This paper presents propagation measurement results at 60 GHz in order to determine the characteristics of indoor radio channels between fixed terminals. Path loss measurements are reported for line-of-sight (LoS) and non-line-of-sight (NLoS) cases, fading statistics in a physically stationary environment are extracted and a detailed investigation of the people movement effect on the temporal fading envelope is performed. Models that presented to predict path loss provide excellent fitting with errors of 1.13 and 3.84 dB for LoS and NLoS topographies, respectively. The dynamic range of fading in a quiescent environment is 8.8 dB and increased to 35 dB when a person moves between the fixed terminals with the channel becoming extremely nonstationary. Temporal variations induced by the moving people depend on the speed, the number of individuals the body sizes and the environment. Slow fading is observed as well as a quasi-wide-sense stationary (QWSS) behavior of the fading, but up to 50 ms of time.
In this paper, a methodology is described in order to investigate the performance of empirical mode decomposition (EMD) in biomedical signals, and especially in the case of electrocardiogram (ECG). Synthetic ECG signals corrupted with white Gaussian noise are employed and time series of various lengths are processed with EMD in order to extract the intrinsic mode functions (IMFs). A statistical significance test is implemented for the identification of IMFs with high-level noise components and their exclusion from denoising procedures. Simulation campaign results reveal that a decrease of processing time is accomplished with the introduction of preprocessing stage, prior to the application of EMD in biomedical time series. Furthermore, the variation in the number of IMFs according to the type of the preprocessing stage is studied as a function of SNR and time-series length. The application of the methodology in MIT-BIH ECG records is also presented in order to verify the findings in real ECG signals.
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