Researchers at Stanford University School of Medicine are examining the feasibility of developing a diagnostic device that uses plastic magnetic resonance (fMRI) and support vector machines (SVM) to more accurately determine the source and intensity of pain without requiring patient information. Such a tool will enhance the diagnosis and treatment of physicians. The following is an explanation of the current challenges and potential opportunities for researchers, published in the academic journal PlosOne.
Patients with severe cognitive or communicative disorders, such as those in intensive care units or those with dementia, may not be able to provide useful information about their own pain. For such patients, there is not much way to determine the presence or absence of pain. Although there are behavioral judgment methods (such as assessing facial expressions, vocalizations, body movements), patients who are affected by movements and other diseases may also fail. Therefore, it is necessary to develop a pain assessment tool that is physiologically based and does not need to communicate with patients.
The project has not yet reached a breakthrough, but the researchers have already achieved some promising results, and have begun to consult medical institutions, hospitals, and patients on the field for the prospect of such equipment. In addition to helping direct users, pain diagnostic tools can also provide opportunities for OEM manufacturers as well as semiconductor and magnetic material manufacturers.
Researchers at Stanford University demonstrated highly accurate pain detection (up to 80%) in a series of experiments and concluded that "fMRI and SVM can detect pain conditions without communicating with the tester." The researchers believe that the next work is to conduct further experiments in the clinic environment.
Successfully reproducing the results of the experiment will not only help the patient, but also the medical device manufacturer. Pain is a common problem that everyone wants to get rid of. Unfortunately, judging the source of the problem to ensure the diagnosis is often difficult. Researchers know that people are generally unable to give specific answers when asked by a physician about the source of pain, so they hope to develop a tool to solve such problems.
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