Comparison of two automated methods for QT interval measurement

Abstract

In this paper we compared two methods of automated QT interval measurement on standard ECG databases: the Root-Mean-Square (RMS) lead combining method aimed at QT monitoring and the method of median of lead-by-lead QT interval measurements.We IntroductionGlobal QT interval is one of the fundamental ECG measurements reported on virtually every 12 lead ECG. A longer than normal QT interval may indicate a congenital or acquired long QT condition [1][2][3]. The AHA/ACC practice guideline for ECG monitoring now includes a recommendation to monitor QT interval for the purpose of drug titration of drugs known to have a pro-arrhythmic effect [4]. If the QT interval lengthens by more than 60ms after starting the drug or the QT interval extends beyond 500 ms the administration of the drug should be stopped or the dosage can be reduced.We have previously presented Philips automated QT interval measurement algorithms for 12-lead ECG, Holter and ECG monitoring applications [5][6][7][8][9][10]. In the ambulatory Holter and patient monitoring ECG applications, the QT interval algorithm uses an RMS waveform from combined available high quality leads and measures QT interval on the RMS ECG. In the resting 12-lead ECG application, the global QT interval measurement is based on a lead-by-lead method. The open question is, of the two, which method is better ignoring the constraints of the application. In this paper, we compared the two automated methods and reported the results using the same ECG datasets. Study PopulationA comparison between automated methods aimed at either monitoring or ambulatory ECG versus 12-lead ECG is hampered by the gross difference in available ECG in each case. Ambulatory ECGs cannot be used to test the 12-lead QT algorithm because of low sample rate, narrow bandwidth and limited leads. For 12-lead ECG analysis, a sample rate of 500 sps and a bandwidth of 0.05 to 150Hz are required. Ambulatory ECG recordings often have sample rates around 200 sps and a cut-off frequency of 40Hz. Only selected parts of the 12-lead analysis are possible with the small number of leads used in an ambulatory or monitoring recording. On the other hand, the sample rate, bandwidth and number of leads may be adequate for a 12-lead ECG to be used for an ambulatory analysis, but the 10 second recording is not long enough for even the learning period of the ambulatory and monitoring algorithmsThe addition of the PTB set to the data publicly available at PhysioNet made this study possible because it has the features that allow direct comparison between ambulatory and 12 lead algorithms [11]. The PTB dataset consists of 549 records from 294 subjects with a sample

ECG Multilead QT Interval Estimation Using Support Vector Machines

“…In contrast, our algorithm performs the QT estimation using a multilead approach, where all leads have a similar weight as we are simply averaging the QT intervals measured in each of the leads. A bias in the estimation using this dataset has also been reported by other researchers [37, 38] during the validation of multilead QT estimation algorithms.…”

Philips QT Interval Measurement Algorithms for Diagnostic, Ambulatory, and Patient Monitoring ECG Applications

“…12 The two methods have different technical requirements and suitable for different environments. 12 The two methods have different technical requirements and suitable for different environments.…”

“…In summary, the two approaches we use in three different applications, namely diagnostic 12-lead, ambulatory Holter, and real time monitoring, provide comparable stable and accurate QT interval measurements. 12 The two methods have different technical requirements and suitable for different environments. We found that the QT measurement approach based on alpha-trimming and measurement of central tendency is most suitable for applications with 12 or more available leads.…”