First of all, there are no true medical robots; none of the systems out there called medical robots are autonomous with regard to duplicating human activity, and few are even semi-autonomous. They are arguably bionic constructs; that is, enhancing the healthcare provider’s performance by electronic or electromechanical devices. The key here is that these devices enhance the abilities of the user, but do not replace them. It is reasonably too late to change the vernacular, and it is just a matter of semantics anyway. But why is this distinction important to design and development? This article addresses two of the reasons why the distinction is important:

  • The regulatory strategy can be significantly different from other medical devices, especially regarding the level of autonomy, team usability validation, and training.

  • Understanding that these systems are an extension of a clinician’s current ability and that they enhance an activity that clinicians may also do manually, thereby having an important impact on the user interface design and development .

Strategic Regulatory Impact

Even though many of the current robotic systems are based on technology that could very well execute a procedure autonomously, the scope of validating the safety and efficacy for FDA approval would be cost prohibitive. This is because you would have to demonstrate that the robot can safely manage contingencies that are often unpredictable during a procedure. This would require validation trials of a scale similar to pharmaceutical clinical trials, where hundreds, if not thousands of patients are required.

Unlike a medication, which is a high-volume consumable that is reimbursed by a payee, a piece of capital equipment marketed to a healthcare facility, does not have the same return on investment that could justify such an investment in validation. However, by keeping the clinician in control and the system relegated to an extension of their abilities, the human is still responsible for the outcome. Now, with the clinician as the decision maker, the validation process is a function of the clinician’s interaction with the robotic system’s user interface. In other words, the manufacturer doesn’t have to validate the user’s clinical abilities, just that the robotic system meets expectations for efficacy, safety, and performance. That said, both the design and usability validation can still be significantly more complex than conventional medical devices.

Design and usability validation of robots can be significantly more complex than conventional medical devices. (Credit: Sompong Sriphet)

Using a surgical robotic system as an example, it being an extension of the surgeon’s abilities, the robotic system impacts the rest of the surgical workflow as well — that being all the other actors involved in the surgical procedure. It is important to note that a conventional surgery, be it open or laparoscopic, is typically a symphony of interactions between a team of clinicians. These clinicians may include lead surgeon, first assist, sterile nurse/tech, circulating nurse, anesthesiologist, and possibly others (e.g., perfusionist) or duplicates of some of the actors listed. In addition, if it is a teaching hospital, there are interns and fellows on the team.

The importance of understanding all the people involved in order to result in a favorable outcome for the patient is because now we are introducing a new actor into the operating room: the robot. Oftentimes this impacts the manner in which the lead surgeon interacts with the team, as well as requiring a physical footprint for the robotic system in an already congested environment. Moreover, once you remove the team leader from the sterile field and isolate that participant in a control console, the team dynamics are profoundly impacted.

Although the intention is often to make the robot an optimized instrument(s) for the surgeon, in application, it can affect the responsibilities of the extended surgical team and their responsibilities. For example, there may be a requirement to exchange end effectors over the course of the procedure, which requires team members to interact with each other and the robot, while the lead is interacting with them without face-to-face communication. Keep in mind that a significant portion of communication is nonverbal. Granted, the actors are wearing masks, but they have learned to read facial expressions inclusive of the mask in addition to body posture.

The point of understanding these team dynamics is that when it comes time to validate the user interface of the robotic system, the team has to be considered and often included in the validation test. Moreover, the teams may or may not be cohesive; that is, in a teaching hospital the team members may change often, whereas in a private institution, they may be a seasoned, cohesive team. For usability validation, both team types would need to evaluate the design. Even more important is that upstream usability engineering research  must be conducted in order to inform the design and regulatory team of the requirements for future validation based on well-understood use-related risk assessments.

The use-related risk assessment can impact yet another regulatory path strategy for a robotic system, complicating risk mitigation and the subsequent validation. This specifically involves training models for the robotic system.

Legacy, manual surgical devices, typically do not require formal training; i.e., training beyond orientation or an “in service.” The difference between orientation and formal training is that orientation is not considered a risk mitigation from a regulatory perspective. In order for training to be a risk mitigation, or design control, it has to have robust documentation that demonstrates, to the regulatory bodies, the degree of control and repeatability the manufacturer maintains.

This means that under the design control process, there is a protocol for how the trainer is trained, a record of who was trained, when they were trained, if and when subsequent training is required, and what qualifications for use of the system the training results in. The definition of system may include the robot proper, the control console, the robot drapes and the end effector’s instrument attachments. It may even include the cleaning and reusability of the instrument attachments. Obviously, formal training is a far greater ongoing burden and responsibility for the manufacturer.

The definition of system may include the robot proper, the control console, the robot drapes, and the end effector’s instrument attachments.

User Interface Design Impact

The team dynamics and the impact of the introduction of a robotic system into a surgical procedure have comparable influence to the regulatory impact with regard to the design and development of all the system’s user interfaces — virtual and physical. The same user research insights that can inform the use-related risk assessment and regulatory strategy apply to the design and development of the robotic system’s user interface.

Consider the example of the lead surgeon’s user interface: there is first the understanding of negative and positive transfer bias in the physical user interface. This also applies to the cognitive load requirements of the system, especially if the system is expecting the surgeon to be responsible for what was previously a team effort. Then there is the accommodation of team dynamics and communication as discussed in the regulatory strategy impact. These considerations also apply to the other user interfaces such as end effector access to the anatomy, instrument attachment, and draping.

Returning to the surgeon’s user interface example and the associated biases, the manner in which the surgeon executes a manual procedure, the variety of instruments and their specific user interfaces, the instruments’ capabilities, kinematics, and feedback can result in either a positive or negative transfer bias depending on how the new control interface is designed. Negative transfer bias can introduce a potentially hazardous condition and use error that could lead to harm — changing the rote manner in which a task is performed relative to how it was learned and practiced previously.

Conversely, the user interface design can afford positive transfer bias by emulating or carefully transitioning from a norm behavior and interface to the new user interface and workflow experience. Depending on training to convert the user’s previously learned skills and behavior is not a viable strategy. A proactive approach to understanding the user’s expectation and aspiration with an in-depth understanding of the perceived attributes that afford the intended behavior is a more robust approach.

This article was written by Sean Hägen, Founding Principal and Director of Research & Synthesis at BlackHägen Design, Dunedin, FL. He focuses on the user research and synthesis phases of product development, including usability engineering , user-centric innovation techniques, and establishing user requirements. For more information, visit here .