IEEE Spectrum’s most popular biomedical stories during 2025 focused on two parallel trends: introducing new technologies, particularly artificial intelligence, into biomedicine, and repurposing older technologies such as Wi-Fi, ultrasound, and lasers for new health applications. These examples do not necessarily represent mature products; rather, they illustrate research pathways that could change how diseases are diagnosed or treated, or how patients are monitored, in the future.
Artificial intelligence appears in some of these projects as a tool for analyzing complex biological signals, while innovation in others depends on modifying how devices and technologies available for years are used. Although some applications seem close to practical use, others remain within the realm of hypotheses or early experiments.
Brain Implants and Early Warnings of Depression
One of the leading stories began with an observation by Patricio Riva-Posse, a psychiatrist at Emory University School of Medicine, that brain implants in one of his patients were sending signals indicating worsening depression before she realized it herself. The experience prompted Riva-Posse and his colleagues to develop what they described as an automated warning system that detects indicators of changes in mental state.
The system relies on implants that continuously record electrical impulses in the brain, then uses an artificial intelligence model to analyze the output and detect signs that may indicate a relapse of depression. In parallel, other research groups in the United States are testing different ways to use stimulating brain implants to treat depression, with or without artificial intelligence. Neurosurgeon Nir Lipsman says the field offers many options for intervention, but the article does not present this system as a treatment widely available.
Graphene Tattoos Monitor Biomarkers
In Dmitry Kireev’s laboratory at the University of Massachusetts Amherst, researchers are developing extremely thin electronic tattoos made of graphene that are almost invisible on the skin and can monitor biomarkers and other bodily signals. Graphene is a strong and flexible conductor, allowing it to be used to measure heart rate and detect the presence of certain compounds in sweat.
Kireev believes these tattoos could eventually help monitor complex medical conditions, including cardiovascular diseases, metabolic disorders, immune diseases, and neurodegenerative diseases. At present, however, the technology still needs to be connected to a conventional electronic circuit. The researchers hope eventually to integrate it into smartwatches so that it becomes easier to wear and use.
Measuring Heart Rate Through Wi-Fi Signals
The Pulse-Fi system is an example of turning a common communications technology into a contactless health-monitoring tool. It uses an artificial intelligence model to analyze heartbeats and estimate heart rate in real time from a distance of up to 10 feet, or about three meters.
The system’s total cost is about $40, according to the article, and it is easy to deploy without the discomfort associated with monitoring devices that require continuous contact with the body. The system works regardless of the user’s position and in different environments. Katia Obraska, a computer scientist at the University of California, Santa Cruz, leads the development of Pulse-Fi and said that the team plans to commercialize the technology. This does not mean that the system has already become a commercially available product.
Ultrasound and Lasers Remain Within the Research Domain
Researchers Sangeeta S. Chavan and Stavros Zanos, from the Institute of Bioelectronic Medicine in New York, hypothesize that ultrasound may be able to activate neurons. The idea is based on vibrating the neuronal cell membrane and opening channels that allow ions to flow into the cell, indirectly changing its voltage and prompting it to release a signal.
According to the researchers’ proposal, targeting specific neurons could make it possible to treat inflammation or diabetes instead of using drugs with broad side effects. However, the text presents this as a research hypothesis, not as a proven treatment or an available clinical alternative.
In a different optical direction, researchers have demonstrated that lasers can send photons through a human head, after this type of work had seemed impossible for years because the head can block light. In the future, this could lead to tools that combine the low cost of electroencephalography, which does not penetrate the outer layers deeply, with the ability of functional magnetic resonance imaging to see deeper regions, though fMRI is more expensive. Jack Radford, the project’s leader, describes the result as proof that something once believed impossible is feasible, not as a ready-to-use diagnostic device.
Robots Move Closer to Making Decisions in the Operating Room
The final story examines the possibility that robots could become capable of making more independent decisions during surgery. The three researchers who prepared the article work in the robotics laboratory at Johns Hopkins University, which is responsible for developing the Smart Tissue Autonomous Robot, known by the acronym STAR. In 2016, STAR performed the first autonomous soft-tissue surgery on a live animal.
Reaching an operating room that relies entirely on autonomous robots still faces obstacles, including the development of multipurpose robotic control systems and the collection of data under strict privacy rules. Nevertheless, the article’s authors believe that the scenario of a patient being received by a surgeon and an autonomous robotic assistant is no longer a distant possibility. This vision remains tied to progress in research and testing, not to an announcement that these systems have been routinely adopted in hospitals.
These stories bring together innovations based on artificial intelligence and others that rediscover the potential of older technologies. The overall review indicates that the value of medical innovation is not always linked to the novelty of the tool, but to how it is used to collect biological signals, affect tissue, or support surgical decision-making. At the same time, the examples show that moving from proof of concept to medical use requires further validation and addressing challenges related to safety, privacy, and reliability.