From: Real time reconstruction of quasiperiodic multi parameter physiological signals
Experiment 1: segmentation | Experiment 2: reconstruction |
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Additive white Guassian noise (AWGN): we use a standard AWGN algorithm [[22]] | |
Transient corruption: We use the following types of transient corruptions. | Non-Gaussian corruption: We use the following types of structured (non-Guassian) interferences in the evaluation of reconstruction. We use MIT-BIH noise stress test database[23] and nstdbgen[24] to generate these interferences. |
∙ Signal interruption: We make the amplitude of the signal zero. | |
∙ Exponential Damping: For signal x(t);1 ≤ t ≤ ℓ x , we damp the signal amplitude by applying the function f(x(t)) = x(t)e(−βt). Here, β = 0.001 is damping coefficient. |  |
∙ Overshooting and clipping: We amplify the signal by a randomly chosen factor (uniformly distributed) between 1 and 5, and clip at the maximum and minimum values of the original signal. | ∙ Electromagnetic interference (EM) |
∙ Muscle artifact (MA) | |
∙ Baseline wander(BW) | |
∙ Super imposition of high frequency signal: We add white noise of the same power as the signal, high pass filtered at 150 Hz. |  |
∙ Super imposition of low frequency signal: We add white noise of the same power as the signal, low pass filtered at 0.05 Hz. |  |