Exploring neuromorphic computing based on spiking neural networks: Algorithms to hardware

N Rathi, I Chakraborty, A Kosta, A Sengupta… - ACM Computing …, 2023‏ - dl.acm.org
Neuromorphic Computing, a concept pioneered in the late 1980s, is receiving a lot of
attention lately due to its promise of reducing the computational energy, latency, as well as …

Deep learning for healthcare applications based on physiological signals: A review

O Faust, Y Hagiwara, TJ Hong, OS Lih… - Computer methods and …, 2018‏ - Elsevier
Background and objective: We have cast the net into the ocean of knowledge to retrieve the
latest scientific research on deep learning methods for physiological signals. We found 53 …

[HTML][HTML] Neural interface systems with on-device computing: machine learning and neuromorphic architectures

J Yoo, M Shoaran - Current opinion in biotechnology, 2021‏ - Elsevier
Highlights•Neural interfaces continue to improve in channel count and form factor.•Low-
power machine learning and neuromorphic processors can be integrated onto neural …

Seizure forecasting from idea to reality. Outcomes of the my seizure gauge epilepsy innovation institute workshop

SB Dumanis, JA French, C Bernard, GA Worrell… - Eneuro, 2017‏ - eneuro.org
Abstract The Epilepsy Innovation Institute (Ei2) is a new research program of the Epilepsy
Foundation designed to be an innovation incubator for epilepsy. Ei2 research areas are …

[کتاب][B] Integration of IoT with cloud computing for smart applications

R Anand, S Juneja, A Juneja, V Jain, R Kannan - 2023‏ - books.google.com
Integration of IoT with Cloud Computing for Smart Applications provides an integrative
overview of the Internet of Things (IoT) and cloud computing to be used for the various …

Building integrated systems for healthcare considering mobile computing and IoT

R Anand, AV Daniel, AL Fred, T Jaiswal… - Integration of IoT with …, 2023‏ - taylorfrancis.com
The healthcare industry stands to be profoundly impacted by the dramatic advances that
mobile computing and the Internet of Things (IoT) can bring. The IoT and mobile computing …

A robust low-cost EEG motor imagery-based brain-computer interface

SAC Yohanandan, I Kiral-Kornek… - 2018 40th Annual …, 2018‏ - ieeexplore.ieee.org
Motor imagery (MI) based Brain-Computer Interfaces (BCIs) are a viable option for giving
locked-in syndrome patients independence and communicability. BCIs comprising …

Machine learning in healthcare: A review

A Saini, AJ Meitei, J Singh - Proceedings of the international …, 2021‏ - papers.ssrn.com
This study attempts to introduce artificial intelligence and its significant subfields in machine
learning algorithms and reviews the role of these subfields in various areas in healthcare …

Denoising algorithm for event-related desynchronization-based motor intention recognition in robot-assisted stroke rehabilitation training with brain-machine …

T Jia, K Liu, C Qian, C Li, L Ji - Journal of Neuroscience Methods, 2020‏ - Elsevier
Background Rehabilitation robots integrated with brain-machine interaction (BMI) can
facilitate stroke patients' recovery by closing the loop between motor intention and actual …

Advanced computing and related applications leveraging brain-inspired spiking neural networks

L Sima, J Bucukovski, E Carlson, NL Yien - arxiv preprint arxiv …, 2023‏ - arxiv.org
In the rapid evolution of next-generation brain-inspired artificial intelligence and increasingly
sophisticated electromagnetic environment, the most bionic characteristics and anti …