Biomedical subjects

Shahram Payandeh

Publications and source records attributed to Shahram Payandeh.

4 recordsLinked to original sources

PubMed2006

Effects of assembling virtual fixtures on learning a navigation task.

An approach to enhance navigation task performance is to integrate sensory guidance (virtual fixtures) into a virtual training system. To evaluate the effects of adding virtual fixtures to skill acquisition, 32 subjects were required to use a PHANToM input device, to transport a virtual object through a computer generated 3-D graphic maze. Subjects practiced navigation under 4 conditions: the maze was augmented with either a graphic fixture (G), attractive force field (F), both graphic and force field (GF), or no (N) virtual fixture. Fifteen practice trials were given before subjects were transferred to a situation with no virtual fixtures. Results showed that the implementation of the force field assisted task performance during practice; however, it failed to show positive transfer effects. In contrast, adding a graphic fixture to the virtual maze helped subjects to define the optimal pathway throughout navigation, which facilitated skill acquisition.

Computer Simulation↗

PubMed2005

Fuzzy classification: towards evaluating performance on a surgical simulator.

Computer-based surgical simulators such as the MIST-VR are able to provide scoring metrics such as time taken to complete a task, number of errors made, and economy of movement. Using MIST-VR's basic metrics, we explored the possibility of classifying skill levels using fuzzy logic. Our objective was to create a fuzzy classifier capable of classifying the performance of a subject training on a surgical simulator into 1 of 3 categories: Novice, Intermediate, and Expert. To accomplish this, we needed to establish a baseline skill level for each category. We had four laparoscopic surgeons, four surgical assistants/residents and four non-surgical staff/students with no laparoscopic experience perform two basic tasks on the simulator involving the placement of a ball into a box. We have found, through this preliminary study, that the results were inconclusive. We suspected a number of issues such as the size of our sample space used to train our classifier, and the difficulty of the chosen tasks adversely affected our results.

Canada↗

PubMed2004

Acquiring laparoscopic manipulative skills: a virtual tissue dissection training module.

Virtual environments for training manipulative skills in laparoscopic surgery are now well established as research areas. Tissue dissection however has not yet been adequately addressed. We have developed a virtual training module in which the task is to dissect a 3D tissue model using a simulated L-hook. Three metrics have been designed to assess performance. 1) Total deviation of actual cut path from the drawn path. 2) Total contact time between the instrument and tissue. 3) Contact discontinuity. The objective of the research was to design a basic tissue dissection module to train, in part, laparoscopic manipulative skills.

Canada↗

PubMed2002

On defining metrics for assessing laparoscopic surgical skills in a virtual training environment.

One of the key components of any training environment for surgical education is a method that can be used for assessing surgical skills. Traditionally, defining such a method has been difficult and based mainly on observations. However, through advances in modeling techniques and computer hardware and software, such methods can now be developed using combined visual and haptic rendering of a training scene. This paper presents some ideas on how metrics may be defined and used in the assessment of surgical skills in a virtual laparoscopic training environment.

Animals↗