ARTICLE SUMMARY:
Surgeons need to know how much pain a patient is experiencing, even while under sedation, so they can administer the right amount of pain medication to promote swift recovery and avoid complications associated with opioids and other analgesics. To that end, Medasense’s PMD-200 device leverages multiparametric input and AI to return an accurate and intuitive measure of physiological pain perception.
Relative to the amount of money that the healthcare system spends on reducing pain, not to mention the opioid epidemic that has put painkilling medication under scrutiny, few resources are available to measure pain objectively. Unlike blood pressure, heart rate, brain activity, or most other vital signs, there is no widely used technology to translate physiological activity into a clear metric of pain perception, with physicians instead relying on a subjective and imprecise scale of 1-10, illustrated with emoting faces to indicate patients’ distress level. Moreover, when patients are sedated during surgery, their bodies continue to respond to the pain of tissue damage despite being unable to communicate, leading doctors to prescribe analgesics at their discretion and often in greater or lesser quantities than are needed. Both underestimation and overestimation entail discomfort or worse for patients, as untreated pain can prolong recovery while excessive medication has its own side effects and consequences.
To address the need for a more informative means of monitoring pain in both conscious and unconscious patients, Tel Aviv-based start-up Medasense has developed an AI-driven system to measure nociception, the physiological response to pain. As founder and CEO Galit Zuckerman-Stark describes, “Our mission is to help patients suffer less from pain or from the adverse side effects of pain medication.” Before founding Medasense, Zuckerman-Stark held various R&D positions in the tech industry, specializing in AI and machine learning. Coming from a background in electrical and computer engineering, Zuckerman-Stark was struck by the contrast in sophistication between the complex semiconductors used in her field of work and the “smiley face/frowny face” tool used in hospitals to gauge pain. “With my expertise and the team, I thought I might be able to provide a new way of thinking that can give patients a more objective assessment of their pain and therefore help their pain treatment,” she explains.
