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The sampling frequency of this data set is 128 Hz For our experimental setup, a subset of the database containing 13 subjects was formed The selection was based on the length of the recordings Waveforms with many artifacts offer limited heartbeat information and thus they were not used in our experiments Once again, the signals were partitioned into two halves, one to build the gallery set, and one to test the system The PTB database is offered from the National Metrology Institute of Germany The data set contains 549 ECG recordings from 294 subjects and every record includes the conventional 12-leads and 3 Frank leads ECG The sampling frequency of these recordings is 1 kHz In addition, for every subject in the PTB database, at least two recordings are offered, collected a few years apart A subset of 14 healthy subjects was formed from the PTB database.

stansTelephone.OffHook(); stansTelephone.DialNumber( 1-900-4CF-CHIX );

(0.181)

The criteria for the selection of the records were to illustrate healthy ECG waveforms and to have at least two recordings for every.

Clearly, your telephone and Stan s telephone can do the same kinds of things because they are both objects of the Telephone class, but each telephone might do the same thing in a different way (such as dial a different number) because each is a separate, distinct instance of a Telephone. Your instance of a Telephone is named yourTelephone, and Stan s instance of a Telephone is named stansTelephone. Each instance is a complete, standalone copy of all the properties and methods that any Telephone has.

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Stan s telephone is similar to most other telephones, but his probably has a few functions that a public telephone doesn t have, and his probably doesn t have some of the functions of Larry Ellison s telephone (such as Oracle-based speed dial). Stan was so enamored with his date that he has asked the factory to invent a Stan-specific telephone with a special speed-dial function, as the following code describes:

subject. The older recording of every subject was used to build the gallery set, and the newer one was used to test the performance of the method. Throughout the experimentation procedure, the three data sets were combined to achieve more general results. In order to fuse the recordings into one data set, resampling was performed when necessary.

class StanPhone extends Telephone { SpeedDial(theNumber) { this.OffHook(); if (theNumber == 1 ) { this.DialNumber( 1-900-4CF-CHIX ); } } }

And Stan wants the factory to manufacture one of these phones for him, as follows:

When a subject arrives to the system to be identi ed, 5 s of his/her ECG is collected and subjected to preprocessing, to eliminate the effects of noise. Having prepared the signals for further analysis, the normalized autocorrelation is computed, and several window lengths of the AC are tested for dimensionality reduction and classi cation, so that the optimal one is identi ed. Even though its possible that windows of AC which correspond to the length of a heartbeat from the ECG offer high performance, it is important to note that not all waves of a heartbeat are invariant to stress conditions, risking this way the identi cation performance in anxiety situations. However, there is evidence that the QRS complex is less affected by emotional conditions [22] compared to the rest of the waves; thus the corresponding AC window length is suggested to be more appropriate for feature extraction. Table 16.1 shows the window and subject recognition rates when the system is tested on different autocorrelation window lengths M. The number of DCT coef cients used for identi cation is denoted by C, while the corresponding number of LDA features after dimensionality reduction depends on the size of the data set. These experiments are performed on the combined healthy data sets of the PTB and MIT healthy databases. Splitting the available ECGs into segments of 5 s each, a test set of 506 windows from 27 subjects is generated. Both the AC/DCT and AC/LDA achieve their highest performance for an AC window length that corresponds approximately to the QRS

Figure 14.6 Projection of reliability index versus factor of safety (without model error). (Christian, J. T., Ladd, C. C. and Baecher, G. B., 1994, Reliability Applied to Slope Stability Analysis, Journal of Geotechnical Engineering, ASCE, Vol. 120, No. 12, pp. 2180 2207, reproduced by permission of the American Society of Civil Engineers.)

stansnewTelephone = new StanPhone();

Table 16.1. Classi cation Performance of the AC/DCT and AC/LDA Method on the PTB Database M 10 20 30 50 70 100 150 200 C (DCT only) 7 13 19 32 44 63 94 125 Subject Rate DCT 25/27 25/27 26/27 25/27 25/27 23/27 25/27 23/27 Window Rate DCT 401/506 416/506 437/506 426/506 421/506 377/506 347/506 337/506 Subject Rate LDA 26/27 26/27 27/27 25/27 24/27 24/27 23/27 24/27 Window Rate LDA 464/506 461/506 485/506 441/506 434/506 433/506 412/506 400/506

Now, whenever Stan wants to talk with a beautiful, intelligent ColdFusion programmer of the female persuasion, all he must do is the following:

stansnewTelephone.SpeedDial ( 1 );

16

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