Emerging wearable interfaces and algorithms for hand gesture recognition: A survey

S Jiang, P Kang, X Song, BPL Lo… - IEEE Reviews in …, 2021 - ieeexplore.ieee.org
Hands are vital in a wide range of fundamental daily activities, and neurological diseases
that impede hand function can significantly affect quality of life. Wearable hand gesture …

EEG-based brain-computer interfaces (BCIs): A survey of recent studies on signal sensing technologies and computational intelligence approaches and their …

X Gu, Z Cao, A Jolfaei, P Xu, D Wu… - … /ACM transactions on …, 2021 - ieeexplore.ieee.org
Brain-Computer interfaces (BCIs) enhance the capability of human brain activities to interact
with the environment. Recent advancements in technology and machine learning algorithms …

Adaptive transfer learning-based multiscale feature fused deep convolutional neural network for EEG MI multiclassification in brain–computer interface

AM Roy - Engineering Applications of Artificial Intelligence, 2022 - Elsevier
Abstract Objective. Deep learning (DL)-based brain–computer interface (BCI) in motor
imagery (MI) has emerged as a powerful method for establishing direct communication …

Time series forecasting of Covid-19 using deep learning models: India-USA comparative case study

S Shastri, K Singh, S Kumar, P Kour… - Chaos, Solitons & Fractals, 2020 - Elsevier
Covid-19 is a highly contagious virus which almost freezes the world along with its economy.
Its ability of human-to-human and surface-to-human transmission turns the world into …

[HTML][HTML] Deploying machine and deep learning models for efficient data-augmented detection of COVID-19 infections

A Sedik, AM Iliyasu, B Abd El-Rahiem… - Viruses, 2020 - mdpi.com
This generation faces existential threats because of the global assault of the novel Corona
virus 2019 (ie, COVID-19). With more than thirteen million infected and nearly 600000 …

An efficient multi-scale CNN model with intrinsic feature integration for motor imagery EEG subject classification in brain-machine interfaces

AM Roy - Biomedical Signal Processing and Control, 2022 - Elsevier
Objective Electroencephalogram (EEG) based motor imagery (MI) classification is an
important aspect in brain-machine interfaces (BMIs) which bridges between neural system …

A comprehensive survey on the biometric recognition systems based on physiological and behavioral modalities

S Dargan, M Kumar - Expert Systems with Applications, 2020 - Elsevier
Biometrics is the branch of science that deals with the identification and verification of an
individual based on the physiological and behavioral traits. These traits or identifiers are …

Security and privacy for the internet of medical things enabled healthcare systems: A survey

Y Sun, FPW Lo, B Lo - IEEE Access, 2019 - ieeexplore.ieee.org
With the increasing demands on quality healthcare and the raising cost of care, pervasive
healthcare is considered as a technological solutions to address the global health issues. In …

[HTML][HTML] A one-dimensional CNN-LSTM model for epileptic seizure recognition using EEG signal analysis

G Xu, T Ren, Y Chen, W Che - Frontiers in neuroscience, 2020 - frontiersin.org
Frequent epileptic seizures cause damage to the human brain, resulting in memory
impairment, mental decline, and so on. Therefore, it is important to detect epileptic seizures …

Towards design and implementation of security and privacy framework for Internet of Medical Things (IoMT) by leveraging blockchain and IPFS technology

R Kumar, R Tripathi - the Journal of Supercomputing, 2021 - Springer
Abstract The Internet of Medical Things (IoMT) is the next frontier in the digital revolution and
it leverages IoT in the healthcare domain. The underlying technology has changed the …