About the project
Implantable BCIs are limited by a strict power budget to prevent thermal tissue damage. Wireless data transmission consumes most power, especially as channel counts scale. This project focuses on designing ultra-low-power ASICs that perform on-chip neural processing, drastically reducing bandwidth needs while maintaining decoding accuracy.
Implantable Brain-Computer Interfaces (BCIs) hold the promise of restoring communication and mobility for individuals with paralysis, as well as enabling new therapeutic avenues for neurological disorders. However, the clinical translation of high-performance BCIs is fundamentally limited by one critical constraint: power consumption.
State-of-the-art implantable BCIs with high-channel-count microelectrode arrays generate massive amounts of neural data, hundreds of megabits per second, yet must operate within a strict power budget of tens of milliwatts to prevent tissue damage from heat dissipation. Wireless data transmission, the dominant power consumer in current systems, creates a fundamental bottleneck. The solution lies not in transmitting raw data, but in intelligent, on-chip processing.
This project focuses on the design of ultra-low-power digital Application-Specific Integrated Circuits (ASICs) that embed intelligence directly at the neural interface. You will develop custom silicon architectures that perform on-chip neural signal processing, feature extraction, and inference, radically reducing wireless bandwidth requirements while maintaining high decoding accuracy.
Implantable BCIs face a fundamental physical bottleneck: thermal dissipation. The human body tolerates only minimal temperature rise in neural tissue (typically < 1–2°C above body temperature), which limits implantable electronics to a power budget of approximately 10–50 milliwatts for a high-channel-count system. Within this tight constraint, wireless telemetry, the transmission of raw neural data through the skin, can consume 80–90% of the total power. As channel counts scale toward 1,000+ electrodes to achieve higher decoding accuracy, this problem becomes exponentially worse. Simply improving battery life or wireless protocols is insufficient; the solution requires a fundamental architectural shift.
The School of Electronics and Computer Science is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.
