W. J. Tompkins

Publications151
h-index40
Citations14,495
Highly Influential Citations787
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A Real-Time QRS Detection Algorithm
TLDR
A real-time algorithm that reliably recognizes QRS complexes based upon digital analyses of slope, amplitude, and width of ECG signals and automatically adjusts thresholds and parameters periodically to adapt to such ECG changes as QRS morphology and heart rate.
View on IEEE
Quantitative Investigation of QRS Detection Rules Using the MIT/BIH Arrhythmia Database
TLDR
This work implemented and tested a final real-time QRS detection algorithm, using the optimized decision rule process, which has a sensitivity of 99.69 percent and positive predictivity of 98.77 percent when evaluated with the MIT/BIH arrhythmia database.
View on IEEE
A patient-adaptable ECG beat classifier using a mixture of experts approach
Presents a "mixture-of-experts" (MOE) approach to develop customized electrocardiogram (EGG) beat classifier in an effort to further improve the performance of ECG processing and to offer…
View on IEEE
ECG beat detection using filter banks
TLDR
A multirate digital signal processing algorithm to detect heartbeats in the electrocardiogram (ECG) which incorporates a filter bank which decomposes the ECG into subbands with uniform frequency bandwidths and inherently lends itself to a computationally efficient structure.
View on IEEE
Comparing Reconstruction Algorithms for Electrical Impedance Tomography
TLDR
An improved electrical impedance tomographic reconstruction algorithm is presented that is generally guaranteed to converge and provides significantly better reconstructions than any of the other methods.
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Biomedical Digital Signal Processing
A New Data-Reduction Algorithm for Real-Time ECG Analysis
TLDR
A new algorithm called CORTES is described here that is suited for real-time applications of ECG analysis and combines the best features of two other techniques called TP and AZTEC.
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Estimation of QRS Complex Power Spectra for Design of a QRS Filter
TLDR
The power spectral analysis shows that the QRS complex could be separated from other interfering signals, and it is observed that a bandpass filter with a center frequency of 17 Hz and a Q of 5 yields the best signal-to-noise ratio.
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Neural-network-based adaptive matched filtering for QRS detection
TLDR
The authors have developed an adaptive matched filtering algorithm based upon an artificial neural network (ANN) for QRS detection that is very effective at removing the time-varying, nonlinear noise characteristic of ECG signals.
View on IEEE
Biomedical Digital Signal Processing: C Language Examples and Laboratory Experiments for the IBM PC
Introduction to computers in medicine electrocardiography signal conversion basics of digital filtering finite impulse response filters infinite impulse response filters integers filters adaptive…
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