In comparison to traditional bulky and rigid electronic devices, the human–machine
interaction (HMI) system with flexible and wearable components is an inevitable future trend …

Abstract Time Series Classification (TSC) involves building predictive models for a discrete
target variable from ordered, real valued, attributes. Over recent years, a new set of TSC …

Decoding speech from brain activity is a long-awaited goal in both healthcare and
neuroscience. Invasive devices have recently led to major milestones in this regard: deep …

Advances in brain science and computer technology in the past decade have led to exciting
developments in brain–computer interface (BCI), thereby making BCI a top research area in …

Patients with amyotrophic lateral sclerosis (ALS) can lose all muscle-based routes of
communication as motor neuron degeneration progresses, and ultimately, they may be left …

Brain–computer interfaces (BCIs) development is closely related to physics. In this paper, we
review the physical principles of BCIs, and underlying novel approaches for registration …

Over the last few decades, the Brain-Computer Interfaces have been gradually making their
way to the epicenter of scientific interest. Many scientists from all around the world have …

In 2002, the UCR time series classification archive was first released with sixteen datasets. It
gradually expanded, until 2015 when it increased in size from 45 datasets to 85 datasets. In …

Although pre-trained transformers and reprogrammed text-based LLMs have shown strong
performance on time series tasks, the best-performing architectures vary widely across …

Brain–computer interfaces (BCIs) use brain activity to control external devices, thereby
enabling severely disabled patients to interact with the environment. A variety of invasive …