Neural Networks for Real-Time Signal Processing in Nano-Bio-Electronic Devices

Nano-bio-electronic devices are at the forefront of technological innovations that integratenanotechnology with biological systems, offering applications in fields such as medical diagnostics,environmental monitoring, and bioelectronics. These devices interface with living tissues or cells todetect biological signals, offering a wide range of opportunities. However, one of the primary challengesin such systems is the efficient and effective real-time signal processing of complex biological signals,which are often noisy, non-linear, and dynamic in nature. Traditional signal processing techniques maynot always be effective in handling the diverse complexities of biological signals, creating a gap thatmachine learning, particularly neural networks, can fill. This article explores the potential of using neuralnetworks for real-time signal processing in nano-bio-electronic devices, focusing on how these modelscan enhance the accuracy, speed, and efficiency of signal interpretation in bioelectronic systems.