da Vinci Si System with single-site instrumentation ©2016, Intuitive Surgical, Inc.

No matter how great a surgeon is, robotic assistance can bring a higher level of precision to the operating table. The ability to remotely operate a robot that can hold precision instruments greatly increases the accuracy of surgical procedures like thoracoscopic surgery, which is used to treat lung cancer.

Of the two most common types of lung cancer, non-small cell lung cancer (NSCLC) is a good candidate for surgery because the tumors spread slowly and are more localized. Since more than 80 percent of people with lung cancer have NSCLC, surgery is a common treatment.

Lung cancer usually starts when epithelial cells that line the inside of the lungs rapidly reproduce into cancerous cells, creating tumors inside the lungs. These tumors have been traditionally removed directly by the skilled hands of a surgeon. Today, we’re starting to see more tumors being removed by robots that are controlled by skilled surgeons. This process is known as robotic assisted lung surgery.

The key benefits of robotic assisted lung surgery are:

It’s minimally invasive and small incisions are used. Traditional lung surgery procedures utilize a large incision across the chest wall. When using robotic assisted surgery, the incision is about half as long. The robotic arms can be maneuvered more intricately, so the incision doesn’t need to be as large. Often a second incision is made for the removal of tissue.

Patients often experience a faster recovery time. When a patient has a robotic lobectomy, they’re often back to their normal routine in a week’s time. Older patients in their 70s and 80s also experience a good recovery with this type of procedure, which is good news considering they’re usually not great candidates for open surgeries. The small incisions are responsible for a faster recovery time compared to the long recovery time after traditional lung surgery.

There are several robotic assisted procedures used to treat lung cancer:

Video-Assisted Thoracoscopic Surgery (VATS)

Fewer than 5 percent of thoracic surgeries in the US are performed robotically. Rush University is one of a few US medical institutions that offer a full range of robotic-assisted lung cancer procedures, including VATS. In fact, Rush is known as a leader in VATS.

VATS is the most common type of robotic assisted lung surgery. With this procedure, one incision is made to insert the surgical instruments for the removal of tissue, while another incision is used to place the camera. The surgeon maneuvers the surgical instruments while an assistant operates the camera so the surgeon can see what’s happening.

The da Vinci Si robotic system

Rush University is now using the da Vinci Si robotic system for lung surgery, where it was once only used for other, more general surgeries.

How the da Vinci Si robotic system works

A surgeon sits at a console to control a four-armed robot that’s been positioned above the patient lying on the operating table. The surgeon observes the scene from a screen that displays images coming from a camera. As the surgeon moves his or her controls, the robot responds accordingly in real-time, and the surgical instruments attached to the robotic arms perform the surgery.

One of Rush University Medical Center’s thoracic surgeons, Gary Chmielewski, says, “any motion I can do with my hands, the robot can simulate inside the patient with more precision and less tissue trauma. It all works together for a better operation that’s easier on the patient.”

Nine years of positive results

A study published in 2014, analyzed the results of different types of robotic lobectomies for treating lung cancer over a period of 9 years. The study was designed to evaluate the evolution of technique as well as the robotic technology. The study found a positive trend in patient outcomes when they opted for the upgraded robotic systems compared to the standard systems.

Twenty years ago, who would have thought having robotic assisted lung surgery would become the most popular, most effective option?

If robots can be used to help surgeons remove tumors from lung cancer patients, what else is possible with robotics? The possibilities are endless.

A few decades ago, touchscreens were impressive, yet clunky pieces of technology reserved for applications that did little more than show off that touchscreens were possible. Today’s touchscreens are commonplace and readily accepted as an easy way to interact with an operating system; they’re accurate, support multi-touch, are comfortable to use, and can even operate in multiple dimensions (pressing hard).

We may not have perfected touchscreens yet, but we’re getting close. Accordingly, engineers and researchers are already speculating about the next phase of UI development, especially for robotics control. So far, the leading candidate is gesture-based control—the use of physical gestures to relay commands.

The idea

The major limitation for touchscreens is the fact that they operate only in two dimensions; the third dimension introduced with force touch is extremely limited. Comparatively, hand gestures and physical movements can operate in three dimensions, and depending on how they’re designed, could feel more natural than swiping and tapping a smartphone screen.

Demand for three-dimensional gestural control is increasing with the onset of virtual reality (VR) and augmented reality (AR) technology; because the digital world we experience will be moving from two dimensions to three dimensions, the controls we use to manage those experiences will also need to change. With enough sophistication, these systems could provide better feedback to the users in control; rather than merely responding with visual feedback like movement or lights, users could feasibly be immersed with physical feedback like vibration or resistance.

Where we stand

Currently, one of the most advanced gestural systems is the Real-Time 3D Gesture Analysis for Natural Interaction with Smart Devices, a project headed by researchers in Linnaeus University in Sweden. However, simpler forms of gesture-based control are already available.

For example, there are projects that use Arduino to create a robot that can respond to four different simple hand gestures (plus a neutral position). Of course, iPhone technology also makes use of some simple “gestures,” such as shaking the phone to undo typing or rotating the phone to experience an immersive 360-degree view of an image or video.

The main obstacles

There are a few obstacles preventing gestures from being solidified as the next landmark in robotics control, however:

• Gesture complexity. The biggest obstacle described by researchers at Linnaeus University is the sheer complexity of physical gestures; to be effective, their recognition systems need to be able to gather and recognize thousands of tiny data points and interpret complex patterns to “understand” what movement is being attempted. Moreover, this big data-based interpretation needs to happen in real-time—especially for applications like live robotics control, or engagement in a VR-based video game. That demands not only an incredibly intelligent system, but a processor that can operate quickly.
• Accessibility. Gesture recognition systems would likely be developed to accommodate a “standard” human model, such as a “standard” right human hand. How would the system accommodate somebody whose hand was missing, or who is missing a few fingers? What about left-handed people? And people with Parkinson’s disease, or who are unable to operate their hands with precision control?
• Applications. For gestures to be accepted as a mainstream way to interact with robotics and virtual environments, robotics and virtual environments need to be available. Virtual reality (VR) technology has been advancing strongly for the past several years and is poised to take a big step forward in user adoption by 2020, but until those user adoption numbers are reliable, the demand for gestural systems is relatively low. Using hand movements and other physical gestures to control a two-dimensional screen, for example, would be largely ineffective.

On paper, gestures seem like the best form of control for the digital devices, robotics, and VR systems of the future. However, there are still many obstacles to overcome before we’re ready for large-scale adoption. Fortunately, researchers are ahead of the curve, already preparing the intelligent gesture-based recognition programs we’ll need when touchscreens become obsolete.