Augmented Reality Membrane Modeling

INTRODUCTION The World Health Organization (WHO) has reported that cataracts are responsible for 51% of the total cases of world blindness. An estimated 20 million people in the United States alone currently suffer from cataract-induced vision impairment [1]. The WHO has also found that coronary heart disease was the cause for approximately 7.4 million deaths in 2012, representing approximately 13% of total mortalities [2]. Though effective, current surgical techniques for treating cataracts and CHD rely heavily on the skill and experience of surgeons. During microsurgical procedures, surgeons use visual feedback when forces are below the threshold of touch [3]. Percutaneous coronary intervention, or angioplasty, similarly requires surgeons to focus on an external monitor displaying an angiogram while concurrently performing the arterial procedure [2]. In effect, both microsurgery and angioplasty techniques require a surgeon’s precise and steady control over visually indistinguishable and tactilely insensitive membranes, nerves, and blood vessels under a microscope [3]. Even with the use of a microscope, surgeons cannot tactilely assess their movements, creating the potential to accidentally rupture blood vessels and membranes. Simulation devices, or phantoms, have become important tools for microsurgeons to practice tissue puncture experiments [3]. Phantoms are devices capable of rendering physical surfaces by using force feedback to create surface characteristics, such as texture, viscosity, and stress and strain. The Geomagic Touch and Magnetic Levitation Haptic Device (MLHD) are two such haptic platforms that are commercially available for surface rendering. The MLHD can move in six degrees of freedom and uses a flotor surrounded by a bed of magnets to generate forces onto the user’s hand [3]. However, the MLHD has been shown to be ineffective at rendering biological membranes due to limitations in force output and inertial effects caused by its heavy flotor [3]. The 1 Degree of Freedom Haptic Renderer (1DOF) was developed to address the limitations of existing haptic platforms. It uses a woofer loudspeaker actuator with force and displacement sensors to simulate tissue interaction [3]. OBJECTIVE A Proportional-Integral-Derivative (PID) controller is to be designed and coded to model two spring simulations to test the viability of the 1DOF as a sensitive membrane modeling device.