2021
DOI: 10.1080/14763141.2021.1959947
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The future of in-field sports biomechanics: wearables plus modelling compute real-time in vivo tissue loading to prevent and repair musculoskeletal injuries

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Cited by 29 publications
(23 citation statements)
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“…Accordingly, new technologies such as wearable sensors (e.g. inertial measurement units, foot force/pressure sensing insoles) and marker-less motion tracking combined with evolving machine learning algorithms may help to advance insights into the inter-limb braking demands of horizontal deceleration, alongside whole body deceleration performance outcomes [ 51 , 125 ]. Given that horizontal decelerations during match play are largely unanticipated, future research should seek to determine how the importance of the biomechanical and neuromuscular determinants identified here for pre-planned horizontal deceleration ability might differ in their associations with un-anticipated horizontal deceleration ability.…”
Section: Limitations and Future Research Directionsmentioning
confidence: 99%
“…Accordingly, new technologies such as wearable sensors (e.g. inertial measurement units, foot force/pressure sensing insoles) and marker-less motion tracking combined with evolving machine learning algorithms may help to advance insights into the inter-limb braking demands of horizontal deceleration, alongside whole body deceleration performance outcomes [ 51 , 125 ]. Given that horizontal decelerations during match play are largely unanticipated, future research should seek to determine how the importance of the biomechanical and neuromuscular determinants identified here for pre-planned horizontal deceleration ability might differ in their associations with un-anticipated horizontal deceleration ability.…”
Section: Limitations and Future Research Directionsmentioning
confidence: 99%
“…Moreover, every athlete (and so every patient) moves differently and such variability further complicates the interpretation of the data. Recent works are facing these issues by proposing innovative approaches (like Principal Component Analysis, joint coordination analysis) aiming to provide a comprehensive understanding of patients’ motion [ 18 , 34 , 76 ]. The goal will be to cluster patients into safe or at-risk bands according to the biomechanical and neuromuscular profile.…”
Section: Smart Technology Requires Smart Thinking Firstmentioning
confidence: 99%
“…However, the estimation of joint loads requires force platforms and can be rarely used outside the lab context. Different options have been proposed to overcome this issue such as the use of musculoskeletal models to predict ground reaction forces and ACL strains from IMUs peak accelerations (Di Paolo et al, 2021; Lloyd, 2021). Regression models and machine learning are state‐of‐art statistical approaches for joint loads estimation outside the laboratory (Giarmatzis, Zacharaki, & Moustakas, 2020).…”
Section: Discussionmentioning
confidence: 99%