Author:

Abstract:

Musculoskeletal and neurological disorders may result in a decreased functionality and gait deviations such as a decrease in gait velocity, asymmetry and compensatory movements. This has a major impact on the quality of life of the patients. One of the treatments can be an ankle-foot orthosis or AFO. To this day, it remains difficult to correlate the subject-specific functional requirements, imposed by the anatomical and pathological characteristics of the subject, to the required mechanical characteristics of the AFO. The required stiffness of the AFO is determined by the expertise and knowledge of the orthopedic technician, there is no standardized procedure to prescribe an AFO. The orthopedic technician uses his craftsmanship to fabricate an AFO, lets the patient walk with it and additional corrections are made by evaluating the gait of the patient. There is no methodology to predict the effect of an AFO on gait before the AFO is manufactured. Such a prediction would benefit clinical decision making and therefore functional outcome. Therefore, the aim of this research is to develop a method enabling the prediction of the functional effect of a specific AFO on a specific patient. This requires both a quantification of the stiffness of the AFO produced with specific design characteristics and an evaluation of the functional effect of the stiffness of the AFO on gait. To quantify the stiffness of the AFO, a literature review is performed and the parameters that influence both the stiffness of golden-standard polypropylene (PP) AFOs and the stresses occurring in those AFOs, are identified. Results of the literature review show that the stiffness of the AFO depends on material properties, thickness, trim line and shape at the level of the malleoli. Furthermore, it reveals that both material properties and thickness change in an uncontrollable way during the production process and that as a consequence the actual manual production techniques do not allow for sufficient control of AFO stiffness (determined by material properties and thickness). Therefore, two FE-models are developed to investigate the influence of the above mentioned changes on the stiffness of the AFO. Results show that these changes have a large effect on the resulting stiffness. To overcome these limitations in the manual production of PP-AFOs, selective laser sintering (SLS) is introduced as a more consistent and controllable production technique. The effectiveness of SLS-AFO on drop foot gait is assessed and a comparison is made between the clinical performance of SLS-AFOs and the clinical performance achieved using custom-molded PP-AFOs. Results indicate a significant beneficial effect of both custom-molded PP-AFO and customized SLS-AFO in terms of spatio-temporal gait parameters and ankle kinematic parameters compared to the barefoot walking. Furthermore, AFOs manufactured by SLS-technique show clinical performances that are at least equivalent to the handcrafted PP-AFOs commonly prescribed in current clinical practice. To evaluate the functional effect of varying AFO-stiffness on gait, first a study that quantifies the effect of the AFO on gait using both experimental and simulation-data is made. Results show that hypothesized effects of increasing AFO-stiffness on gait, like decreasing plantar flexion during loading response, are proved using predictive simulations but are not confirmed by the experimental data. These predictive simulations are control-based simulations where either the kinematics are used as an input (the controls) to evaluate muscle activations, or the muscle excitations are used as the input in a forward dynamic analysis to evaluate the kinematics. This formulation is however artificial as the AFO will tend to change both the patient's kinematic and muscle excitations. To allow a simultaneous change of the kinematic pattern and the muscle excitations during gait while remaining in a control-based algorithm, different formulations are proposed. Both single muscle compensation mechanisms and more optimal kinematic gait patterns can be suggested using these algorithms. Finally, an algorithm using musculoskeletal simulations to optimize the stiffness of the AFO based on the prediction of metabolic energy expenditure during gait is proposed. Resulting AFO-stiffnesses are realistic values but results also show that the kinematic input to the algorithm remains of great importance.