NeuroCam: a 4096-channel flexible brain-machine interface
Peer-Reviewed Publication
Updates every hour. Last Updated: 29-Dec-2025 13:11 ET (29-Dec-2025 18:11 GMT/UTC)
This study develops an electrocorticography (ECoG) device named NeuroCam, which boasts up to 4096 recording channels with only 128 leads for signal fan-out, supporting large-scale manufacturing. This innovation delivers a pivotal breakthrough in overcoming the key bottlenecks of existing ECoG devices, including limited channel counts, low density, complicated wiring, and challenges in scaling production. It provides a novel tool for decoding complex neural activities, supports the breakthrough development of advanced brain-machine interface (BMI) technology, and opens up opportunities for neuroscience research as well as the diagnosis and treatment of neurological disorders such as epilepsy.
China, Tianjin-Researchers at Nankai University have 3D-printed soft hydrogel thermocell “power patches” that can hug skin and devices, turning gentle temperature differences into electricity. By Combining 3D printing and immersion activation strategies, they “sculpt” microstructured hydrogel thermocell surfaces that grip rough, moving heat sources and boost power output several-fold. These patches can also serve as self-powered touch and motion sensors, suggesting that customizable wearable power supplies could quietly harvest waste heat from bodies and irregular heat sources for future sustainable, human-integrated electronics.
To tackle the high energy and latency costs of compressed sensing workloads in edge computing, researchers at Tsinghua University developed a memristor-based compressed sensing accelerator (memCS). By utilizing a computing-in-memory (CIM) architecture and hardware-software co-optimization framework to mitigate accuracy loss from hardware non-idealities, the memCS achieved a near-software computing accuracy (31.11 dB peak signal-to-noise ratio) while delivering an 11.22x speedup and 30.46x energy savings compared to GPUs, paving the way for efficient edge computing.