Electrophysiological recordings of neural activity in a mouse's brain are very popular among neuroscientists for understanding brain function. One particular area of interest is acquiring recordings from the Purkinje cells in the cerebellum in order to understand brain injuries and the loss of motor functions. However, current setups for such experiments do not allow the mouse to move freely and, thus, do not capture its natural behaviour since they have a wired connection between the animal's head stage and an acquisition device. In this work, we propose a lightweight neuronalspike detection and classification architecture that leverages on the unique characteristics of the Purkinje cells to discard unneeded information from the sparse neural data in real time. This allows the (condensed) data to be easily stored on a removable storage device on the head stage, alleviating the need for wires. Synthesis results reveal a >95% overall classification accuracy while still resulting in a small-form-factor design, which allows for the free movement of mice during experiments. Moreover, the power-efficient nature of the design and the usage of STT-RAM (Spin Transfer Torque Magnetic Random Access Memory) as the removable storage allows the head stage to easily operate on a tiny battery for up to approximately 4 days.

Modern Implantable Medical Devices (IMDs) feature wireless connectivity, which makes them vulnerable to security attacks. Particular to IMDs is the battery Denial-of-Service attack whereby attackers aim to fully deplete the battery by occupying the IMD with continuous authentication requests. Zero-Power Defense (ZPD) based on energy harvesting is known to be an excellent protection against these attacks. This paper establishes essential design specifications for employing ZPD techniques in IMDs, offers a critical review of ZPD techniques found in literature and, subsequently, gives crucial recommendations for developing comprehensive ZPD solutions.

Implantable Medical Devices (IMDs) such as pacemakers and neurostimulators are highly constrained in terms of energy. In addition, the wireless-communication facilities of these devices also impose security requirements considering their life-critical nature. However, security solutions that provide considerable coverage are generally considered to be too taxing on an IMD battery. Consequently, there has been a tendency to adopt ultra-lightweight security primitives for IMDs in literature. In this work, we demonstrate that the recent advances in embedded computing in fact enable the IMDs to use more mainstream security primitives, which do not need to compromise significantly on security for fear of impacting IMD autonomy.