Administering needle-based procedures in anesthesiology, such as epidurals, is a complex and delicate procedure. However, the current training methods for doctors are costly and fall short in preparing them for every patient and situation they’ll face.
A new proposed patent from the Penn State College of Engineering plans to change that.
The haptic force needle insertion simulator, created by a team of researchers led by Jason Moore, associate professor of mechanical engineering, is a low-cost, hand-held device that simulates the tactic feeling of the instrument passing through several layers of tissue. It also connects to a computer program that can assess the user’s performance.
These factors are crucial because the doctor’s hands need to produce a steady rate of insertion which can be challenging. “There’s a buildup of force upon tissue deflection and a sudden release of force upon tissue puncture,” Moore said. “This training tool can help surgeons, residents, and med students improve their dexterous abilities.”
Working in harmony, the tool and program interface will provide real-time feedback on the physician’s performance during training. This response is crucial to the device and represents a new efficiency and effectiveness of surgical training.
Currently, the most effective way to train clinicians is to observe other doctors. Sanjib Adhikary, associate professor of anesthesiology at Penn State Hershey and co-investigator of the project, said, “Those of us who teach these procedures find it very difficult to teach the needle, eye, and image coordination skills.”
Using the simulator, doctors will be better prepared for these procedures. “It can raise the ability of residents before they begin performing these procedures on patients,” Moore said. “It also gives them a very nice way to assess their performance and understand where improvements can be made.”
Other training methods, like using mannequins, are more expensive and don’t account for the range of body types a doctor would encounter in their patients.
This device is able to change its simulation based on these different scenarios, like varying skin thickness and excess body weight.
Eventually, this tool could be adapted to train doctors in other specialties like emergency medicine, radiology, and surgery.
