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adding the figure for the most recent period, will update the total figure. Therefore, keeping the moving average up to date is a simple task. For example, if the actual guest count in the thirteenth month was 2,296, the new 12-month total is: 30,003 2,406 2,296 29,893

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As stated previously, an EEG signal can re ect brain activities; therefore, it is regarded as a powerful tool to analyze cerebral consciousness status (e.g., coma and quasi-braindeath). We distinguish cerebral consciousness status by analyzing EEG frequency components within the frequency range from 0 Hz to 30 Hz; in particular, we are interested (See Table 10.2) in the delta range (0.5 to 4 Hz), theta range (4 to 8 Hz), alpha wave (8 to 12 Hz), and 13 Hz components within the low beta range. This is because the patients are in a state of coma, as noted before, and this means that the brain activity of interest dominates lower-frequency ranges. We consider two patients (patient 1 and patient 2) in a coma state. EEG data for each patient has been provided by [3]. Since these recordings were collected, patient 1 has a wakened from coma while patient 2 has died. It is proposed to apply EMD to extract the relevant features from the EEG data and to illustrate how these features can be used to detect inevitable brain death in patient 2. Time amplitude plots of length one second for each of the six EEG channels (FP1, FP2, . . . , etc.) for patient 1 and patient 2 are given in the left columns of Figures 10.6 and 10.7, respectively. EMD was applied to each of the channels to decompose them into their IMFs and the resulting Hilbert spectrum was computed. The Hilbert spectrum of each channel within the range 0 to 30 Hz is given in Figures 10.6 and 10.7, respectively. The third column of each gure shows the frequency amplitude plots for each channel obtained by averaging the corresponding Hilbert spectrum plots.

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t Considering that near the convergence (D^r , D^r , D^r , cD^r ) will be small in comx y z parison with (^r , ^r , ^r , c^r ), a rst-order Taylor series development is possible and x y z t leads to f (^r Dxr , ^r Dyr , ^r Dzr , ^r Dtr ) x y z t f (^r , ^r , ^r , ^r ) x y z t @f (^r , ^r , ^r , c^r ) x y z t @f (^r , ^r , ^r , c^r ) x y z t Dxr Dyr @^r x @^r y (8:9)

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