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Electronics


circuit designs that are impractical to realise with low-cost technologies. Although the work is in its early stages, Sporea believes that, in time, carefully designed circuits for specific applications could be significantly smaller, lighter and cheaper to make. “Because of the high-energy efficiency, batteries can be made smaller or removed altogether if alternative sources of energy can be used. In particular, where sensors or monitors have a disposable element, our approach could also reduce waste.” Elsewhere, an international research team led by Mahsa Shoaran, a professor at the Institute of Electrical Engineering & Center for Neuroprosthetics at EPFL in Switzerland, has received a $6.6m grant from the US National Institute of Mental Health to use Shoaran’s own tiny AI systems to treat severe psychiatric illnesses. Though they use many of the same techniques as Song and Sporea’s devices, these are designed to operate inside the body. “Mental disorders seem to arise more from communication failures between brain regions, than from dysfunction of any single region,” Shoaran explained when the grant was announced in October 2020. “We will develop a new implantable microchip for treating severe psychiatric illness by adjusting the patterns of activity in certain brain circuits. Our device will implement new algorithms that measure and control the rhythmic firing of neurons in distributed brain networks, restoring patterns of healthy communication in the brain.” Shoaran’s lab specialises in low-power integrated circuits for neural signal processing and closed-loop stimulation. Its systems incorporate modern machine learning techniques, using decision trees optimised for the hardware and algorithm, directly on the chip, meaning brain functions can be tracked and stimulated with unprecedented efficiency.


“The translational challenge is that efficient, real- time synchrony monitoring requires signal processing capabilities not found in any existing or anticipated neuromodulation device,” added Shoaran. “We have developed power-efficient synchrony estimation circuits, specifically optimised for DBS [deep brain stimulation]-like implants that will enable us to achieve this goal.”


AI for simplicity


Thanks to projects like those being led by Song, Sporea and Shoaran, it may soon be possible to augment simple devices with AI algorithms to obtain accurate measurements without using time- consuming and invasive diagnostic procedures. “Data-driven AI algorithms together with simple devices may achieve similar measurement precision to complicated devices, while being much more efficient and less painful,” says Song. Likewise, Sporea believes that the work he is doing will have benefits for manufacturers and patients: “The whole package is very compelling. Low-cost fabrication, robust operation and superior functionality are very likely to bring many interesting developments to monitoring and therapies, with increased comfort and convenience.” As machine learning becomes more portable and medical devices converge with personal technologies, it’s clear there is much to consider, address and even mitigate. Ensuring the safety of closed-loop AIs implanted in people’s brains is an entirely new challenge for regulators, but understanding how patients interact with apps is similarly difficult. Affording patients the ability to better self-manage, not to mention removing the need entirely, can be both liberating and beneficial; doing it safely is the next challenge. ●


 


 


 9” x 3.8” footprint, 40mm height  Operating input range 85-264VAC  Output voltage 24-56VDC  Up to 1200W boost power for 10sec  Analog and digital control and monitoring  5VSB AUX and adjustable 5-12VDC Fan output


WE POWER YOUR PRODUCTS recom-power.com/1200-V


MMI048_RECOM.indd 1 Medical Device Developments / www.nsmedicaldevices.com 26/03/2021 10:59 75


 -40° to +80°C operating temperature range  Operation mode indication signals  Medical, industrial, and ITE safety certified


 2 MOPP insulation system, suitable for BF type applications


 Compliant to EMI class B limits with sufficient margin $6.6m


Grant from the US National Institute of Mental Health to an international research team led by Mahsa Shoaran to use tiny AI systems to treat severe


psychiatric illnesses. EPFL


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