Human Motion, Orthopaedics, Sports Medicine and Digital Methods
The HOSD platform aims to understand how human movement and physical activity and their behavioural, functional and performance dimensions serve as outcome measures, diagnostic biomarkers and modality for treatment, prevention or delay in many disease areas.
The HOSD platform aims to understand and exploit towards clinical trials and practice how human movement and physical activity and their behavioural, functional and (sports) performance dimensions serve as outcome measures, (early) diagnostic biomarkers and modality for treatment, prevention or delay in many disease areas. This particularly applies to where the musculoskeletal system is directly affected, e.g. in orthopaedics and sports injury but also where the effects are less direct but evident, such as with neurodegenerative diseases and other NCD’s of high patient and socioeconomic burden such as cancer, diabetes, multiple sclerosis or ageing. Here activity profiles and movement patterns are also relevant for patient stratification into clinical trials.
We conduct and support research related to the systematic assessment of human movement biomechanics, physical activity behaviour, functional performance and associated biometrics using lab-based methods (3D motion capture, force plates), portable, ambulant or remote methods for out-of-lab and free-field measurements, as well as real-life monitoring using e.g. wearable devices, sensors or other digital tools including electronic patient self-reports, experience sampling methods and multi-modal approaches. Our activities comprise the development, selection, configuration, technical and clinical validation and application of such methods in research and clinical practice in translational (from bench-to-bed and back) and transversal (across medical disciplines and diseases) manners. These activities naturally interface with biosignal processing and data science methods such as machine learning.
WATCH 📺 – Motion Capture with markerless and monocular AI-driven systems – New tools for digital health
Projects & clinical trials
Some of the group’s research projects include:
- 3D motion analysis of gait, run and hop-test as a routine clinical tool to objectify clinical outcomes following anterior cruciate ligament (ACL) surgery.
- Identifying 3D motion and physical activity biomarkers in patients after anterior cruciate ligament (ACL) reconstruction towards preventing injury relapse, safe return-to-play and predicting outcome for individualised rehabilitation (S-TRAINING).
- Pre-operative gait analysis and activity monitoring to support patient-specific surgical planning of knee ostetomies for personalised medicine and improved outcomes.
- Early and remote diagnostics of knee osteoarthritis via mobility biomarkers from wearable activity monitors – development and validation.
- Combining app-based patient self-reports, symptom diaries and triggered functional test assessed with a wearable monitor (“guided routines”) towards understanding how perception of pain, joint stiffness or instability affects functional performance and habitual activity levels and vice-versa.
Featured team members
Gait asymmetry in spatiotemporal and kinetic variables does not increase running-related injury risk in lower limbs – 07/12/2023
Case report – 13/12/2023
Surgical technique – 13/12/2023
A systematic approach to managing complications after proximal tibial osteotomies of the knee – 06/12/2023
A practical guide to the implementation of AI in orthopaedic research – part 1 – 16/11/2023
Management of anterior cruciate ligament revision in adults – 01/01/2023
The posterior cruciate ligament–posterior femoral cortex angle (PCL–PCA) and the lateral collateral ligament (LCL) sign are useful parameters to indicate the progression of knee decompensation over time after an ACL injury – 01/01/2023
Reference Values and Determinants of Spatiotemporal and Kinetic Variables in Recreational Runners – 19/10/2023
Selecting the best compositions of a wheelchair basketball team: a data-driven approach – 05/10/2023
Accelerated evidence synthesis in orthopaedics—the roles of natural language processing, expert annotation and large language models – 28/09/2023
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