Researchers from MIT have developed a system to measure the patient’s pain level by detecting their brain activity. Such a system is expected to help doctors with diagnosing and treating noncommunicative patients. It is expected that this could reduce the risk of chronic pain that can occur after surgery.
How does the system work? MIT researchers have used functional near-infrared spectroscopy (fNIRS), a technique that enables direct monitoring of brain activity via a relatively non-invasive, safe, portable, and low-cost method. By measuring changes in near-infrared light, it allows researchers to monitor blood flow in the front part of the brain.
Then after measuring brain signals, scientists have developed personalized machine-learning models to recognize patterns of oxygenated hemoglobin levels related to pain responses. When the sensors are set up, the models can distinguish whether a patient is experiencing pain with around 87 percent precision.
Because we are able to detect pain with this high accuracy, using only a few sensors on the forehead, we have a solid basis for bringing this technology to a real-world clinical setting. - Lopez-Martinez Ph.D. student in the Harvard-MIT Program in Health Sciences and Technology and a researcher at the MIT Media Lab
Earlier surgery patients had to take anesthesia and medication based on their age, weight, previous diseases, and other factors. But now it seems doctors could anticipate the level of pain as the new system could provide surgeons with real-time information regarding an unconscious patient’s pain levels. This will undoubtedly help doctors to adjust anesthesia and medication dosages accordingly to stop pain signals and also provide relief to patients from chronic pain.