Health Sensing and Microsystems

We operate at the interface of electrical engineering, biomedical engineering, and clinical translation. The group focuses on the surrounding technologies that enable wearable and implantable medical devices to operate reliably outside the laboratory, with particular emphasis on communications, data, security, power, and system-level integration.

Our research is motivated by the observation that many promising bioelectronic devices fail not because the sensor is inadequate, but because the supporting infrastructure is underdeveloped. We therefore treat sensing, computation, wireless communication, and power management as a single co-designed system. This systems-first approach allows us to address constraints such as long-term autonomy, data integrity, latency, privacy, and robustness early in the design process.

Application-wise, the group works across several domains. In neurotechnology, we develop architectures for the acquisition, compression, transmission, and secure handling of high-throughput neural data, with a focus on low-latency and low-power operation suitable for wearable and implantable platforms. In parallel, we work with clinical datasets from wearable devices aimed at monitoring stress, pain, and neurological conditions, where challenges around data quality, synchronisation, annotation, and explainability are as important as the sensing hardware itself. These application areas serve both as scientific drivers and as realistic testbeds for the technologies we develop.

From a technical standpoint, the group builds complete electronic and computational stacks. This includes analogue front ends for biopotential and biosignal acquisition, embedded electronics and mixed-signal systems for sensor interfacing, low-power wireless backends, and end-to-end firmware stacks that span device, gateway, and edge processing. Power-aware design is central to our work, encompassing ultra-low-power architectures, duty-cycled operation, and energy-constrained computation. Security and data governance are treated as design constraints, not afterthoughts, particularly for systems intended for clinical deployment.

Clinical translation is a defining component of the group's philosophy. We collaborate with clinicians and translational researchers to ensure that engineering decisions are informed by real clinical workflows, regulatory constraints, and patient needs. The aim is to build platforms that can realistically move from proof-of-concept prototypes towards clinical studies and real-world deployment.

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