AI augments advances in medical electronics
One of the biggest drivers of growth and advances in medical electronics is the integration of artificial intelligence. AI, particularly AI-enabled diagnostic imaging, is a major driver of innovation, helping address the rising data volume and decision complexity produced by imaging-diagnostics equipment. Although wearables and implantables are a significantly smaller piece of the medical electronics pie, these segments are also driving improvements, particularly for sensors, analog front ends (AFEs), power-management devices, and wireless system-on-chips (SoCs).
In the May/June 2026 issue, we look at how underlying technologies are driving improvements in medical electronic devices, from imaging-diagnostics equipment to wearables diagnostics such as continuous glucose monitors (CGMs).
The medical electronics market is expected to reach $11.9 billion in 2026, with a compound annual growth rate of 6.7% from 2026 to 2031, according to Mordor Intelligence. More than 600 AI-enabled devices were approved by the FDA by mid-2024, resulting in near-real-time workflows for image analysis, reducing both scan times and interpretation backlogs, according to the market research firm.
Contributing writer Abhishek Jadhav looks at how AI-powered medical imaging is turning data into faster diagnoses. Jadhav reports that computed tomography (CT) and magnetic resonance imaging (MRI) have created a growing challenge of data and decision-making. As imaging generates more information to interpret, AI helps to improve these systems by supporting faster, smarter workflows for higher-accuracy diagnoses.
He addresses the use of AI across the medical imaging pipeline and how it is augmented through a range of tasks, from the moment an exam is ordered to the final clinical interpretation; AI models in imaging diagnostics to perform complex tasks such as detecting minute pathological changes, precisely segmenting anatomical structures, and fusing information from different clinical sources; and how integrating AI into medical imaging brings enormous improvements in speed and operational efficiency.
Contributing writer Stefano Lovati looks at some real-world examples of AI/ML integration into medical systems and how it is improving imaging, robotic surgery, and remote monitoring. As AI/ML is increasingly integrated into medical systems, it is delivering smarter and faster care by bringing intelligence closer to where the data is created and used, he said.
Lovati finds that recent advances in computer vision, large language models, edge computing, and real-time signal processing are improving medical diagnosis and reducing the latency between data acquisition and actionable clinical results. This is enabling advances in robotic surgery and remote monitoring while delivering more integrated systems to improve patient care.
In the wearables space, one of the key advances in medical electronics is CGMs. These wearable devices enhance quality of life and allow clinicians to adjust therapy based on accurate, continuous data streams, reports Marco Doms, senior manager of business development of new platforms at Littelfuse Inc. He looks at the role of CGMs in connected healthcare as well as engineering challenges, including integrating protection and sensing for reliable operation, thermal monitoring and patient safety, and regulatory and compliance considerations.
CGMs have reshaped diabetes management by delivering real-time glucose readings, Doms said. But behind this innovation are complex engineering challenges: developing a device that operates safely and reliably on a micro-scale power budget and maintains precise sensing accuracy in all conditions while fitting into a small form factor, he said.
A key component driving improvements in medical electronics is sensors. With the wide range of medical devices, from wearable glucose monitors to CT and MRI scan equipment, there is a variety of sensors incorporated into these devices. Lovati looks at some key sensor technologies, such as pressure and temperature sensors, as well as biosensors and accelerometers.
He also examines how medical sensors work together with AFEs, power-management devices, and wireless SoCs to deliver solutions that maximize diagnostic accuracy, reliability, and efficiency.
Also in this issue is a product roundup of sensors launched at Sensors Converge 2026. This year’s conference spotlighted sensor and sensing solution breakthroughs for applications from wearables and smartphones to industrial and automotive. Sensor manufacturers continue to focus on shrinking solutions while addressing the need for lower-power-consumption devices.
Don’t miss the top 10 circuit-protection devices introduced over the past year. These new devices deliver enhanced performance and address the need to streamline assembly and reduce printed-circuit-board space.
Cover image: Adobe Stock
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