References

Customer Cases

Cardiolund has developed the ECG Parser with a particularly robust algorithm to overcome the challenges of dealing with simplified ECG recordings performed at home. In addition to providing standard ECG measurements, the Cardiolund algorithm parses each ECG recording in great detail to provide beat classification, rhythm analysis and markers of all important events.

With Cardiolund’s software our customers can position themselves in the lead of competing systems on the markets they enter. Here are highlights of our customer's systems and how they use Cardiolund's software.

Zenicor Medical Systems

Zenicor Medical Systems is a Swedish medtech company providing solutions for remote cardiology diagnostics and stroke prevention. The Zenicor’s thumb-ECG system has integrated the Cardiolund ECG Parser as a robust algorithm for detecting atrial fibrillation and other arrhythmias in ECG signals.

The Zenicor ECG system uses the ECG Parser to perform interval measurement, beat classification and rhythm analysis, as well as categorisation of recordings based on their contents.

Coala Life

Coala Life is a medtech company founded in Sweden that have developed a device for monitoring cardiac health. Their device is an event monitor that can perform both thumb ECG and chest ECG recordings, and it also records a phonocardiogram (PCG) along with the chest ECG.

The Coala Life system uses the Cardiolund ECG Parser for automated ECG analysis, they also employ a number of other custom signal analysis algorithms developed by Cardiolund.

Cortrium

Cortrium is a Danish medtech company that have developed a battery powered Holter Monitor for multiday 3-channel chest recordings.

The Cortrium Analysis System uses the Cardiolund ECG Parser and custom reporting software to provide pdf and online Holter reports.

The system provides standard Holter reporting with HRV statistics, diagnosis of arrhythmias, including atrial fibrillation & atrial flutter, ventricular fibrillation & ventricular flutter, ventricular events, supraventricular events, and pauses.

PulseOn

PulseOn is a Finnish medtech company that has developed the PulseOn Arrhythmia Monitor System. The system consists of a wrist-worn device and a data management service. The wrist device continuously measures patient’s heartbeats using PCG to analyze pulse rate for possible cardiac rhythm irregularities. If an episode of irregular rhythm is detected, the device notifies the patient to take a lead-I ECG recording using the same device.

The PulseOn Arrhythmia Monitor System employs Cardiolund ECG Parser for automated ECG analysis.


Scientific Leadership

Cardiolund is at the leading edge of scientific research in analysis of ECG signals from patients with atrial fibrillation (AF). The algorithms we provide have root in extensive research carried out by Cardiolund and our research partners.

Our methodology related to atrial fibrillation has been presented and applied in the following scientific journal papers:

Scientific References

Atrial fibrillation episode patterns as predictor of clinical outcome of catheter ablation
Saiz-Vivó J, Corino V, Martín-Yebra A, Mainardi L, Hatala R, Sörnmo L
Medical and Biological Engineering and Computing, Feb 2023. (DOI link)

Spectral Analysis of Heart Rate Variability in Time-Varying Conditions and in the Presence of Confounding Factors
Sörnmo L, Bailon R, Laguna P
IEEE Reviews in Biomedical Engineering p.1-21, Nov 2022. (DOI link)

QT interval Adaptation to Heart Rate Changes in Atrial Fibrillation as a Predictor of Sudden Cardiac Death
Martin-Yebra A, Sörnmo L, Laguna P
IEEE Transactions on Biomedical Engineering 69(10). p.3109-3118, Oct 2022. (DOI link)

A comparative study of the performance of methods for f-wave extraction
Mihandoost S, Sörnmo L, Doyen M, Oster J
Physiological Measurement 43(10). Oct 2022. (DOI link)

Training Convolutional Neural Networks on Simulated Photoplethysmography Data : Application to Bradycardia and Tachycardia Detection
Sološenko A, Paliakaitė B, Marozas V, Sörnmo L
Frontiers in Physiology 13, Jul 2022. (DOI link)

Considerations on Performance Evaluation of Atrial Fibrillation Detectors
Butkuviene M, Petrenas A, Solosenko A, Martin-Yebra A, Marozas V, Sörnmo L
IEEE Transactions on Biomedical Engineering 68(11) pp. 3250-3260, Nov 2021. (DOI link)

Modeling and estimation of temporal episode patterns in paroxysmal atrial fibrillation
Henriksson M, Martín-Yebra A, Butkuvienė M, Rasmussen J, Savelev A, Marozas V, Petrėnas A, Platonov P, Sörnmo L
IEEE Transactions on Biomedical Engineering, Vol. 68, pp. 319–329, 2021. (DOI link)

Considerations on performance evaluation of atrial fibrillation detectors
Butkuvienė M, Petrėnas A, Sološenko A, Martín-Yebra A, Marozas V, Sörnmo L
IEEE Transactions on Biomedical Engineering, Vol. 68, Issue 11, November 2021. (DOI link)

Identification of transient noise to reduce false detections in screening for atrial fibrillation
Halvaei H, Svennberg E, Sörnmo L, Stridh M
Frontiers in Physiology 2021 Jun 4, Vol. 12:672875. PMID: 34149452; PMCID: PMC8212862. (DOI link)

Short-term reproducibility of parameters characterizing atrial fibrillatory waves
M. Henriksson, A. García-Alberola, L. Sörnmo
Computers in Biology and Medicine 2020 Feb, Vol. 117:103613. Epub 2020 Jan 16. PMID: 32072968. (DOI link)

ECG-derived respiratory rate in atrial fibrillation
Kontaxis S, Lázaro J, Corino V, Sandberg F, Bailón R, Laguna P, Sörnmo L
IEEE Transactions on Biomedical Engineering, Vol. 67, pp. 905–914, 2020. (DOI link)

Short-term reproducibility of parameters characterizing atrial fibrillatory waves
Henriksson M, García-Alberola A, Sörnmo L
Computers in Biology and Medicine, Vol. 117, 103613, 2020. (DOI link)

ECG-derived Respiratory Rate in Atrial Fibrillation
S. Kontaxis, J. Lázaro, V.D.A. Corino, F. Sandberg, R. Bailón, P. Laguna, L. Sörnmo
IEEE Transactions on Biomedical Engineering, 2019. (DOI link)

Reference database and performance evaluation of methods for extraction of atrial fibrillatory waves in the ECG
R. Alcaraz, L. Sörnmo, J.J. Rieta
Physiological Measurement, Vol. 40, 075011, 2019. (DOI link)

Detection of atrial fibrillation using a wrist-worn device
A. Solosenko, A. Petrenas, B. Paliakaite, L. Sörnmo, V. Marozas
Physiological Measurement, Vol. 40, 025003, 2019. (DOI link)

Model-based assessment of f-wave signal quality in patients with atrial fibrillation
Henriksson M, Petrėnas A, Marozas V, Sandberg F, Sörnmo L
IEEE Transactions on Biomedical Engineering, Vol. 65, pp. 2600-2611, 2018. (DOI link)

Changes in f-wave characteristics during cryoballoon catheter ablation
M. Henriksson, A. García-Alberola, R. Goya, A. Vadillo, F. Melgarejo Meseguer, F. Sandberg, L. Sörnmo
Physiological Measurement, Vol. 39, pp. 105001, 2018. (DOI link)

Frequency tracking of atrial fibrillation in ambulatory electrocardiogram signals
B. Paliakaite, A. Petrenas, M. Henriksson, J. Skibarkiene, R. Kubilius, L. Sörnmo, V. Marozas
Computers in Biology and Medicine, Vol. 102, pp. 227–233, 2018. (DOI link)

Atrial Fibrillation from an Engineering Perspective
L. Sörnmo (editor)
Springer Nature, 316 pages book, 2018 (978-3-319-68513-7). (Springer link)

Model-based assessment of f-wave signal quality in patients with atrial fibrillation
Henriksson M, Petrenas A, Marozas V, Sandberg F, Stridh M, Sörnmo L
IEEE Transactions on Biomedical Engineering, 2018. (DOI link)

Modeling of the photoplethysmographic signal in atrial fibrillation
Solosenko A, Petrenas A, Marozas V, Sörnmo L
Computers in Biology and Medicine, Vol. 81, pp. 130–138, 2017. (DOI link)

Electrocardiogram modeling during paroxysmal atrial fibrillation: Application to the detection of occult episodes
Petrenas A, Marozas V, Solosenko A, Kubilius R, Skibarkiene J, Oster J, Sörnmo L
Physiological Measurement, Vol. 38, pp. 2058–2080, 2017.

A statistical atrioventricular node model accounting for pathway switching during atrial fibrillation
Henriksson M, Corino V, Sörnmo L, Sandberg F
IEEE Transactions on Biomedical Engineering, vol. 63, 1842–1849, 2016. (PubMed link)

Clinical use and limitations of non-invasive electrophysiological tests in patients with atrial fibrillation
Corino V, Mainardi L, Sandberg F, Sörnmo L, Platonov P
Invited paper, Journal of Atrial Fibrillation, vol. 9, pp. 62–67, 2016. (DOI link)

Detection of occult paroxysmal atrial fibrillation
Petrenas A, Sörnmo L, Lukoseviçius A, Marozas V
Medical and Biological Engineering & Computing, vol. 53, pp. 287–297, 2015. (PubMed link)

A modified Lewis ECG lead system for ambulatory monitoring of atrial arrhythmias
Petrenas A, Marozas V, Jaruševičius G, Sörnmo L
Journal of Electrocardiology, vol. 48, pp. 157–163, 2015. (PubMed link)

Ultra low-energy ASIC implementation of a real-time atrial fibrillation detector
Andersson O, Chon K, Sörnmo L, Neves Rodrigues J
IEEE Transactions on Biomedical Circuits and Systems, vol. 9, pp. 377–386, 2015.

Low complexity detection of atrial fibrillation in continuous ambulatory monitoring
Petrenas A, Marozas V, Sörnmo L
Computers in Biology and Medicine, vol. 65, pp. 184–191, 2015.

Non-invasive assessment of beta blockers and calcium channel blockers on the AV node during permanent atrial fibrillation
Sandberg F, Corino V, Mainardi L, Ulimoen S, Enger S, Tveit A, Platonov P, Sörnmo L
Journal of Electrocardiology, vol. 48, pp. 861–866, 2015. (PubMed link)

Novel noninvasive tools for characterizing atrioventricular nodal conduction in patients with atrial fibrillation
Corino V, Sandberg F, Mainardi L, Platonov P, Sörnmo L
Journal of Electrocardiology, vol. 48, pp. 938–942, 2015.

Noninvasive assessment of atrioventricular nodal function: Effect of rate-control drugs during atrial fibrillation
Corino V, Sandberg F, Mainardi L, Platonov P, Sörnmo L
Annals of Noninvasive Electrocardiology, vol. 20, pp. 534–541, 2015. (PubMed link)

Non-invasive evaluation of the effect of metoprolol on the atrioventricular node during permanent atrial fibrillation
Corino V, Sandberg F, Enger S, Mainardi L, Platonov P, Tveit A, Ulimoen S, Sörnmo L
Europace, vol. 16, iv129–iv134, 2014. (PubMed link)

Long term characterization of atrial fibrillation: wave morphology, frequency and irregularity
Goya-Esteban R, Sandberg F, Barquero-Pérez Ó, García-Alberola A, Sörnmo L, Rojo-Álvarez J
Medical and Biological Engineering & Computing, vol. 52, pp. 1053–1060, 2014. (PubMed link)

Rapid slowing of the atrial fibrillatory rate after administration of AZD7009 predicts conversion of atrial fibrillation.
Aunes M, Egstrup K, Frison L, Berggren A, Stridh M, Sörnmo L, Edvardsson N.
J Electrocardiol. 2014 May-Jun;47(3):316–23. doi:10.1016/j.jelectrocard.2013.12.008. Epub 2013 Dec 18. (PubMed link)

Atrial fibrillatory rate in the clinical context: natural course and prediction of intervention outcome
Platonov P, Corino V, Seifert M, Holmqvist F, Sörnmo L
Invited paper, Europace, vol. 16, iv110–iv119, 2014. (PubMed link)

Association between atrial fibrillatory rate and heart rate variability in patients with atrial fibrillation and congestive heart failure.
Corino VD, Cygankiewicz I, Mainardi LT, Stridh M, Vasquez R, Bayes de Luna A, Holmqvist F, Zareba W, Platonov PG.
Ann Noninvasive Electrocardiol. 2013 Jan;18(1):41–50. doi: 10.1111/anec.12019. Epub 2012 Nov 22. (PubMed link)

Non-invasive robust estimation of refractory period of atrioventricular node during atrial fibrillation
Corino V, Sandberg F, Mainardi L, Sörnmo L
International Journal of Bioelectromagnetism, vol. 15, pp. 41–46, 2013.

Atrioventricular nodal function during atrial fibrillation: Model building and robust estimation
Corino V, Sandberg F, Mainardi L, Sörnmo L
Biomedical Signal Processing and Control, vol. 8, pp. 1017–1025, 2013.

Atrial flutter and atrial tachycardia detection in ECG recordings using a particle filter and a high resolution time–frequency spectral approach
Lee J, McManus D, Bourell P, Sörnmo L, Chon K
Biomedical Signal Processing and Control, vol. 8, pp. 992–999, 2013.

Decrease of the atrial fibrillatory rate, increased organization of the atrial rhythm and termination of atrial fibrillation by AZD7009.
Aunes-Jansson M, Edvardsson N, Stridh M, Sörnmo L, Frison L, Berggren A.
J Electrocardiol. 2013 Jan-Feb;46(1):29–35. doi:10.1016/j.jelectrocard.2012.09.002. Epub 2012 Dec 6. (PubMed link)

Effects of dronedarone and amiodarone on atrial fibrillatory rate in patients with persistent atrial fibrillation.
John S, Salmas J, Kornej J, Löbe S, Stridh M, Sörnmo L, Hindricks G, Husser D, Bollmann A.
Int J Cardiol. 2013 Sep 1;167(5):2354–6. doi: 10.1016/j.ijcard.2012.11.042. Epub 2012 Nov 23. (PubMed link)

Analysis of atrial fibrillatory rate during spontaneous episodes of atrial fibrillation in humans using implantable loop recorder electrocardiogram.
Platonov PG, Stridh M, de Melis M, Urban L, Carlson J, Corbucci G, Holmqvist F.
J Electrocardiol. 2012 Nov-Dec;45(6):723–6. doi:10.1016/j.jelectrocard.2012.05.003. Epub 2012 Jun 12. (PubMed link)

Low atrial fibrillatory rate is associated with poor outcome in patients with mild to moderate heart failure.
Platonov PG, Cygankiewicz I, Stridh M, Holmqvist F, Vazquez R, Bayes-Genis A, McNitt S, Zareba W, de Luna AB; MUSIC Trial Investigators.
Circ Arrhythm Electrophysiol. 2012 Feb;5(1):77–83. doi:10.1161/CIRCEP.111.964395. Epub 2012 Jan 10. (PubMed link)

Propagation pattern analysis during atrial fibrillation based on sparse modeling
Richter U, Faes L, Ravelli F, Sörnmo L
IEEE Transactions on Biomedical Engineering, vol. 59, pp. 1319–1328, 2012. (PubMed link)

An echo state neural network for QRST cancellation during atrial fibrillation
Petrenas A, Marozas V, Sörnmo L, Lukoseviçius A
IEEE Transactions on Biomedical Engineering, vol. 59, pp. 2950–2957, 2012. (PubMed link)

Left atrial appendage activity translation in the standard 12-lead ECG.
Platonov PG, Nault I, Holmqvist F, Stridh M, Hocini M, Haïssaguerre M.
J Cardiovasc Electrophysiol. 2011 Jun;22(6):706–10. doi:10.1111/j.1540–8167.2010.01909.x. Epub 2010 Oct 6. (PubMed link)

Förmakens fibrilleringsfrekvens möjligt prognosstöd vid förmaksflimmer.
Olsson SB, Platonov P, Holmqvist F, Bollmann A.
Läkartidningen 2010;107:1839-1843.

A novel approach to propagation pattern analysis in intracardiac atrial fibrillation signals.
Richter U, Faes L, Cristoforetti A, Masè M, Ravelli F, Stridh M, Sörnmo L.
Ann Biomed Eng. 2011 Jan;39(1):310–23. doi: 10.1007/s10439–010–0146–8. Epub 2010 Aug 28. (PubMed link)

Classification of paroxysmal and persistent atrial fibrillation in ambulatory ECG recordings
Alcaráz R, Sandberg F, Sörnmo L, Rieta J
IEEE Transactions on Biomedical Engineering, vol. 58, pp. 1441–1449, 2011. (PubMed link)

An atrioventricular node model for analysis of the ventricular response during atrial fibrillation
Corino V, Sandberg F, Mainardi L, Sörnmo L
IEEE Transactions on Biomedical Engineering, vol. 58, pp. 3386–3395, 2011. (PubMed link)

Letter by Platonov et Al regarding article, Dominant frequency of atrial fibrillation correlates poorly with atrial fibrillation cycle length
Platonov PG, Stridh M, Sörnmo L.
Circ Arrhythm Electrophysiol. 2010 Apr;3(2):e4; author reply e5. doi:10.1161/CIRCEP.110.943274. (PubMed link)

Circadian variation in dominant atrial fibrillation frequency in persistent atrial fibrillation.
Sandberg F, Bollmann A, Husser D, Stridh M, Sörnmo L.
Physiol Meas. 2010 Apr;31(4):531–42. doi: 10.1088/0967–3334/31/4/005. Epub 2010 Mar 5. (PubMed link)

Analysis of changes in the beat-to-beat P-wave morphology using clustering techniques.
Herreros A, Baeyens E, Johansson R, Carlson J, Perán JR, Olsson B.
Biomedical Signal Processing and Control 2009;4:309-316.

Right atrial organization and wavefront analysis in atrial fibrillation.
Richter U, Bollmann A, Husser D, Stridh M.
Med Biol Eng Comput. 2009 Dec;47(12):1237–46. doi: 10.1007/s11517–009–0540–2. Epub 2009 Oct 15. (PubMed link)

A genotype-dependent intermediate ECG phenotype in patients with persistent lone atrial fibrillation genotype ECG-phenotype correlation in atrial fibrillation.
Husser D, Stridh M, Sörnmo L, Roden DM, Darbar D, Bollmann A.
Circ Arrhythm Electrophysiol. 2009 Feb;2(1):24–8. doi:10.1161/CIRCEP.108.799098. (PubMed link)

Atrial fibrillatory rate and risk of stroke in atrial fibrillation.
Bollmann A, Husser D, Lindgren A, Stridh M, Härdig BM, Piorkowski C, Arya A, Sörnmo L, Olsson SB.
Europace. 2009 May;11(5):582–6. doi: 10.1093/europace/eup062. Epub 2009 Mar 14. (PubMed link)

Relation between atrial fibrillatory rate and markers of inflammation and haemostasis in persistent human atrial fibrillation.
Tveit A, Bollmann A, Seljeflot I, Husser D, Stridh M, Sörnmo L, Arnesen H, Olsson SB, Smith P.
Thromb Haemost. 2009 Mar;101(3):601–3. (PubMed link)

Waveform characterization of atrial fibrillation using phase information.
Stridh M, Husser D, Bollmann A, Sörnmo L.
IEEE Trans Biomed Eng. 2009 Apr;56(4):1081–9. doi: 10.1109/TBME.2008.2006624. Epub 2008 Oct 31. (PubMed link)

Spectral validation improves frequency tracking obtained by time-frequency analysis during atrial fibrillation.
Corino VD, Mainardi LT, Stridh M, Sornmo L.
Conf Proc IEEE Eng Med Biol Soc. 2008;2008:5733–6. doi:10.1109/IEMBS.2008.4650516. (PubMed link)

Improved time–frequency analysis of atrial fibrillation signals using spectral modeling.
Corino VD, Mainardi LT, Stridh M, Sörnmo L.
IEEE Trans Biomed Eng. 2008 Dec;55(12):2723–30. doi:10.1109/TBME.2008.2002158. (PubMed link)

Analysis of atrial fibrillation: from electrocardiogram signal processing to clinical management.
Sörnmo L, Stridh M, Husser D, Bollmann A, Olsson SB.
Philos Trans A Math Phys Eng Sci. 2009 Jan 28;367(1887):235–53. doi:10.1098/rsta.2008.0162. Review. (PubMed link)

Fibrillatory rate response to candesartan in persistent atrial fibrillation.
Bollmann A, Tveit A, Husser D, Stridh M, Sörnmo L, Smith P, Olsson SB.
Europace. 2008 Oct;10(10):1138–44. doi: 10.1093/europace/eun195. Epub 2008 Jul 28. (PubMed link)

Spatial characteristics of atrial fibrillation electrocardiograms.
Richter U, Stridh M, Bollmann A, Husser D, Sörnmo L.
J Electrocardiol. 2008 Mar-Apr;41(2):165–72. doi: 10.1016/j.jelectrocard.2007.10.006. (PubMed link)

Frequency tracking of atrial fibrillation using hidden Markov models.
Sandberg F, Stridh M, Sörnmo L.
IEEE Trans Biomed Eng. 2008 Feb;55(2 Pt 1):502–11. doi:10.1109/TBME.2007.905488. (PubMed link)

A Gaussian mixture model for time-frequency analysis of atrial fibrillation electrocardiograms.
Corino VD, Mainardi LT, Bollmann A, Husser D, Stridh M, Sörmno L.
Conf Proc IEEE Eng Med Biol Soc. 2007;2007:271–4. (PubMed link)

Atrial fibrillatory rate and risk of left atrial thrombus in atrial fibrillation.
Bollmann A, Husser D, Stridh M, Holmqvist F, Roijer A, Meurling CJ, Sörnmo L, Olsson SB.
Europace. 2007 Aug;9(8):621–6. Epub 2007 Jun 29. (PubMed link)

Exercise testing for non-invasive assessment of atrial electrophysiological properties in patients with persistent atrial fibrillation.
Husser O, Husser D, Stridh M, Sörnmo L, Corino VD, Mainardi LT, Lombardi F, Klein HU, Olsson SB, Bollmann A.
Europace. 2007 Aug;9(8):627–32. Epub 2007 Jun 26. (PubMed link)

Electrocardiographic characteristics of fibrillatory waves in new-onset atrial fibrillation.
Husser D, Cannom DS, Bhandari AK, Stridh M, Sörnmo L, Olsson SB, Bollmann A.
Europace. 2007 Aug;9(8):638–42. Epub 2007 Apr 30. (PubMed link)

Transthoracic tissue Doppler imaging of the atria to determine atrial fibrillation cycle length.
Bollmann A, Husser D, Stridh M, Sörnmo L.
J Cardiovasc Electrophysiol. 2007 Mar;18(3):E13–4. Epub 2007 Jan 30. (PubMed link)

Validation and clinical application of time-frequency analysis of atrial fibrillation electrocardiograms.
Husser D, Stridh M, Cannom DS, Bhandari AK, Girsky MJ, Kang S, Sörnmo L, Bertil Olsson S, Bollmann A.
J Cardiovasc Electrophysiol. 2007 Jan;18(1):41–6. (PubMed link)

Detection and feature extraction of atrial tachyarrhythmias. A three stage method of time-frequency analysis.
Stridh M, Bollmann A, Olsson SB, Sörnmo L.
IEEE Eng Med Biol Mag. 2006 Nov-Dec;25(6):31–9. Review. (PubMed link)

Analysis of surface electrocardiograms in atrial fibrillation: techniques, research, and clinical applications.
Bollmann A, Husser D, Mainardi L, Lombardi F, Langley P, Murray A, Rieta JJ, Millet J, Olsson SB, Stridh M, Sörnmo L.
Europace. 2006 Nov;8(11):911–26. Review. (PubMed link)

Electroatriography - time-frequency analysis of atrial fibrillation from modified 12-lead ECG configurations for improved diagnosis and therapy.
Husser D, Stridh M, Sörnmo L, Toepffer I, Klein HU, Bertil Olsson S, Bollmann A.
Med Hypotheses. 2007;68(3):568–73. Epub 2006 Oct 9. (PubMed link)

Atrial fibrillatory rate and sinus rhythm maintenance in patients undergoing cardioversion of persistent atrial fibrillation.
Holmqvist F, Stridh M, Waktare JE, Sörnmo L, Olsson SB, Meurling CJ.
Eur Heart J. 2006 Sep;27(18):2201–7. Epub 2006 Sep 6. (PubMed link)

Frequency analysis of atrial fibrillation from the surface electrocardiogram.
Husser D, Stridh M, Sornmo L, Olsson SB, Bollmann A.
Indian Pacing Electrophysiol J. 2004 Jul 1;4(3):122–36. (PubMed link)

Atrial fibrillation signal organization predicts sinus rhythm maintenance in patients undergoing cardioversion of atrial fibrillation.
Holmqvist F, Stridh M, Waktare JE, Roijer A, Sörnmo L, Platonov PG, Meurling CJ.
Europace. 2006 Aug;8(8):559–65. Epub 2006 Jul 10. (PubMed link)

Indices of electrical and contractile remodeling during atrial fibrillation in man.
Holmqvist F, Stridh M, Waktare JE, Sörnmo L, Roijer A, Meurling CJ.
Pacing Clin Electrophysiol. 2006 May;29(5):512–9. (PubMed link)

Prediction of sinus rhythm maintenance following DC-cardioversion of persistent atrial fibrillation - the role of atrial cycle length.
Meurling CJ, Roijer A, Waktare JE, Holmqvist F, Lindholm CJ, Ingemansson MP, Carlson J, Stridh M, Sörnmo L, Olsson SB.
BMC Cardiovasc Disord. 2006 Mar 13;6:11. (PubMed link)

Comparison of atrial signal extraction algorithms in 12-lead ECGs with atrial fibrillation.
Langley P, Rieta JJ, Stridh M, Millet J, Sörnmo L, Murray A.
IEEE Trans Biomed Eng. 2006 Feb;53(2):343–6. (PubMed link)

Predicting spontaneous termination of atrial fibrillation using the surface ECG.
Nilsson F, Stridh M, Bollmann A, Sörnmo L.
Med Eng Phys. 2006 Oct;28(8):802–8. Epub 2006 Jan 25. (PubMed link)

Rapid fluctuations in atrial fibrillatory electrophysiology detected during controlled respiration.
Holmqvist F, Stridh M, Waktare JE, Brandt J, Sörnmo L, Roijer A, Meurling CJ.
Am J Physiol Heart Circ Physiol. 2005 Aug;289(2):H754–60. (PubMed link)

Pilot study: Noninvasive monitoring of oral flecainide’s effects on atrial electrophysiology during persistent human atrial fibrillation using the surface electrocardiogram.
Husser D, Binias KH, Stridh M, Sornmo L, Olsson SB, Molling J, Geller C, Klein HU, Bollmann A.
Ann Noninvasive Electrocardiol. 2005 Apr;10(2):206–10. (PubMed link)

Analysis of the surface electrocardiogram for monitoring and predicting antiarrhythmic drug effects in atrial fibrillation.
Husser D, Stridh M, Sornmo L, Platonov P, Olsson SB, Bollmann A.
Cardiovasc Drugs Ther. 2004 Sep;18(5):377–86. Review. (PubMed link)

Time-frequency analysis of the surface electrocardiogram for monitoring antiarrhythmic drug effects in atrial fibrillation.
Husser D, Stridh M, Sornmo L, Geller C, Klein HU, Olsson SB, Bollmann A.
Am J Cardiol. 2005 Feb 15;95(4):526–8. (PubMed link)

Determinants and prognostic significance of immediate atrial fibrillation recurrence following cardioversion in patients undergoing pulmonary vein isolation.
Husser D, Bollmann A, Kang S, Stridh M, Sornmo L, Olsson SB, Bhandari AK, Cannom DS.
Pacing Clin Electrophysiol. 2005 Feb;28(2):119–25. (PubMed link)

Echocardiographic and electrocardiographic predictors for atrial fibrillation recurrence following cardioversion.
Bollmann A, Husser D, Steinert R, Stridh M, Soernmo L, Olsson SB, Polywka D, Molling J, Geller C, Klein HU.
J Cardiovasc Electrophysiol. 2003 Oct;14(10 Suppl):S162–5. (PubMed link)

Frequency measures obtained from the surface electrocardiogram in atrial fibrillation research and clinical decision-making.
Bollmann A, Husser D, Stridh M, Soernmo L, Majic M, Klein HU, Olsson SB.
J Cardiovasc Electrophysiol. 2003 Oct;14(10 Suppl):S154–61. (PubMed link)

Sequential characterization of atrial tachyarrhythmias based on ECG time-frequency analysis.
Stridh M, Sörnmo L, Meurling CJ, Olsson SB.
IEEE Trans Biomed Eng. 2004 Jan;51(1):100–14. (PubMed link)

Detection of autonomic modulation in permanent atrial fibrillation.
Stridh M, Meurling C, Olsson B, Sörnmo L.
Med Biol Eng Comput. 2003 Nov;41(6):625–9. (PubMed link)

Non-invasive assessment of atrial fibrillation (AF) cycle length in man: potential application for studying AF.
Meurling CJ, Sörnmo L, Stridh M, Olsson SB.
Ann Ist Super Sanita. 2001;37(3):341–9. Review. (PubMed link)

Characterization of atrial fibrillation using the surface ECG: time-dependent spectral properties.
Stridh M, Sörnmo L, Meurling CJ, Olsson SB.
IEEE Trans Biomed Eng. 2001 Jan;48(1):19–27. (PubMed link)

Spatiotemporal QRST cancellation techniques for analysis of atrial fibrillation.
Stridh M, Sörnmo L.
IEEE Trans Biomed Eng. 2001 Jan;48(1):105–11. (PubMed link)

Attenuation of electrical remodelling in chronic atrial fibrillation following oral treatment with verapamil.
Meurling CJ, Ingemansson MP, Roijer A, Carlson J, Lindholm CJ, Smideberg B, Sornmo L, Stridh M, Olsson SB.
Europace. 1999 Oct;1(4):234–41. (PubMed link)