Project in the spotlight: Improving diagnostics for shoulder pains thanks to Living Lab Care Robotics

How can you improve the diagnostics of shoulder pain with the use of artificial intelligence (AI)? Students from the Applied Data Science minor from Medical Delta Living Lab Care Robotics are involved in this research question.

The minor started in 2017 and was set up by the Technology for Health research group of the Haagsche Hogeschool and the Leiden University Medical Center (LUMC). The minor has been nominated for the Pim Breebaart Award, an award for the project that best connects research, education and practice within the Haagsche Hogeschool.

Central to the research is the question of whether and how artificial intelligence (AI) can support a physician in his diagnostics. In Medical Delta Living Lab Care Robotics, movement sensors connected to a computer system look at patients with shoulder pain. The sensors record the movements of the shoulder and relate these movements to the big data in the computer. If in this manner a pattern is "recognized", this leads to a diagnosis that is compared to the doctor's diagnosis.

"AI's support for diagnostics has enormous potential," says Dr. Erwin de Vlugt, Technology for Health lecturer at the Haagsche Hogeschool. “A doctor, no matter how experienced, can sometimes overlook something. Artificial intelligence combines what the movement sensors on the patient's body see with the data that is already available. That is now focused on the shoulder movements, but can be extended to any part of the musculoskeletal system. We may soon be able to include someone's facial expression in the study. Or other parts of the body. Then, for example, AI could indicate that the shoulder pain originated from a poorly functioning knee. "

New golden standard

The research is done in collaboration with doctors and patients at the LUMC. De Vlugt: “The patients are cooperating because they get a diagnosis faster and can leave the outpatient clinic sooner. This project is being conducted in a rehabilitation environment. The doctors there are already used to a lot of technology and are positive about the potential added value of AI. We are now learning to make AI as good as the doctor. If we succeed, we might get a new golden standard. "

“The research of this minor brings together various disciplines in education, research and the professional field: data science, technology, IT, design and nursing. All stakeholders feel the same challenge. All disciplines are gifted in conceptual thinking. The nurses are the interpreters of what happens on the hospital floor. The great thing is that the development of the application is based on knowledge and methodology. And that we can now test the first prototypes. "

Meaningful

"As a research team within this minor, we can be meaningful for society," says lecturer-researcher Dr. Tony Andrioli of the Haagsche Hogeschool. ”The collaboration with so many disciplines and with the people of the LUMC is binding and enriching. It would be wonderful if a new diagnostic reality could emerge from this."