Pressure sensors inspired by nature for non-invasive surgeries
CategoriesSustainable News

Pressure sensors inspired by nature for non-invasive surgeries

Pressure sensors inspired by nature for non-invasive surgeries

Spotted: Surgeons are increasingly turning to robotics to assist with surgeries. Many of these involve ‘graspers’ – tools controlled remotely by the surgeon. One drawback of these tools is that the surgeon cannot feel exactly how much pressure is being exerted. While pressure sensors are used for this, they often lack the precision required for delicate surgeries.

Now, researchers at the National University of Singapore (NUS) have developed a novel aero-elastic pressure sensor, called ‘eAir’, which they hope will address these challenges. The sensor could potentially transform some types of surgery by enabling better tactile feedback for surgeons, allowing more precise manipulation of patient tissues.

Conventional pressure sensors have trouble delivering consistent readings and can miss subtle changes in pressure – leading to potential errors. To address this, the NUS team drew inspiration from a phenomenon known as the ‘lotus leaf effect’. This is a natural phenomenon where minuscule, water-repelling structures cause water droplets to roll off a leaf’s surface. The team has engineered a sensor that mimics this effect, detecting minute pressure changes.

The eAir sensor includes a liquid and a trapped layer of air. As external pressure increases, the air layer compresses. The surface of the sensor registers the movement at the interface of air and liquid, triggering a change in electrical signals that accurately reflects even minute amounts of exerted pressure.

The NUS team is hoping to collaborate with key players in the medical field to develop the so. They have filed a patent for the eAir sensor technology in Singapore, and are working to refine the sensor for real-world applications.

This is not the first time we have seen researchers take inspiration from the natural world. Springwise has also covered cancer researchers who used spiders for inspiration and energy-saving paints inspired by butterflies.

Written By: Lisa Magloff

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A supercomputer for AI inspired by the human brain
CategoriesSustainable News

A supercomputer for AI inspired by the human brain

A supercomputer for AI inspired by the human brain

Spotted: Artificial intelligence (AI) is already making inroads into our daily lives through virtual assistants, image recognition, and financial fraud detection. However, even the best AI hardware is still a long way from the energy-efficient, low latency, and high-throughput processing our own brains are capable of – but maybe not for long.

Back in 2018, researchers at the Advanced Processor Technologies Research Group at the University of Manchester developed SpiNNaker (spiking neural network architecture) — a supercomputer architecture that mimicked the interactions of biological neurons. SpiNNaker is being used as one component in the Human Brain Project (HBP), a 10-year project that aims to create an ICT-based research infrastructure for brain research, cognitive neuroscience, and brain-inspired computing.

In 2019, the second-generation SpiNNaker 2 was developed by Technische Universität Dresden in collaboration with the University of Manchester. From this project, SpiNNcloud – a Technische Universität Dresden spinoff – was born. The company’s unique computer hardware is used for applications such as robotics, sensing, and prediction.

Now, SpiNNcloud has announced it is receiving a €2.5 million grant from the European Innovation Council (EIC) for its newest project, “SpiNNode: SpiNNaker2 on the edge”. The funding will be used to expand and develop brain-inspired hardware for mobile applications and test it in real-life industrial situations.

The need for energy-efficient hardware has become more pressing with the development, and widespread adoption, of more sophisticated AI models. Christian Eichhorn, Co-CEO of SpiNNcloud Systems, explains, “AI such as ChatGPT is now entering our everyday lives and, therefore, represents a revolution comparable to that of the internet. Training this AI model consumes as much electricity as 3,000 households use in a month (…) We are working on the most energy-efficient computing hardware for large-scale applications, as this will be key to significantly reducing the carbon footprint of AI.”

Advances in AI are coming thick and fast, and Springwise has spotted several recent innovations, including the development of faster and more efficient optical neural networks, and numerous products such as a platform for tracking the climate footprint of food products.

Written By: Lisa Magloff

Reference