critical for assessing new treatments. Dynamic continuous ST-segment

recovery methods provide a quantitative marker of speed of reperfusion

with more information than serial static methods. However, continuous

data streams are hampered by data gaps caused by noise or artifact

despite optimal filtering. To overcome the impact of gaps on time until

first evidence of 50% or more reperfusion from peak ST levels (T1), we

used a novel statistical approach more attractive than simply eliminating

noisy data. If gaps occur before first observed recovery, T, then T may

or may not be T1. Our approach uniquely adjusts for variable data gaps

and multiple events.

Methods: A total of 610 continuous digital 12-lead ST-segment

recordings without gaps before T met criteria for analysis. Data gaps

were inputted into the gcleanh data streams with location and length

similar to historic ST-segment data. A gap likelihood function (GLF)

conditional on gap location was used to estimate T1. Standard statistical

methods are compared with the GLF using simulation methods to

compare efficiency, relative bias, and SD.

Results: See Table 1.

Conclusions: Gap likelihood function is more accurate than standard

statistical methods and provides more intuitive methodology for analyzing

continuous data streams.

doi:10.1016/j.jelectrocard.2005.06.058

Cosine-trend time-diversity electromagnetic interference filter for

electrocardiographic waveforms

Eric D. Helfenbein, A. Dean Forbes (Advanced Algorithm Research Center,

Philips Medical Systems, USA)

Digital electrocardiographic (ECG) recordings often contain unwanted

electromagnetic interference (EMI). Filtering techniques are usually

applied to remove the EMI so that the underlying physiological signal

can be processed. For high-resolution ECG applications such as

detection of afterpotentials or microvolt T-wave alternans, the major

challenge is to remove EMI while retaining the signal integrity. We have

designed a cosine-trend time-diversity EMI filter that has many

advantages over current EMI filtering methods and can be used for

both standard and high-resolution electrocardiography. The dominant

EMI in ECGs is usually the result of the sinusoidal power line and thus

usually appears as sinusoids at the power line frequency and a few of its

harmonics. A typical method for EMI removal is to process the

waveform with a digital notch or comb filter. Disadvantages of these

filters is that (1) they will bring,Q thereby introducing distortions; (2) they

remove signal of interest at the notch frequencies; and (3) they often do

not adapt to changes in power line frequency. The cosine-trend time-

diversity EMI filter takes advantage of gquieth regions between cardiac

cycles in the ECG signal during which time the EMI can be estimated.

First, the exact frequency of the EMI is determined using the fast

Fourier transform. Regression methods are then used to fit linear

combinations of basic functions composed of sine and cosine waves at

the power line frequency and its harmonics to the observed EMI. The

resulting estimate of the EMI signal is then subtracted from the ECG

waveform region of interest. We have applied this method to single

cardiac cycles using a sliding window approach and to longer regions

with excellent results. This novel filter method is highly adaptable to

variations in power line frequency and removes EMI with negligible

distortion to the underlying ECG.

doi:10.1016/j.jelectrocard.2005.06.059

Use of standards in the review of medical devices

Charles Ho, Donald Jensen, Frank Lacy, Neal Muni, Sabina Reilly,

Elias Mallis (Center for Devices and Radiological Health, Department

of Health and Human Services, US Food and Drug Administration,

Rockville, MD, USA)

The Center for Devices and Radiological Health of the US Food and Drug

Administration (FDA) uses a myriad of standards to facilitate the review of

premarket submissions of medical devices. The benefits of using standards

in this manner include providing a set of common requirements and test

protocols to the device manufacturer, thus reducing the manufacturer’s need

to breinvent the wheelQ each new bench test to ensure safety and

effectiveness of the device. Furthermore, with the present trend toward

international harmonization of standards, tests performed in accordance

with an international standard may be acceptable to several countries.

However, there are instances when the FDA does not agree with a few or

many provisions in a standard. This article aims to clarify the approaches

taken by FDA to balance or resolve disagreements. One approach begins

with the recognition of only some provisions of a standard or, more

commonly, excluding those parts of a standard that are unacceptable to the

FDA. Other approaches include working with the Standards Development

Organizations so that the standard can be revised to include a language that

is more agreeable to all parties involved. Specific examples will be

presented on medical devices such as electrocardiographic cables and

connectors, and noninvasive blood pressure monitors.

doi:10.1016/j.jelectrocard.2005.06.060

An objective test of T-wave alternans algorithm on noisy signals

Harry Hostetler a, Joel Xue b, Brian Young b, Willi Kaiser b, Martin Findeis b,

David Gutterman a ( aMedical College of Wisconsin, Milwaukee, Wisconsin,bGE Healthcare, Milwaukee, Wisconsin)

Background: T-wave alternans (TWA) has been associated with ventricular

arrhythmias. However, an objective test is needed to determine whether a

TWA signal can be identified in the presence of high levels of noise

generated during a typical exercise stress test when repolarization

variability may be augmented. A specific algorithm for isolating TWA

from electrocardiographic (ECG) signals during exercise was developed.

The purpose of this study was to test the hypothesis that the time domain

TWA algorithm can accurately quantify simulated exercise TWA patterns.

Methods: Noise was added to computer-generated ECG signals with

known TWA quantified by amplitude and phase. The TWA amplitude

varied from 0 to 100 lV measured as a peak-to-peak difference. The added

noise contained 3 basic types: high frequency with peak-to-peak voltage

varied from 20 to 500 lV, baseline wander varied from 0 to 2000 lV, andfiducial point shift from 0 to 16 m/s. This signal was then output to a

standard 12-lead ECG. Two systems were used to analyze this data: The

CASE system (GE Healthcare, Milwaukee, Wis), which is a standard stress

test machine, and a research workstation, which is a system that can run

experimental stress test algorithms. The experiment was repeated using

physiological noise from the MIT database. This noise was then applied to

the computer-generated ECG with known TWA. The TWA amplitude was

again varied from 0 to 100 lV.Results: From this, the CASE sensitivity in the time domain was found to be

75% at 9 lV, 83% at 38 lV, and 84% at 87 lV of alternans in combined

background noise. These peak-to-peak voltages are equivalent to 4, 10, and

20 lV, respectively, of mean TWA as measured in the frequency domain.

Table 1

Method Parameter Relative bias SD Median

True values 0.0168 – – 41

Exclude data with gaps 0.0232 0.34 0.005 30

Standard interval censor 0.0189 0.12 0.002 37

Standard right censor 0.0176 0.05 0.002 39

GLF 0.0171 0.00 0.002 41

Poster Session II / Journal of Electrocardiology 38 (2005) 88–93 89