Flexible Medical Patch Processes Data Without Cloud Delays
A team from the Pritzker School of Molecular Engineering at the University of Chicago, working alongside Argonne National Laboratory, has developed a flexible patch that processes health data directly on the wearer's body. The device relies on a neuromorphic computing circuit built from organic electrochemical transistors, enabling it to analyze heart rhythm and other vital signs in real time. This eliminates the lag that typically occurs when data must be sent to external servers for processing.
How the Technology Works and What Tests Showed
The patch was made possible by a new method for printing organic electrochemical transistors onto flexible surfaces. The lab, led by Sihong Wang, focuses on electronics that can stretch and bend like human skin. The group had previously created stretchable transistor arrays and a flexible OLED display. Their latest goal was a neuromorphic circuit that operates using electrical current and ion movement within a special gel layer. This gel can store information, giving each transistor its own memory.
During testing, the team applied a pre-trained algorithm to treat ventricular fibrillation. When analyzing cardiac mapping data from a donated human heart, the system identified the location of electrical waves with 99.6% accuracy. The array was stretched to more than one and a half times its original length. In another experiment, a neural network examined vital signs and personal medical records, achieving 83.5% accuracy in predicting heart attack risk.
Sihong Wang, one of the research leaders, stated: 'The goal of this work is to create smarter wearable and implantable devices.'
Wang added that 'this technology could become a personal, fast-acting doctor built into a wearable device.' He explained that 'remote computing is not suitable for this due to lag, but analysis directly inside the device can make this approach a reality.' Co-author Jixuan Zhao noted: 'In software, the parameters of a neural network are just numbers, but in a real device, they depend on the physical properties of the material, its history, and its limitations.' Another co-author, Fanfan Xia, emphasized that 'instead of sending information to a remote server, you can start analyzing it right where it originates.'
Data transmission delays can be critical when every millisecond counts. For example, current treatment for ventricular fibrillation often involves a strong electrical shock to the entire heart. Researchers are exploring a more targeted approach: tracking abnormal electrical waves and stopping them with small pulses. Analysis must happen within milliseconds, as electrical signals spread very quickly. Data used for analysis can include:
- cholesterol levels
- blood sugar
- maximum heart rate
- electrocardiogram readings
The creation of a flexible patch with a neuromorphic computing circuit opens new possibilities for diagnosing and treating cardiovascular diseases. Reducing processing delays by handling data directly on the patient's body could significantly improve the effectiveness of emergency care, especially for ventricular fibrillation. This may lead to a major reduction in complication risks and better treatment outcomes, marking an important step toward personalized medicine.
As advancements in wearable technology continue to evolve, the integration of AI in health monitoring systems is also making significant strides. Recently, a study revealed that AI can achieve high accuracy in identifying heart diseases from ECG data, showcasing the potential for real-time diagnostics and personalized healthcare solutions. This complements the development of flexible patches that analyze heart rhythms instantly, highlighting a growing trend towards smarter health devices.