Forced orthodontic extrusion for an apparently hopeless anterior tooth by using a simplified approach

When restoring severely compromised teeth, respecting the supracrestal tissue attachment and retaining the most coronal and radicular tooth structure is essential to achieving a sufficient ferrule. Forced orthodontic extrusion is a minimally invasive method that allows hard- and soft-tissue conservation. This article describes the treatment of a severely damaged maxillary central incisor that was managed by using a simplified orthodontic extrusion method with intracoronal elastic and metal ligatures applied through a palatal bar and followed by the biologically oriented preparation technique (BOPT). This orthodontic procedure reduces a forward clockwise advance during vertical extrusion, thus maintaining the buccal bone plate.

Computer-based test-bed for clinical assessment of hand/wrist feed-forward neuroprosthetic controllers using artificial neural networks

Neuroprosthestic systems can be used to restore hand grasp and wrist control in individuals with C5/C6 spinal cord injury. A computer-based system was developed for the implementation, tuning and clinical assessment of neuroprosthetic controllers, using off-the-shelf hardware and software. The computer system turned a Pentium III PC running Windows NT into a non-dedicated, real-time system for the control of neuroprostheses. Software execution (written using the high-level programming languages LabVIEW and MATLAB) was divided into two phases: training and real-time control. During the training phase, the computer system collected input/output data by stimulating the muscles and measuring the muscle outputs in real-time, analysed the recorded data, generated a set of training data and trained an artificial neural network (ANN)-based controller. During real-time control, the computer system stimulated the muscles using stimulus pulsewidths predicted by the ANN controller in response to a sampled input from an external command source, to provide independent control of hand grasp and wrist posture. System timing was stable, reliable and capable of providing muscle stimulation at frequencies up to 24Hz. To demonstrate the application of the test-bed, an ANN-based controller was implemented with three inputs and two independent channels of stimulation. The ANN controller's ability to control hand grasp and wrist angle independently was assessed by quantitative comparison of the outputs of the stimulated muscles with a set of desired grasp or wrist postures determined by the command signal. Controller performance results were mixed, but the platform provided the tools to implement and assess future controller designs.