People involved from BSS
2015 – 2018
KNEEMO is the Initial Training Network (ITN) for knee osteoarthritis research funded through the European Commission’s Framework 7 Programme. It includes 15 research fellows employed at eight different host institutions.
University of Twente is involved as an associated partner in KNEEMO ITN providing supervision and training, in close collaboration with the industrial partner Xsens Technologies B.V..
The overall aim of KNEEMO ITN is join up the European research effort in knee osteoarthritis, to thus provide a step-change in the understanding and non-pharmacological management of the disease through early identification and personalized interventions.
- Objective 1: To provide personalized biomechanical knee models
- Objective 2: To enable the timely web of patients at high risk of developing OA, or with a poor initial prognosis
- Objective 3: To design and evaluate new technology for biomechanical assessments
- Objective 4: To develop personalised (targeted and tailored) interventions
The contribution of BSS/UTwente and Xsens within the KNEEMO network focuses on the 3rd objective. More specifically the project objective is to develop a remote-sensing measurement system for physical activity and knee joint load monitoring in free-living environments.
The research theme of the KNEEMO ITN is “towards targeted and tailored interventions for knee osteoarthritis”, and focuses on identifying the right patients for the right treatment at the right time. Research areas include anatomy, musculoskeletal modelling, prevention and early identification of patients, epidemiology, biomechanical mechanisms, and intervention studies. Knee Osteoarthritis (KOA) is the most common chronic musculoskeletal disorder, currently affecting over 8 million people within the EU, for which currently no cure is available. Adverse biomechanics, affected through some of the major health issues of our time (ageing, obesity, sedentary lifestyle) lie at the heart of the disease.
Knee joint medial contact force is a crucial factor in knee osteoarthritis, contributing to the degeneration of the cartilage. Its non-invasive assessment is not yet possible though, therefore surrogate measures as the frontal and sagittal plane net knee moments have been suggested. However, their estimation requires a gait laboratory with optical motion capture and force plate systems. Therefore, these measures cannot be monitored outside a laboratory, for instance in a clinic or during the patients’ daily lives. A system able to estimate net moments and possibly net contact forces, and afterwards drive a real-time biofeedback to offload the joint, would be useful in the diagnosis, prevention and rehabilitation phase of the knee osteoarthritis patients.
Use of inertial measurement units to track the human movement has emerged to a powerful technique during the last decade. The most important advantage of this approach is that it can be used in almost any environment without any laboratory space restrictions. A number of IMUs is fused using a scaled biomechanical model, to derive the human body kinematics. Recent advances in biomechanical analysis techniques allowed also the prediction of kinetics through marker-based kinematic data. This opens a new door in applying these methods in inertial motion capture systems, in order to derive the ground reaction and lower limb forces and moments at any environment.