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BackgroundHepatitis B virus (HBV) infection is a major global public health concern. Although recent findings suggest an inverse relationship between HBV infection and multiple myeloma (MM), the true relationship between these two conditions remains unclear.
AimThe primary aim of this meta‐analysis was to evaluate the association between HBV infection, defined as hepatitis B surface antigen positivity,...
To achieve a reliable two-dimensional control by noninvasive EEG-based brain-computer interface (BCI), users are typically required to receive long-term training to learn effective regulation of their brain rhythmic activities, and to maintain sustained attention during the operation. We proposed a two-dimensional BCI using event-related desynchronization and event-related synchronization associated...
Electroencephalography (EEG) is an appealing basis for brain-computer interface technology because EEG is non-invasive. However, because EEG signals are spatially blurred and typically have very low signal-to-noise ratios, extracting relevant information in the single-event case is challenging. The most easily accessible information is one-dimensional (for example, mu rhythm amplitude, average hemispherical...
Patients that suffer from loss of motor control would benefit from a brain-computer interface (BCI) that would, optimally, be noninvasive, allow multiple dimensions of control, and be controlled with quick and simple means. Ideally, the control mechanism would be natural to the patient so that little training would be required; and the device would respond to these control signals in a predictable...
People have the perception that prior to making a voluntary movement, there is an intention to move. The timing of this subjective impression has been measured using Libet's clock and is on average about 300 ms prior to EMG onset. EEG and MEG show activity prior to movement, and by the voltage measurement, there is a rising negativity called the Bereitschafts potential beginning about 1.5 s prior...
This study introduces a method for accurate identification of the waveform of the evoked potentials by decomposing the component responses. The decomposition was achieved by zero-pole modeling of the evoked potentials in the discrete cosine transform (DCT) domain. It was found that the DCT coefficients of a component response in the evoked potentials could be modeled sufficiently by a second order...
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