Research

Laser phonomicrosurgery is a demanding surgical technique requiring significant psychomotor skills. Scaleability, operative distance, and the anatomically small nature of the vocal folds all combine to create numerous surgical challenges. Currently the dominant user interface for remotely aiming a CO2 surgical laser is the manual micromanipulator. A micromanipulator is a electro-mechanical device that orientates an optical mirror system to control the aiming of the laser beam to ensure accurate localization on the tissue of interest.

A portable continuous wave ultrasound system is being developed to observer venous and arterial blood flow. This ultrasound system contains an onboard direct digital synthesis (DDS) microcontroller to produces a frequency variable sinusoidal signal. A 5 MHz signal produce by the DDS is amplified, using high-speed op amps, to excite the piezoelectric ultrasound transducer (PZT).

The goal of this project is to establish and control formation movement of an EvBot II colony without explicitly stating which position each EvBot II is to maintain. Each EvBot II will compete for its position in the formation based on an internal heuristic that is a function of: (1) the location of the EvBot II, (2) the desired formation, (3) the proximity of the EvBot II to the formation configuration, and (4) an internal self-diagnostic control algorithm.

Current work focuses on determining methods of integrating multiple diverse sensors, and corresponding motor states, into a unified framework for learning and control. Initial implementation will be performed on the EvBot II robotic platform. Through effective sensorimotor integration, learning time will be reduced, and the learned control systems will exhibit more robustness of control and increased generalizability.

The goal of the research project is to increase the consistency and efficiency rates for the microinjection of embryonic stem cells into blastocysts through automation and development of an intelligent control strategy.

The first part of this project involves an investigation of current musculoskeletal modeling techniques and an attempt increase the accessibility and visibility of these techniques to clinical researchers.  There are many software packages available for analyzing motion capture data, but a lot of researchers are forced to write their own software due to compatibility problems or prohibitive costs.

Wireless sensor networks (WSN’s) provide unprecedented spatial and temporal sensory resolution.  The ubiquity of wireless sensor networks is made possible by their small size, Figure 1.  These devices have remarkably low power consumption and once powered up, can operate without service for months, or years.