Objectives The availability of large and varied Electroencephalogram (EEG) datasets,
rapidly advances and inventions in deep learning techniques, and highly powerful and …

Wearable sensors offer great potential in sports, fitness, and medicine. However, their
limited battery life poses a major obstacle to their widespread use. This paper explores …

Denoising and compression of 2D and 3D images are important problems in modern
medical imaging systems. Discrete wavelet transform (DWT) is used to solve them in …

In clinical practice, sleep stage classification (SSC) is a crucial step for physicians in sleep
assessment and sleep disorder diagnosis. However, traditional sleep stage classification …

The purpose of this study is to solve the issues in reconstruction computation complexity of
the current method in wireless body area network (WBAN) through developing compressed …

We propose a framework that enables the cluster head (CH) to harvest energy from uplink
transmission by Internet of Things (IoT) nodes employing data compression under …

While numerous studies have explored using various sensing techniques to measure
attention states, moment-to-moment attention fluctuation measurement is unavailable. To …

Data compression is back bone of network traffic in data communication applications. It not
only helps in efficient utilization of the resources but also provides a seamless experience to …

The 5G networks will see implementation in mHealth in the upcoming years, and it becomes
increasingly important to be able to test and develop software for the new generation of …

Denoising and compression of tomographic images are important problems in modern
medical imaging systems. Discrete wavelet transform (DWT) is used to solve them in …