacy. It is possible that this new approach could bring about improvements in the pain associated with knee osteoarthritis without the need for continued adherence to muscle strengthening programmes., Trial Registration: ISRCTN51913166 (Registered 24-02-2020, Retrospectively registered).

Background: Appropriate footwear for individuals with diabetes but no ulceration history could reduce the risk of first ulceration. However, individuals who deem themselves at low risk are unlikely to seek out bespoke footwear which is personalised. Therefore, our primary aim was to investigate whether group-optimised footwear designs, which could be prefabricated and delivered in a retail setting, could achieve appropriate pressure reduction, or whether footwear selection must be on a patient-by-patient basis. A second aim was to compare responses to footwear design between healthy participants and people with diabetes in order to understand the transferability of previous footwear research, performed in healthy populations., Methods: Plantar pressures were recorded from 102 individuals with diabetes, considered at low risk of ulceration. This cohort included 17 individuals with peripheral neuropathy. We also collected data from 66 healthy controls. Each participant walked in 8 rocker shoe designs (4 apex positions × 2 rocker angles). ANOVA analysis was then used to understand the effect of two design features and descriptive statistics used to identify the group-optimised design. Using 200 kPa as a target, this group-optimised design was then compared to the design identified as the best for each participant (using plantar pressure data)., Results: Peak plantar pressure increased significantly as apex position was moved distally and rocker angle reduced ( p  < 0.001). The group-optimised design incorporated an apex at 52% of shoe length, a 20° rocker angle and an apex angle of 95°. With this design 71-81% of peak pressures were below the 200 kPa threshold, both in the full cohort of individuals with diabetes and also in the neuropathic subgroup. Importantly, only small increases (<5%) in this proportion were observed when participants wore footwear which was individually selected. In terms of optimised footwear designs, healthy participants demonstrated the same response as participants with diabetes, despite having lower plantar pressures., Conclusions: This is the first study demonstrating that a group-optimised, generic rocker shoe might perform almost as well as footwear selected on a patient by patient basis in a low risk patient group. This work provides a starting point for clinical evaluation of generic versus personalised pressure reducing footwear.

Background: Both increased knee muscle co-contraction and alterations in central pain processing have been suggested to play a role in knee osteoarthritis pain. However, current interventions do not target either of these mechanisms. The Alexander Technique provides neuromuscular re-education and may also influence anticipation of pain. This study therefore sought to investigate the potential clinical effectiveness of the AT intervention in the management of knee osteoarthritis and also to identify a possible mechanism of action., Methods: A cohort of 21 participants with confirmed knee osteoarthritis were given 20 lessons of instruction in the Alexander Technique. In addition to clinical outcomes EMG data, quantifying knee muscle co-contraction and EEG data, characterising brain activity during anticipation of pain, were collected. All data were compared between baseline and post-intervention time points with a further 15-month clinical follow up. In addition, biomechanical data were collected from a healthy control group and compared with the data from the osteoarthritis subjects., Results: Following AT instruction the mean WOMAC pain score reduced by 56 % from 9.6 to 4.2 (P < 0.01) and this reduction was maintained at 15 month follow up. There was a clear decrease in medial co-contraction at the end of the intervention, towards the levels observed in the healthy control group, both during a pre-contact phase of gait (p < 0.05) and during early stance (p < 0.01). However, no changes in pain-anticipatory brain activity were observed. Interestingly, decreases in WOMAC pain were associated with reductions in medial co-contraction during the pre-contact phase of gait., Conclusions: This is the first study to investigate the potential effectiveness of an intervention aimed at increasing awareness of muscle behaviour in the clinical management of knee osteoarthritis. These data suggest a complex relationship between muscle contraction, joint loading and pain and support the idea that excessive muscle co-contraction may be a maladaptive response in this patient group. Furthermore, these data provide evidence that, if the activation of certain muscles can be reduced during gait, this may lead to positive long-term clinical outcomes. This finding challenges clinical management models of knee osteoarthritis which focus primarily on muscle strengthening., Trial Registration: ISRCTN74086288 , 4th January 2016, retrospectively registered.

Background: Textile-based transducers are an emerging technology in which piezo-resistive properties of materials are used to measure an applied strain. By incorporating these sensors into a sock, this technology offers the potential to detect critical events during the stance phase of the gait cycle. This could prove useful in several applications, such as functional electrical stimulation (FES) systems to assist gait., Methods: We investigated the output of a knitted resistive strain sensor during walking and sought to determine the degree of similarity between the sensor output and the ankle angle in the sagittal plane. In addition, we investigated whether it would be possible to predict three key gait events, heel strike, heel lift and toe off, with a relatively straight-forward algorithm. This worked by predicting gait events to occur at fixed time offsets from specific peaks in the sensor signal., Results: Our results showed that, for all subjects, the sensor output exhibited the same general characteristics as the ankle joint angle. However, there were large between-subjects differences in the degree of similarity between the two curves. Despite this variability, it was possible to accurately predict gait events using a simple algorithm. This algorithm displayed high levels of trial-to-trial repeatability., Conclusions: This study demonstrates the potential of using textile-based transducers in future devices that provide active gait assistance.