Skip to main content

Medical training robots for airway management

Medical training is the best countermeasure for accidents concerning airway management, but the best training methods require human volunteers, which presents far too many risks and ethical problems. This is why medical doctors and students employ several types of medical training simulators.

Most existing models only have a few sensors attached to their systems, providing little quantitative information to the trainee and forcing instructors to provide subjective assessments. In addition, they do not simulate the real-world conditions of the tasks very well.

As an alternative, we proposed an innovative training system using Robot Technology (RT), with a high number of embedded sensors, actuators, and evaluation units within the training system.

This innovative, RT-based training system was introduced as a way to provide more effective training.

At the minimum, an innovative training system must fulfil four specific conditions: it must 1) provide useful feedback to trainees and objective assessments of the training progress, 2) reproduce relevant patient patterns, 3) reproduce patient scenarios for real-world conditions of the task and adjust the degree of difficulty to achieve an effective training, and 4) simulate high-fidelity simulated human anatomy.

Based on the concept of the innovative training system, an airway management training system is created. Finally, a set of experiments were carried out by doctor subjects and student subjects to verify the usefulness of our proposed training system. 

Publications

Awards

Patents



View on YouTube

Please accept all cookies to view this content. Alternatively view the content on YouTube

Project partner

Kyoto Kagaku

Related Research Group(s)

robot lab

Robotics and Automation - We carry out world-class research in robotics and autonomous systems, exploiting and exploring opportunities to develop innovative solutions for industrial and societal applications.


Partnering with confidence

Organisations interested in our research can partner with us with confidence backed by an external and independent benchmark: The Knowledge Exchange Framework. Read more.


Project last modified 10/09/2021