Abstract: Disclosed herein is a current control for a lighting assembly, which may be an LED lighting assembly, which may be a pulse width modulated (“PWM”) current control or other form of current control where each current-controlled unit is uniquely addressable and capable of receiving illumination color information on a computer lighting network. In an embodiment, the invention includes a binary tree network configuration of lighting units (nodes). In another embodiment, the present invention comprises a heat dissipating housing, made out of a heat-conductive material, for housing the lighting assembly. The heat dissipating housing contains two stacked circuit boards holding respectively the power module and the light module. The light module is adapted to be conveniently interchanged with other light modules.

Abstract: An apparatus for facilitating the implantation of an artificial component in one of a hip joint, a knee joint, a hand and wrist joint, an elbow joint, a shoulder joint, and a foot and ankle joint. The apparatus includes a pre-operative geometric planner and a pre-operative kinematic biomechanical simulator in communication with the pre-operative geometric planner.

Abstract: Apparatuses and methods are disclosed for determining an implant position for at least one artificial component in a joint and facilitating the implantation thereof. The apparatuses and methods include creating a joint model of a patient's joint into which an artificial component is to be implanted and creating a component model of the artificial component. The joint and artificial component models are used to stimulate movement in the patient's joint with the artificial component in a test position. The component model and the joint model are used to calculate a range of motion in the joint for at least one test position based on the simulated motion. An implant position, including angular orientation, in the patient's joint is determined based on a predetermined range of motion and the calculated range of motion.

Abstract: Apparatuses and methods are disclosed for determining an implant position for at least one artificial component in a joint and facilitating the implantation thereof. The apparatuses and methods include creating a joint model of a patient's joint into which an artificial component is to be implanted and creating a component model of the artificial component. The joint and artificial component models are used to simulate movement in the patient's joint with the artificial component in a test position. The component model and the joint model are used to calculate a range of motion in the joint for at least one test position based on the simulated motion. An implant position, including angular orientation, in the patient's joint is determined based on a predetermined range of motion and the calculated range of motion.

Abstract: Apparatuses and methods are disclosed for determining an implant position for at least one artificial component in a joint and facilitating the implantation thereof. The apparatuses and methods include creating a joint model of a patient's joint into which an artificial component is to be implanted and creating a component model of the artificial component. The joint and artificial component models are used to simulate movement in the patient's joint with the artificial component in a test position. The component model and the joint model are used to calculate a range of motion in the joint for at least one test position based on the simulated motion. An implant position, including angular orientation, in the patient's joint is determined based on a predetermined range of motion and the calculated range of motion.

Abstract: In an electronic device powered by a battery, a method of determining a charge of the battery. Initially, a discharge curve specifying the battery's voltage as a function of time is determined. This discharge curve is calibrated according to actual measurements. Next, a battery state model is established. The battery state model is comprised of a number of discrete charge states. The probability of the actual battery's charge for a particular charge state is specified by the battery state model for each of the charge states. The battery's voltage is periodically measured. Based on the measured voltage and the discharge curve, a voltage probability distribution is computed. The battery discharge model is updated by applying Bayes theorem to the old discharge model and the voltage probability distribution. The charge of the battery based on a mean value of the battery discharge model is then displayed.