The capability to model human joint motion is a fundamental step towards the definition of effective treatments and medical devices, with an increasing request to adapt the devised models to the specificity of each subject. Joint models are also important for gait analysis, where they can be used to reduce the effect of skin artefact on the motion estimation accuracy [1]. Among the different models proposed for the ankle, spatial parallel mechanisms proved to replicate the natural tibiotalar motion with a high accuracy [2, 3] and were used to define models with both rigid and deformable ligaments [1]. These models start from the consideration, supported by relevant experimental analyses [2], that the natural tibiotalar motion has a single degree of freedom (1DOF), guided by the passive structures of the joint. They feature the main articular structures that guide the joint motion, namely articular contacts and isometric fibres of the tibiocalcaneal (TiCaL) and calcaneofibular (CaFiL) ligaments. The main limitation of these models is that they require a motion estimate of the subject to adjust the model parameters. An accurate estimation of the joint motion is difficult to obtain in vivo: non-invasive techniques can be inaccurate (skin-markers) or too complicated (fluoroscopy) for standard practice, while more invasive techniques (bone-pins) are not acceptable in several applications. A new technique was proposed recently that obtains the ankle natural motion by maximizing the joint congruence at all flexion angles [4]: it only requires the 3D model of articular surfaces, which can be obtained by medical images. In the present study, a procedure is developed that combines this technique and parallel mechanisms, in order to define spatial models that include the joint constraints and predict the tibiotalar natural motion of a specific subject from standard medical images. To validate the procedure, which is general and can be applied in vivo without the need to measure the patient articular motion, five ankles have been analyzed in vitro, experimentally measuring their natural motion by bone pins.

A personalized spatial model of the ankle motion from medical images / Nicola Sancisi, Michele Conconi, Vincenzo Parenti-Castelli. - STAMPA. - (2017), pp. 979-979. (Intervento presentato al convegno ISB 2017 tenutosi a Brisbane, Australia nel 23-27 luglio 2017).

A personalized spatial model of the ankle motion from medical images

Nicola Sancisi;Michele Conconi;Vincenzo Parenti-Castelli
2017

Abstract

The capability to model human joint motion is a fundamental step towards the definition of effective treatments and medical devices, with an increasing request to adapt the devised models to the specificity of each subject. Joint models are also important for gait analysis, where they can be used to reduce the effect of skin artefact on the motion estimation accuracy [1]. Among the different models proposed for the ankle, spatial parallel mechanisms proved to replicate the natural tibiotalar motion with a high accuracy [2, 3] and were used to define models with both rigid and deformable ligaments [1]. These models start from the consideration, supported by relevant experimental analyses [2], that the natural tibiotalar motion has a single degree of freedom (1DOF), guided by the passive structures of the joint. They feature the main articular structures that guide the joint motion, namely articular contacts and isometric fibres of the tibiocalcaneal (TiCaL) and calcaneofibular (CaFiL) ligaments. The main limitation of these models is that they require a motion estimate of the subject to adjust the model parameters. An accurate estimation of the joint motion is difficult to obtain in vivo: non-invasive techniques can be inaccurate (skin-markers) or too complicated (fluoroscopy) for standard practice, while more invasive techniques (bone-pins) are not acceptable in several applications. A new technique was proposed recently that obtains the ankle natural motion by maximizing the joint congruence at all flexion angles [4]: it only requires the 3D model of articular surfaces, which can be obtained by medical images. In the present study, a procedure is developed that combines this technique and parallel mechanisms, in order to define spatial models that include the joint constraints and predict the tibiotalar natural motion of a specific subject from standard medical images. To validate the procedure, which is general and can be applied in vivo without the need to measure the patient articular motion, five ankles have been analyzed in vitro, experimentally measuring their natural motion by bone pins.
2017
Proceedings of XXVI Congress of the International Society of Biomechanics
979
979
A personalized spatial model of the ankle motion from medical images / Nicola Sancisi, Michele Conconi, Vincenzo Parenti-Castelli. - STAMPA. - (2017), pp. 979-979. (Intervento presentato al convegno ISB 2017 tenutosi a Brisbane, Australia nel 23-27 luglio 2017).
Nicola Sancisi, Michele Conconi, Vincenzo Parenti-Castelli
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/627181
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