WILMINGTON, Mass. - Analog Devices , Inc. (NASDAQ: NASDAQ:ADI) announced today the FDA 510(k) clearance and commercial launch of its Sensinel Cardiopulmonary Management (CPM) System, marking the company's first FDA clearance in its 59-year history. The Sensinel CPM System is a non-invasive wearable device designed to remotely monitor patients with chronic diseases such as heart failure.
The system is intended to aid in the management of cardiopulmonary diseases by providing care teams with physiological data to facilitate early and precise remote management of chronic conditions. Patients can self-apply the Sensinel CPM Wearable for a few minutes daily at home, and the device automatically uploads the health data to the Sensinel CPM Cloud Platform via a cellular connection.
Patrick O'Doherty, Senior Vice President of Digital Healthcare at ADI, highlighted that the device, developed with input from cardiologists, could help improve patient care, streamline clinician workflows, and potentially reduce healthcare costs. Heart failure affects over 6 million Americans and is projected to increase, alongside the associated costs, which are largely driven by hospitalizations.
Dr. Sean Pinney, Chief of Cardiology at Mount Sinai Morningside, praised the system for its accuracy and reliability in improving predictive care. Dr. Venu Gopinathan, ADI Fellow and Managing Director of Medical Products at ADI, emphasized the importance of the system's design in fitting into the care workflow and providing actionable data without overwhelming clinicians.
The new Sensinel CPM System is now available commercially, representing the first product from Analog Devices' new wearable healthcare line, Sensinel. The company, a global semiconductor leader, has a long history in the healthcare industry, providing technologies that bridge the physical and digital worlds.
This news is based on a press release statement from Analog Devices, Inc. The company cautions that the press release contains forward-looking statements subject to various factors and uncertainties that could cause actual results to differ materially from those described.
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