The starting point is the recently developed TLEM which will undergo rigid validation under multiple circumstances. In addition, the underlying theoretical concepts built-in in the model and muscle activities will be validated using extensive measurements on healthy subjects.

A marker-free structured light based measurement method is further developed and tested on the normal subjects, which allows to measure kinematics on the patients (later in the project) without the requirement of reflective markers.

Since individual M-S characteristics may differ considerably between  subjects, we will develop and validate state of the art 3-D image analysis techniques to distract important parameters to create 3-D patient-specific models.

The developed patient-specific models should predict a different functional outcome for different individuals as measured in the healthy subjects. In addition, the model predictions should be concurrent with the measured parameters (e.g. glucose metabolism, oxygen consumption and muscle alignment).

Next, an interactive link is generated between the M-S model and the surgeon. Using virtual reality algorithms, the surgeon can modify the M-S model of his patient to simulate his operative plan. The module should allow 3-D visualization and modification of the parameterized M-S system of the patient.

Functional patient measurements are performed before and after surgery. The kinematic measurements are done using the new marker-free structured light based method. The measurements will allow to exactly quantify the functional effect of the surgical intervention. This will be compared to predictions of the patient-specific models and the difference will be quantified and is assumed to be caused by the adaptive capacity of patients. This adaptive capacity that is until now missing in M-S models will therefore be quantified and implemented.

The predictions of TLEM are mathematical and as such not usable for surgeons. Therefore, a pre- and post-processing facility is created which ‘hides’ the complex mathematical formulations and allows clinical interpretation of the results of the simulated surgical interventions for the surgeons.

A computer navigation module is developed that transfers the surgical plan as selected by the surgeon after performing an interactive surgical session on the M-S model of his patient. This allows the surgeon to perform the operation exactly as pre-operatively found optimally. The selected operative plan is fed into the navigation system to guide the surgeon through the surgery in a step-wise manner.

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