The rapid development in medical devices and communication technologies led to the
emergence of the Internet of Medical Things (IoMT), resulting in several new applications …

The ability to design smarter, more predictive healthcare solutions for use in the community
(at work and at home) and in healthcare facilities has been greatly enhanced by recent …

In this paper, an algorithm is proposed for efficient compression of bio-signals based on
discrete Tchebichef moments and Artificial Bee Colony (ABC). The Tchebichef moments are …

Electroencephalography (EEG) signal is a crucial biomedical signal that helps assess the
psychological, neural, and cognitive conditions of the human brain. However, the huge size …

Abstract Background and objective Brain-Computer Interfaces (BCI) are used to provide
environmental interaction among individuals, especially people with disabilities. Spelling …

Communication of bioelectric signals, such as electroencephalography (EEG) signals, will
be a key technology for smooth interaction between users and remote robots. The existing …

Analog discrete cosine transform (DCT) with CMOS image sensor is an advantageous
alternative in low power wireless Compressed Sensing (CS) Systems. The researchers have …

This paper proposes a comprehensive review of Electroencephalography (EEG) data
analytics. The EEG signal definition and the analysis process are presented. The public EEG …

Brain computer interfaces (BCI) are used through event-related potentials. An example of
BCI systems is speller systems, which aims to identify the letter that focused through visual …

This dissertation research presents a novel physiologically-aware and fidelity-preserving
communication architecture for the transmission of biomedical signals for applications in …