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Biomedical Circuits, Systems, and Applications

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Research on biomedical sensing systems and signal processing algorithms has been very prolific in recent years with a variety of solutions in a wide range of application scenarios, for example long-term monitoring of human vital signs for disease detection. Low-power consumption and energy efficiency are the key features of such systems starting from the sensor node for data acquisition, towards embedded systems for data handling, and accurate algorithms for data processing.

Many research topics are actively ongoing around the human body, from chip design, to system development, to algorithmic investigations in various application scenarios. In the following sections you find links to past and current projects that you might find interesting.

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Digital Medical Ultrasound Imaging

Ultrasound Imaging Probes

Ultrasound is one of the most used medical imaging modalities. Its main features are: real-time operation, low-cost, wide-availability, excellent spatial and time resolution, low-power. Recently, multiple innovative systems are being developed, targeting both high-end and wearable/embedded applications.

At IIS, we are exploring the next generation of medical ultrasound imaging systems, spanning from very high-end systems (FPGA-based digital probes with >100 channels and ultra high-speed Gb/s interfaces), to wearable wireless systems (FPGA or MCU-based, equipped with WiFi or Bluetooth links).

More information can be found here.

Flexible Electronic Systems and Embedded Epidermal Devices

Ultrasound Transparent EMG System

Flexible Electronic Systems use polymers and other flexible or stretchable materials to create wearable and conformable devices. These systems consist of various components, including flexible and bendable parts, such as electrodes and transducers, as well as small rigid components, such as energy storage units, transistors, and complete integrated circuits (ICs). The design of these systems allows for comfortable wear, as they can be positioned close to or even attached to the human body as epidermal devices. The integration of digital electronic components enables these devices to perform complex functions, such as continuous monitoring and modulation of physiological signals and communication with other devices.

However, the development of such systems is faced with several challenges. These challenges include material properties, such as flexibility, stretchability, and biocompatibility, as well as reliability issues due to bending and mechanical stress on the entire hardware and signal stack, and interface challenges at all levels of integration. Advanced and specialized manufacturing techniques are also required for their fabrication. Our research focuses on improving the interconnectivity and processing reliability of digital circuits on flexible, stretchable substrates. This helps to bring hardware intelligence closer to the skin surface, and we also develop smart embedded solutions to optimize the manufacturing process.

More information can be found here.

Human Intranet

Human Intranet is an open, scalable platform that seamlessly integrates an ever-increasing number of sensor, actuation, computation, storage, communication and energy nodes located on, in, or around the human body acting in symbiosis with the functions provided by the body itself. Human Intranet presents a system vision in which, for example, disease would be treated by chronically measuring biosignals deep in the body, or by providing targeted, therapeutic interventions that respond on demand and in situ.

In the following, a summary of the main projects is given. More details can be found here.

Brain-Machine Interfaces

Noninvasive brain–machine interfaces (BMIs) and neuroprostheses aim to provide a communication and control channel based on the recognition of the subject’s intentions from spatiotemporal neural activity typically recorded by EEG electrodes.

In this project, our goal is to develop efficient and fast learning algorithms that replace traditional signal processing and classification methods by directly operating with raw data from electrodes. Furthermore, we aim to efficiently deploy those algorithms on tightly resource-limited devices (e.g., Microcontroller units) for near sensor classification using artificial intelligence.

Epilepsy Seizure Detection Device

Seizure detection systems hold promise for improving the quality of life for patients with epilepsy that afflicts nearly 1% of the world's population. In this project, our goal is to develop efficient techniques for EEG as well as non-EEG signals to detect an upcoming seizure in an ultra-low-power device.

Wearables for Sports and Fitness Tracking

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The popularity of wearable technology is growing rapidly in the sports and fitness industry. With fitness trackers and smartwatches, it's easy to monitor key metrics like heart rate, steps, and calories burned, which helps users reach fitness goals and participate in online challenges. These devices can even create personalized training programs based on data collected. Wearables also give athletes real-time feedback on performance and technique to improve competitive skills and coaches new opportunities to monitor and analyze training data for better management. Furthermore, wearable technology can be used for rehabilitation and managing chronic conditions such as chronic pain, providing patients with the necessary information to make informed decisions about their treatment.

More information can be found here.