Integrating wearables and modelling for monitoring rehabilitation following total knee joint replacement

• Published in: Computer methods and programs in biomedicine 2022-10, Vol.225, p.107063-107063, Article 107063
• Main Authors: Yeung, S., Kim, H.K., Carleton, A., Munro, J., Ferguson, D, Monk, A.P., Zhang, J., Besier, T., Fernandez, J.
• Format: Article
• Language: English
• ISSN: 0169-2607; 1872-7565
• DOI: 10.1016/j.cmpb.2022.107063

•Wearable computed ‘tibial shock’ is a good surrogate for knee joint contact force from computer modelling.•Wearables showed 20% of patients did not improve knee joint loading.•Traditional patient related outcome measures did not detect these patient changes.•This study has important implications for improving patient outcomes, equity, and for those who live in rural regions.•To our knowledge no other studies exist in the literature evaluating the use of wearables and modelling together following total knee replacement surgery. Wearable inertial devices integrated with modelling and cloud computing have been widely adopted in the sports sector, however, their use in the health and medical field has yet to be fully realised. To date, there have been no reported studies concerning the use of wearables as a surrogate tool to monitor knee joint loading during recovery following a total knee joint replacement. The objective of this study is to firstly evaluate if peak tibial acceleration from wearables during gait is a good surrogate metric for computer modelling predicted functional knee loading; and secondly evaluate if traditional clinical patient related outcomes measures are consistent with wearable predictions. Following ethical approval, four healthy participants were used to establish the relationship between computer modelling predicted knee joint loading and wearable measured tibial acceleration. Following this, ten patients who had total knee joint replacements were then followed during their 6-week rehabilitation. Gait analysis, wearable acceleration, computer models of knee joint loading, and patient related outcomes measures including the Oxford knee score and range of motion were recorded. A linear correlation (R2 of 0.7–0.97) was observed between peak tibial acceleration (from wearables) and musculoskeletal model predicted knee joint loading during gait in healthy participants first. Whilst patient related outcome measures (Oxford knee score and patient range of motion) were observed to improve consistently during rehabilitation, this was not consistent with all patient's tibial acceleration. Only those patients that exhibited increasing peak tibial acceleration over 6-weeks rehabilitation were positively correlated with the Oxford knee score (R2 of 0.51 to 0.97). Wearable predicted tibial acceleration revealed three patients with a consistent knee loading, five patients with improving knee loading, and two patients with declining knee loading d