Electroencephalogram (EEG) signals are useful in understanding the human brain diseases
like epilepsy which is characterized by an enduring predisposition to generate epileptic …

Electroencephalogram (EEG) is the biopotential recording of electrical signals generated by
brain activity. It is useful for monitoring sleep quality and alertness, clinical applications …

Wireless telemonitoring of physiological signals is an important topic in eHealth. In order to
reduce on-chip energy consumption and extend sensor life, recorded signals are usually …

On-chip neural data compression is an enabling technique for wireless neural interfaces that
suffer from insufficient bandwidth and power budgets to transmit the raw data. The data …

With the growth of telemedicine systems, transferring a large number of medical signals
such as for an EEG is a critical challenge. Intelligent analyzing systems, responsible for …

Abstract Advances in Compressed Sensing (CS) are enabling promising low-energy
implementation solutions for wireless Body Area Networks (BAN). While studies …

Electroencephalography (EEG) is widely used in clinical diagnosis, monitoring and Brain-
Computer Interface systems. Usually EEG signals are recorded with several electrodes and …

This letter proposes a novel 1.5-D algorithm for multi-channel electroencephalogram (EEG)
compression. The proposed algorithm only needs to perform 1-D Discrete Wavelet …

In this paper, we propose a novel approach for the compression of multichannel
electroencephalograph (EEG) signals. The method assumes that EEG signals are the linear …

In recent years, there has been a growing interest in the compression of
electroencephalographic (EEG) signals for telemedical and ambulatory EEG applications …