Real-time processing and decoding of neural signals play a crucial role in biohybrid
neuroprostheses, as they provide feedback to modulate or replace neural function …

The recent years have seen unprecedented growth in the manufacturing of
neurotechnological tools. The latest technological advancements presented the …

With the increase in population around the world along with the rise of chronic diseases, it is
a need of the hour to develop efficient healthcare systems that manage and deliver the …

This paper focuses on ultra-low power embedded classification of neural activities. The
machine learning (ML) algorithm has been trained using evoked local field potentials (LFPs) …

Personalization of gait neuroprosthetics is paramount to ensure their efficacy for users, who
experience severe limitations in mobility without an assistive device. Our goal is to develop …

Spike-based neuromorphic hardware has great potential for low-energy brain-machine
interfaces, leading to a novel paradigm for neuroprosthetics where spiking neurons in silicon …

Nanofabrication can help us to emulate natural intelligence. Forward-engineering brain
gained enormous momentum but still falls short in human neurodegenerative disease …

Brain signals are recorded using different techniques to aid an accurate understanding of
brain function and to treat its disorders. Untargeted internal and external sources …

Recent advances in neurotechnology allow neurological impairments to be treated or
reduced by brain machine interfaces and neuroprostheses. To develop energy-efficient and …

To understand brain functions and diagnose brain disorders, scientists have developed
various probing tools and techniques. This development has been facilitated by the rapid …