RF Energy Harvesting Wireless Communications: RF Environment, Device Hardware and Practical Issues.

Radio frequency (RF) based wireless power transfer provides an attractive solution to extend the lifetime of power-constrained wireless sensor networks. Through harvesting RF energy from surrounding environments or dedicated energy sources, low-power wireless devices can be self-sustaining and environment-friendly. These features make the RF energy harvesting wireless communication (RF-EHWC) technique attractive to a wide range of applications.

Receiver-Initiated Handshaking MAC Based on Traffic Estimation for Underwater Sensor Networks .

In underwater sensor networks (UWSNs), the unique characteristics of acoustic channels have posed great challenges for the design of medium access control (MAC) protocols. The long propagation delay problem has been widely explored in recent literature. However, the long preamble problem with acoustic modems revealed in real experiments brings new challenges to underwater MAC design.

A numerical study of the effect of varied blood pressure on the stability of carotid atherosclerotic plaque.

Background: Blood pressure (BP) is associated with early atherosclerosis and plaque rupture because the BP variability can significantly affect the blood flow velocity and shear stress over the plaque. However, the mechanical response of BP variability to the plaque remains unclear. Therefore, we investigated the correlation between different maximum systolic blood pressure (SBP) and the stress distribution on plaque, as well as the stress over the plaque and blood velocity around the plaque using different BP variations, which are the BP variability in different phases during one cardiac cycle and beat-to-beat BP variability.

Investigation on cardiovascular risk prediction using genetic information.

Cardiovascular disease (CVD) has become the primary killer worldwide and is expected to cause more deaths in the future. Prediction and prevention of CVD have therefore become important social problems. Many groups have developed prediction models for asymptomatic CVD by classifying its risk based on established risk factors (e.

Comparison of median filter and discrete dyadic wavelet transform for noise cancellation in electrocardiogram.

Development of noise cancellation algorithm is essential to facilitate accurate detection of electrocardiogram (ECG) in mobile health and wearable medical devices. In this study, we captured ECG from 20 subjects when they were at rest and during routine activities. The motion artifact in ECG was filtered using two non-linear filters: median filter and discrete dyadic wavelet transform.

Simulation of induced electric field distribution based on five-sphere model used in rTMS.

Repetitive Transcranial magnetic stimulation (TMS) is a relatively new technique, which is non-invasive and painless used to stimulate the central and peripheral neural tissues. The principle is generating time-varying magnetic fields to stimulate the cerebral cortex neuron and inducing eddy current inside the tissues. Many researches study on the distributing of magnetic field and electric field induced inside the human brain, whereas the static electric field was neglected roughly in many studies.