Mohamed Elgendi

PhD Biomedical Engineering

Journal Publications

 

  1. M. Elgendi, P. Bobhate, S. Jain, L. Guo, J. Rutledge, Y. Coe, R. Zemp, D. Schuurmans, I. Adatia, "The Voice of the Heart: Vowel-Like Sound in Pulmonary Artery Hypertension," Diseases 6 (2) 26, 2018.
  2. Y. Liang, Z. Chen, G. Liu,  M. Elgendi, "An optimal filter for short photoplethysmogram signals," Nature Scientific Data  accepted March 27th, 2018. 
  3. R. Hussein, M. Elgendi, Z.J. Wang, R. Ward, "Robust Detection of Epileptic Seizures Based on L1-Penalized Robust Regression of EEG Signals," Expert Systems with Applications, 104 , 153-167, 2018. 
  4.  M. Elgendi, Y. Liang, R. Ward, "Toward Generating More Diagnostic Features from Photoplethysmogram Waveforms," Diseases 6 (1) 20 , 2018.
  5.  M. Elgendi, "Less Is More in Biosignal Analysis: Compressed Data Could Open the Door to Faster and Better Diagnosis," Diseases 6 (1) 18 , 2018.
  6.  Y. Liang, Z. Chen, G. Liu,  M. Elgendi, "A new, short-recorded photoplethysmogram dataset for blood pressure monitoring in China," Nature Scientific Data  (5), 180020.
  7. M. Elgendi, A. Al-Ali, A. Mohamed, & R. Ward, "Improving Remote Health Monitoring: A low-complexity ECG Compression Approach," Diagnostics 8 (1) 10, 2018.
  8. M. Elgendi, "Merging Digital Medicine and Economics: Two Moving Averages Unlock Biosignals for Better Health," Diseases 6 (1) 6 , 2018.
  9. M. Elgendi, "Scientists Need Data Visualization Training," Nature Biotechnology 35 (10):990-991, 2017. 
  10. M. Elgendi, A. Mohamed, R. Ward," Efficient ECG Compression and QRS Detection for E-Health Applications," Scientific Reports 7: 459, 2017. 
  11. L. Guo, P. Bobhate, S. Kumar, K. Vadlamudi, T. Kaddoura, M. Elgendi, P. Holinski, Y. Coe, J. Rutledge, I. Adatia, "Hyperoxia Reduces Oxygen Consumption in Children with Pulmonary Hypertension," Pediatric Cardiology 1-6, 2017. 
  12. M. Elgendi, "TERMA Framework for Biomedical Signal Analysis: An Economic-Inspired Approach," Biosensors 6(4): 55, 2016
  13. M. Elgendi, Newton Howard, Nigel H. Lovell, Andrzej Cichocki, Matt Brearley, Derek Abbott,  Ian Adatia, "A Six-Step Framework on Biomedical Signal Analysis for Tackling Noncommunicable Diseases: Current and Future Perspectives" JMIR Biomedical Engineering 1(1):e1, 2016.
  14. M. Elgendi, M. Meo, D. Abbott, "A Proof-of-Concept Study: Simple and Effective Detection of P and T Waves in Arrhythmic ECG Signals," Bioengineering 3(4): 26, 2016.
  15. M. Elgendi, I. Norton, M. Brearley, D. Abbott, D. Schuurmans, "A pilot study: Can heart rate variability (HRV) be determined using short-term photoplethysmograms?" F1000Research 5:2354, 2016.
  16. M. Elgendi, "Optimal Signal Quality Index for Photoplethysmogram Signals," Bioengineering 3(4): 21, 2016.
  17. M. Elgendi, "Eventogram: A Visual Representation of Main Events in Biomedical Signals," Bioengineering 3(4): 22, 2016.
  18. T. Kaddoura, K. Vadlamudi, S. Kumar, P. Bobhate, L. Guo, S. Jain, M. Elgendi, J. Coe, D. Kim, D. Taylor, W. Tymchak, D. Schuurmans, R. Zemp, I. Adatia, "Acoustic diagnosis of pulmonary hypertension: automated speech-recognition-inspired classification algorithm outperforms physicians," Scientific Reports 2016. 
  19. L. Guo, P. Bobhate, Y. Cui, S. Kumar, S. Jain,  M. Elgendi,  S. Pharis, L. Ryerson, I. Adatia, "Measurement of Oxygen Consumption to Determine Cardiac Output in Critically Ill Children: a Comparison Between the Breath-by Breath-Method and Respiratory Mass Spectrometry," American Journal of Critical Care 25(3):243-248, 2016.
  20. P. Kumar, F. Mahmood, D. Menoth, K. Wong, A. Agrawal, K. Wong, M. Elgendi, R. Shukla, J. Dauwels, and A. Chan, "Effect of Subliminal Lexical Priming on the Subjective Perception of Images: a Machine Learning Approach," PLoS ONE  11(2): e0148332, 2016. 
  21. M. Elgendi, P. Bobhate, S. Jain, L. Guo, J. Rutledge, Y. Coe, R. Zemp, D. Schuurmans, I. Adatia, "Detection of Heart Sounds in Children With and Without Pulmonary Arterial Hypertension―Daubechies Wavelets Approach," PLoS ONE 10(12): e0143146, 2015.
  22. M. Elgendi, P. Bobhate, S. Jain, L. Guo, J. Rutledge, Y. Coe, R. Zemp, D. Schuurmans, I. Adatia, "The unique heart sound signature of children with pulmonary artery hypertension," Pulmonary Circulation 5(4): 631-639, 2015. 
  23. M. Elgendi, I. Norton, M. Brearley, R. Fletcher, D. Abbott, N. Lovell, D. Schuurmans, " Towards Investigating Global Warming Impact on Human Health Using Derivatives of Photoplethysmogram Signals," Int. J. Environ. Res. Public Health 12(10): 12776-12791, 2015.
  24. M. Elgendi, R. Fletcher, I. Norton, M. Brearley, D. Abbott, N. Lovell, D. Schuurmans, "Frequency analysis of photoplethysmogram and its derivatives," Computer Methods and Programs in Biomedicine 122(3): 503-512, 2015.
  25. M. Elgendi, R. Fletcher, I. Norton, M. Brearley, D. Abbott, N. Lovell, D. Schuurmans, "On time-domain analysis of photoplethysmogram signals for monitoring heat stress," Sensors 15(10): 24716-24734, 2015.
  26. M. Elgendi, B. Eskofier, D. Abbott, "Fast T wave detection calibrated by clinical knowledge with annotation of P and T waves," Sensors 15(7):17693–17714, 2015.
  27. E. Gallego-Jutgla, J. Sole-Casals, F. Vialatte, M. Elgendi, A. Cichocki, and J. Dauwels, "A hybrid feature selection approach for the early diagnosis of Alzheimer’s disease," Journal of Neural Engineering, 12(1): 016018, 2015. 
  28. M. Elgendi, I. Norton, M. Brearley, D. Abbott, D. Schuurmans, "Detection of a and b waves in the acceleration photoplethysmogram," Biomedical Engineering OnLine 13:139, 2014. 
  29. M. Elgendi, "Detection of c, d, and e waves in the acceleration photoplethysmogram," Computer Methods and Programs in Biomedicine 117(2): 125–136, 2014 
  30. M. Elgendi, P. Bobhate, S. Jain, L. Guo, J. Rutledge, Y. Coe, R. Zemp, D. Schuurmans, I. Adatia, "Time-domain analysis of heart sound intensity in children with and without pulmonary artery hypertension: a pilot study using a digital stethoscope," Pulmonary Circulation, 4(4): 685-695, 2014.
  31. M. Elgendi, F. Picon, N. Magnenat-Thalmann, D. Abbott, "Arm movement speed assessment via Kinect camera: A preliminary study in healthy subjects," Biomedical Engineering OnLine 13:88, 2014. 
  32. M. Elgendi, P. Bobhate, S. Jain, L. Guo, J. Rutledge, Y. Coe, R. Zemp, D. Schuurmans, I. Adatia, "Spectral analysis of the heart sounds in children with and without pulmonary artery hypertension," International Journal of Cardiology 173(1): 92–99, 2014. 
  33. M. Elgendi, B. Eskofier, S. Dokos, D. Abbott, "Revisiting QRS detection methodologies for portable, wearable, battery-operated, and wireless ECG systems," PLoS ONE  9(1): e84018, 2014. 
  34. M. Elgendi, I. Norton, M. Brearley, D. Abbott, D. Schuurmans, "Systolic Peak Detection in Acceleration Photoplethysmograms Measured from Emergency Responders in Tropical Conditions," PLoS ONE 8(10): e76585, 2013. 
  35. M. Elgendi, "Fast QRS detection with an optimized knowledge-based method: evaluation on 11 standard ECG databases," PLoS ONE 8(9): e73557, 2013. 
  36. G. Guo and M. Elgendi, "A New Recommender System for 3D E-Commerce: An EEG Based Approach," Journal of Advanced Management Science 1(1), 2013.
  37. M. Elgendi, "Standard Terminologies for Photoplethysmogram Signals," Current Cardiology Reviews 8(3), 2012. 
  38. M. Elgendi, "On the Analysis of Fingertip Photoplethysmogram Signals," Current Cardiology Reviews 8(1), 2012.
  39. M. Elgendi, M. Jonkman, and F. De Boer, "Improved QRS detection algorithm using dynamic thresholds," International Journal of Hybrid Information Technology 2(1), 2009.

 

Book Chapters

  1. M. Elgendi, J. Dauwels, B. Rebsamen, R. Shukla, Y. Putra, J. Gamez, N. ZePing, B. Ho, N. Prasad, A. Nair, V. Mishuhina, F. Vialatte, M. Constable, A. Cichocki, C. Latchoumane, J. Jeong, D. Thalmann,and N. Magnenat-Thalmann; “From Auditory and Visual to Immersive Neurofeedback: Application to Diagnosis of Alzheimer’s Disease”; Neural computation, neurodevices, and neural prosthesis, 2014, pp 63-97 [PDF
  2. M. Elgendi, B. Rebsamen, A. Cichocki, F. Vialatte, and J. Dauwels, “Real-Time Wireless Sonification of Brain Signals”, Advances in Cognitive Neurodynamics (III), 2013, pp 175-181 [PDF]
  3. S. Sarda, M. Constable, J. Dauwels, S. Dauwels, M. Elgendi, Z. Mengyu, U. Rasheed, Y. Tahir, D. Thalmann and N. Thalmann:"Real-Time Feedback System for Monitoring and Facilitating Discussions" , Natural Interaction with Robots, Knowbots and smartphones-Putting Spoken Dialog Systems into Practice, Lecture Notes in Computer Science 2013, Springer [PDF]
  4.  M. Elgendi, M. Jonkman, and F. De Boer, “Heart Rate Variability and Acceleration Plethysmogram measured at rest”; Communications in Computer and Information Science, Lecture Notes, Springer (invited: 02-04-10) [PDF]

Conference Papers

  1.  R. Hussein, M. Elgendi, R. Ward, A. Mohamed, "Computationally Efficient EEG Feature Learning for Early Detection of Epileptic Seizure," Proc. the fifth IEEE Global Conference on Signal and Information Processing, Montreal, Quebec, Canada on November 14-16, 2017.
  2. S. Gradl, H. Leutheuser, M. Elgendi, N. Lang, and B. Eskofier, " Temporal correction of detected R-peaks in ECG signals: A crucial step to improve R-peak detection algorithms," Proc. 37th  Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Milano, Italy; 25–29 Aug 2015. 
  3. M. Elgendi, Preliminary study for localizing c, d, and e waves in photoplethysmogram signals, Proc. 36th  Annual International Conference of the IEEE Engineering in Medicine and Biology Society, accepted on the 3rd June 2014.
  4. P. Kumar, F. Mahmood, D. Menoth, K. Wong, A. Agrawal, K. Wong, M. Elgendi, R. Shukla, J. Dauwels, and A. Chan, On the effect of subliminal priming on subjective perception of images: a machine learning approach, Proc. 36th  Annual International Conference of the IEEE Engineering in Medicine and Biology Society, accepted on the 3rd June 2014. 
  5. J. Dauwels, P. Kumar, F. Mahmood, K. Wong, A. Agrawal, M. Elgendi, S. Kannan, D. Menoth, R. Shukla, J. Dauwels, and A. Chan, A study on the effect of subliminal priming on subjective perception of images: a machine learning approach, ICBME2013, accepted. 
  6. P. Kumar, F. Mahmood, K. Wong, M. Elgendi, A. Agrawal, S. Kannan, D. Menoth, R. Shukla, J. Dauwels, and A. Chan, Inferring subliminal primes from EEG through machine learning, EMBC2013, accepted. 
  7. S. Sarda, M. Constable, J. Dauwels, S. Dauwels (Okutsu), M. Elgendi, Z. Mengyu, U. Rasheed, Y. Tahir, D. Thalmann, Nadia Magnenat-Thalmann, “Real-Time Feedback System for Monitoring and Facilitating Discussions”, IWSDS'2012 Workshop on Spoken Dialog Systems, Paris, France; 28-30 Nov 2012 [PDF]
  8. E. Gallego-Jutgla, M. Elgendi, F. Vialatte, J. Sole-Casals, A. Cichocki, C. Latchoumane, J. Jeong, and J. Dauwels, “Diagnosis of Alzheimer’s Disease from EEG by Means of Synchrony Measures in Optimized Frequency Bands”, EMBC2012, San Diego, USA; 28th Aug-3rd Sep 2012 [PDF
  9. M. Elgendi, F. Picon, and N. Magenant-Thalmann, “Real-Time Speed Detection of Hand Gesture using Kinect”, Workshop on Autonomous Social Robots and Virtual Humans", the 25th Annual Conference on Computer Animation and Social Agents (CASA 2012), Singapore; 09-11 May 2012
  10. M. Elgendi, F. Vialatte, M. Constable Vialatte, and J. Dauwels, “Immersive Neurofeedback: A New Paradigm”, NCTA2011, Paris; 24-26 Oct 2011 [PDF]
  11. M. Elgendi, F. Vialatte, A. Cichocki, C. Latchoumane, J. Jeong, and J. Dauwels, “Optimization of EEG Frequency Bands for Improved Diagnosis of Alzaheimer Disease”, EMBC2011, Boston; 30Aug-3rdSep 2011 [PDF]
  12. M. Elgendi, M. Jonkman, and F. De Boer, “Applying the APG to measure Heart Rate Variability” Proceedings IEEE ICCAE, Computer and Automation Engineering, Singapore, pp.100-103, 26-28 Feb 2010
  13. M. Elgendi, M. Jonkman, and F. De Boer, “Frequency Bands Effects on QRS Detection” Proceedings Springer-Verlag, Biomedical Engineering Systems and Technologies, Spain; pp.428-431, 20-23 Jan 2010  [PDF] 
  14. M. Elgendi, M. Jonkman, and F. De Boer, “Heart Rate Variability Measurement Using the Second Derivative Photoplethysmogram” Proceedings Springer-Verlag, Biomedical Engineering Systems and Technologies, Spain; pp. 82-85, 20-23 Jan 2010.
  15. M. Elgendi, M. Jonkman, and F. De Boer, “Measurement of a-a Intervals at Rest in the Second Derivative Plethysmogram” Proceedings IEEE, Bioelectronics and Bioinformatics, RMIT University, pp.75-79, 9-11 Dec 2009 [PDF]
  16. M. Elgendi, M. Jonkman, and F. De Boer, “Recognition of T Waves in ECG signals” Proceedings IEEE NEBEC, Massachusetts Institute of Technology, pp.10-14, 3-5 April 2009 [PDF]
  17. M. Elgendi, M. Jonkman, and F. De Boer, “R Wave Detection using Coiflets Wavelets” Proceedings IEEE NEBEC, Massachusetts Institute of Technology, pp.1-4, 3-5 April 2009. [PDF]
  18. M. Elgendi, M. Jonkman, and F. De Boer, “P Wave Demarcation in Electrocardiogram” Proceedings IEEE NEBEC, Massachusetts Institute of Technology, pp.5-9, 3-5 April 2009 [PDF]
  19. M. Elgendi, M. Jonkman, and F. De Boer, “A Robust QRS Complex Detection Algorithm using Dynamic Thresholds” Proceedings IEEE CSA, Computer Science and its Applications, Tasmania University, pp.153-158, 13-15 Oct 2008 [PDF]
  20. M. Elgendi, M. Jonkman, and F. De Boer, “Premature Atrial Complexes Detection using the Fisher Linear Discriminant” Proceedings IEEE ICCI, Cognitive Informatics, Stanford University, pp.83-88, 14-16 Aug 2008 [PDF]
  21. M. Elgendi, M. Jonkman, and F. De Boer, “Classification of the Feature Vectors of ECG Signals” Proceedings ICICT, American University in Cairo, pp.228-231, 8-12 Dec 2006 [PDF]
  22. M. Elgendi, M. Elaadawy, H. Kishk, “Automatic Iris Recognition using Neural Networks and Wavelet” Proceedings SPIE, Vol. 5616, p.p. 69-76, 2004 [PDF]