Education

Radiology Imaging Fellowship
Johns Hopkins University School of Medicine, Department of Radiology, Baltimore, MD 2009-2010
Biomedical Eng. Fellowship
Johns Hopkins University, Department of Biomedical Engineering, Baltimore, MD 2008-2009
Biomedical Eng. Fellowship
Drexel University, Department of Biomedical Engineering, Philadelphia, PA 2007-2008
PhD Degree (ECE)
Tampere University of Technology, Tampere, Finland 2004-2007
M.S. Degree (BME)
Iran University of Science and Technology, Tehran, Iran 1999-2002

Areas of Interest

Clinical Interests

My current clinical interests include developing novel system and methods using advanced signal/image processing, machine learning and radiological methods for the diagnosis, prognosis and treatment effectiveness monitoring of many diseases. I have been trained in medical imaging, computer science, and engineering.

Research Interests

Research Activities

Research Focus
I have over 22 years of experience in both academic and industrial settings. I have focused on various aspects of medical imaging and spectroscopy (Ultrasound, MRI, PET/CT, Optical), biosensing and wearables (ECG, EEG, EMG, BCG, Pulse Ox), algorithm development using machine learning and AI, computer vision, signal and image processing methods for many different industrial and medical applications. I have BSc and MSc degrees in electrical and biomedical engineering and a PhD in AI for biomedical applications. I also completed two different fellowships in biomedical engineering and radiology. I have worked as Tenure -Track Faculty at Johns Hopkins University School of Medicine and visiting faculty at Stanford School of Medicine, and with several other adjunct faculty appointments in ECE and BME in the past. I have directed, as PI and Co-Investigator, on numerous research projects funded by federal grants and have extensively published over 90 proceedings and journal papers. I have also patented several systems and methods for industrial and medical applications. I have also served as editor and reviewer for several peer-reviewed journals and conferences.

Inventions, Patents, Copyrights (pending, awarded)

  • Nov 16, 2021 US Patent 20190293620 Vasefi F., Farkas D.L., Akhbardeh A., Kang L., Stanislov Sokolov S. Apparatus and method for multimode analytical sensing of items such as food, filed on Mar . 19, 2019, granted om Nov 16th, 2021.
  • Nov 23, 2021 US Patent 17/534,160 Akhbardeh A. System and Method for Quantitatively Measuring Dyspnea, filled on Nov 24, 2020 (pending).
  • Dec 20, 2021 US Patent 16/557,663 Akhbardeh A. Automated Lung Ultrasound Quantification and Reading for Diagnosis and Treatment Effectiveness Monitoring (pending).
  • April 21, 2016 US Patent 20160106339, Behzadi Y., Akhbardeh A, Lewis C. System, Apparatus And Methods For Data Collection And Assessing Outcomes, Date Awarded: Apr. 21, 2016
  • Aug 20, 2019 US Patent 10,388,017 B2, 2019, Jacobs MA, Akhbardeh, A. Advanced Treatment Response Prediction Using Clinical Parameters and Advanced Unsupervised Machine Learning: The Contribution Scattergram, filed on July 31, 2014, awarded on Aug 20, 20.
  • May 12, 2016 US Patent 20,160,132,754, 2016: Inventors: Akhbardeh A., Jacobs MA. An integrated real-time tracking system for normal and anomaly tracking and the methods therefore Date Awarded: May 12, 2016.
  • Oct 2, 2014 US Patent 20,140,296,655A1: Inventors: Akhbardeh A., Tehrani A. Real-time tracking of cerebral hemodynamic response (RTCHR) of a subject based on hemodynamic parameters.
  • Feb 17, 2012 US Patent 9,008,462, Inventors: Akhbardeh A, Jacobs MA. Methods and systems for registration of radiological images. Date Awarded: April 14, 2015
  • Feb 09, 2016 US Patent 9,256,966, Inventors: Jacobs MA, Akhbardeh A. Multiparametric Non-linear dimension reduction methods for segmentation and classification of radiological images. Date Awarded: Feb 09, 2016

(WIPO) World Intellectual Property Organization for Trade Patents = 6

  • Nov 23, 2021 PCT/US2021/060651: Inventor: Akhbardeh A., Quantitative Measurement Of Dyspnea.
  • Sep 26, 2019 WO2019183136A1: Inventors: Vasefi F., Farkas D.L., Akhbardeh A., Kang L., Stanislov Sokolov S. Apparatus and method for multimode analytical sensing of items such as food.
  • Oct 9, 2014 WO2014164717A1: Inventors: Akhbardeh A., Tehrani A. Real-time tracking of cerebral hemodynamic response (RTCHR) of a subject based on hemodynamic parameters.
  • Dec 11, 2014 WO2014197402A1: Inventors: Behzadi Y., Akhbardeh A, Lewis C. System, Apparatus And Methods For Data Collection And Assessing Outcomes Date Awarded: November 28, 2013.
  • May 28, 2013 WO2013177586: Inventors: Akhbardeh A., Jacobs MA. An integrated real-time tracking system for normal and anomaly tracking and the methods therefore Date Awarded: November 28, 2013.
  • July 31, 2014 WO2015017632: Inventors: Jacobs MA, Akhbardeh A. Advanced treatment response prediction using clinical parameters and advanced unsupervised machine learning: the contribution scattergram. Date Awarded: February 5, 2015.

Publications

RESEARCH ACTIVITIES
Original peer– reviewed scientific articles.

  1. Chauvin J., Akhbardeh A., Brunnemer R., Vasefi F., Bearman G., Huong A., Tavakolian K., “Simulated Annealing-Based Wavelength Selection for Robust Tissue Oxygenation Estimation Powered by the Extended Modified Lambert-Beer Law”, Applied Sciences, 2022.
  2. N. Orangi-Fard, A. Akhbardeh, and H. Sagreiya, “Predictive Model for ICU Readmission Based on Discharge Summaries Using Machine Learning and Natural Language Processing,” Informatics, vol. 9, no. 1, p. 10, Jan. 2022.
  3. Akhbardeh, A., Sagreiya, H., Durot, I., and Rubin, D.L. (2021). “Machine Learning for Automated Hepatic Fat Quantification.” TechConnect Briefs 2021, pp105-108.
  4. Krysko, K.M., Akhbardeh, A., Arjona, J., Nourbakhsh, B., Waubant, E., Antoine Gourraud, P. and Graves, J.S. (2021), Biosensor vital sign detects multiple sclerosis progression. Ann. Clin. Transl. Neurol., 8: 4-14.
  5. Gorji, H. T., Shahabi, S. M., Sharma, A., Tande, L. Q., Husarik, K., Qin, J., Chan, D. E., Baek, I., Kim, M. S., MacKinnon, N., Morrow, J., Sokolov, S., Akhbardeh, A., Vasefi, F., & Tavakolian, K. (2022). Combining deep learning and fluorescence imaging to automatically identify fecal contamination on meat carcasses. Scientific reports, 12(1), 2392.
  6. A. El Kaffas, A. Hoogi, J. Zhou, I. Durot, H. Wang, J. Rosenberg, A. Tseng, H. Sagreiya, A. Akhbardeh, D.L. Rubin, A. Kamaya, D. Hristov and J.K. Willmann, Spatial Characterization of Tumor Perfusion Properties from 3D DCE-US Perfusion Maps are Early Predictors of Cancer Treatment Response, Sci Rep 10, 6996, 2020.
  7. Sueker, M., Stromsodt, K., Gorji, H. T., Vasefi, F., Khan, N., Schmit, T., Varma, R., Mackinnon, N., Sokolov, S., Akhbardeh, A., Liang, B., Qin, J., Chan, D. E., Baek, I., Kim, M. S., & Tavakolian, K. (2021). Handheld Multispectral Fluorescence Imaging System to Detect and Disinfect Surface Contamination. Sensors (Basel, Switzerland), 21(21), 7222.
  8. I. Durot, A. Akhbardeh, H. Sagreiya, A. M. Loening, D.L. Rubin, “A New Multimodel Machine Learning Framework to Improve Hepatic Fibrosis Grading Using Ultrasound Elastography Systems from Different Vendors.” Ultrasound in medicine & biology vol. 46,1 (2020): 26-33.
  9. Chauvin, J.; Duran, R.; Tavakolian, K.; Akhbardeh, A.; MacKinnon, N.; Qin, J.; Chan, D.E.; Hwang, C.; Baek, I.; Kim, M.S.; Isaacs, R.B.; Yilmaz, A.G.; Roungchun, J.; Hellberg, R.S.; Vasefi, F. Simulated Annealing-Based Hyperspectral Data Optimization for Fish Species Classification: Can the Number of Measured Wavelengths Be Reduced? Appl. Sci. 2021, 11, 10628.
  10. A. Akhbardeh, A. El Kaffas, H. Sagreiya, J.K. Willmann, D.L. Rubin, “A multi-model framework to estimate perfusion parameters using contrast-enhanced ultrasound imaging,” Med Phys. 2019 Feb;46(2):590-600.
  11. Qin, J., Vasefi, F., Hellberg, R.S., Akhbardeh, A., Isaacs, R.B., Yilmaz, A.G., Hwang, C., Baek, I., Schmidt, W.F., Kim, M.S. (2020). Detection of fish fillet substitution and mislabeling using multimode hyperspectral imaging techniques. Food Control, 114, 107234.
  12. H. Sagreiya, A. Akhbardeh, D. Li, R. Sigrist, B. Chung, G. Sonn, Lu. Tian, J.K. Willmann, “Point Shear Wave Elastography Using Machine Learning to Differentiate Renal Cell Carcinoma and Angiomyolipoma,” Ultrasound Med Biol. 2019 Aug;45(8):1944-1954.
  13. I. Durot, A. Akhbardeh, J. Rosenberg, J. K. Willmann, “Point Shear Wave Elastography for Grading Liver Fibrosis: Can the Number of Measurements be Reduced? ,” Ultrasound Med Biol. 2018 Dec;44(12):2569-2577.
  14. A. Eisenried, N. Austin , B. Cobb , A. Akhbardeh , B. Carvalho , D. Yeomans and A. Tzabazis, “ Objective pain assessment in volunteers and patients using functional near infrared spectrometry,” Pain Research. 2018 Sep 24; 11:1991-1998.
  15. V. Zakeri, A. Akhbardeh, N. Alamdari, R. Fazel-Rezai, M. Paukkunen and K. Tavakolian, “Analyzing Seismocardiogram Cycles to Identify the Respiratory Phases,” in IEEE Transactions on Biomedical Engineering, vol. 64, no. 8, pp. 1786-1792, Aug. 2017.
  16. Kakkad S, Zhang J, Akhbardeh A, et al. Collagen fibers mediate MRI-detected water diffusion and anisotropy in breast cancers. Neoplasia. 2016;18(10):585-593.
  17. Samata M. Kakkad, Jiangyang Zhang, Alireza Akhbardeh, Meiyappan Solaiyappan, Venu Raman, Dieter Leibfritz, Kristine Glunde, Zaver M. Bhujwalla; Abstract 734: Water diffusion decreased in low collagen containing hypoxic regions of breast cancer xenograft. Cancer Research 15 April 2013; 73 (8_Supplement): 734.
  18. J. Hossain, Y. Du, J. Links, A. Rahmim, N. Karakatsanis, A. Akhbardeh, J. Lyons, E. Frey, “Estimation of dynamic time activity curves from dynamic cardiac SPECT imaging”, Physics in Medicine and Biology, 2015 Apr 21; Vol. 60, Issue 8, pp. 3193-3208.
  19. S.M. Kakkad, M.F. Penet, A. Akhbardeh, A.P. Pathak, M. Solaiyappan, V. Raman, D. Leibfritz, K. Glunde, and Z.M. Bhujwalla , Hypoxic tumor environments exhibit disrupted collagen I fibers and low macromolecular transport, PLOS ONE, 2013 December; Vol. 8, Issue 12, pp. 81869-81880.
  20. A. Akhbardeh, and M.A. Jacobs, “Comparative analysis of nonlinear dimensionality reduction techniques for breast MRI segmentation,” Med Phys. 2012 Apr; Vol. 39, Issue 4, pp. 2275–2289.
  21. S. Junnila, A. Akhbardeh, M. Koivuluoma, and A. Värri, “An Electromechanical Film Sensor Based Wireless Ballistocardiographic Chair: Implementation and Performance,” Journal of Signal Processing Systems, Springer New York, 2009, Vol. 57, Issue 3, pp. 305-320.
  22. A. Akhbardeh, Nikhil, P.E Koskinen and O. Yli-Harja, “Towards the Experimental Evaluation of Novel Supervised Fuzzy Adaptive Resonance Theory for Pattern Classification,” Pattern Recognition Letters – Elsevier, 2008, Vol. 29, Issue 8, pp. 1082-1093.
  23. A. Akhbardeh, S. Junnila, M. Koivuluoma, A. Värri, “Applying Novel Time-Frequency Moments Singular Value Decomposition (TFM-SVD) Method and Artificial Neural Networks for Ballistocardiography,” EURASIP Journal on Advances in Signal Processing, Vol. 2007, Issue 1, pp. 38-48.
  24. A. Akhbardeh, S. Junnila, M. Koivuluoma, T. Koivistoinen, V. Turjanmaa, T. Kööbi, and A. Värri, “Towards a Heart Disease Diagnosing System based on Force Sensitive chair’s measurement, Biorthogonal Wavelets and Neural Network classifiers,” Engineering Applications on Artificial Intelligence- Elsevier, Vol. 20, Issue 4, 2007, pp. 493-502.
  25. A. Akhbardeh, S. Junnila, T. Koivistoinen, and A. Värri, “An Intelligent Ballistocardiographic Chair using a Novel SFART Neural Network and Biorthogonal Wavelets”, Journal of Medical Systems, Vol. 31, Issue 1, 2007, pp. 69-77.

Book Chapters, Monographs [BC]

  1. Chauvin J., Duran R., Ng S., Burke T., Barton K., MacKinnon N., Tavakolian K., Akhbardeh A. and Vasefi F. Advanced Optical Technologies in Food Quality and Waste Management. (2021) IntechOpen Press: Innovation in the Food Sector Through the Valorization of Food and Agro-Food.
  2. Rivaz H., Akhbardeh A. and Boctor E.M. Speckle Detection in Echocardiographic Images. (2011) IntechOpen Press: Echocardiography.

Proceeding Articles

  1. Sagreiya H,  Akhbardeh A and Jacobs M.A., “Novel Quantitative Tool for Assessing Pulmonary Disease Burden in COVID-19 Using Ultrasound,” The American Association of Physicists in Medicine (AAPM) meeting, Washington DC, 2022.
  2. Husarik K., Gorji H.T, Qin J., Chan D.E., Baek I., Kim M.S., MacKinnon N., Sokolov S., Akhbardeh A., Vasefi F., Tavakolian K., “Handheld dual-wavelength fluorescence imaging system for improving food safety: case study in restaurants and institutional kitchens,” Proc. SPIE, Sensing for Agriculture and Food Quality and Safety XIV, May 2022.
  3. Tellinghuisen M., Carriere C., Husarik K., Elderini T., Gorji H.T., Qin J., Chan D.E., Baek I., Kim M.S., MacKinnon N., Sokolov S., Akhbardeh A., Vasefi F., and Tavakolian K., “Autonomous robot with fluorescence imaging system for invisible contamination detection and pathogen deactivation”, Proc. SPIE, Sensing for Agriculture and Food Quality and Safety XIV, 30 May 2022.
  4. Gorji H.T., Shahabi S.M., Tande L.Q, Sharma A., Qin J., Chan D.E., Baek I., Vasefi F., MacKinnon N., Akhbardeh A., Kim M.S., and Tavakolian K., “Food safety assurance and training of meat inspectors using handheld fluorescence imaging with deep learning detection algorithm”, Proc. SPIE, Sensing for Agriculture and Food Quality and Safety XIV, 30 May 2022.
  5. Nischal Khanal, Rabie Fadil, Hamed Gorji, Bo Liang, Fartash Vasefi, Nicholas MacKinnon, Alireza Akhbardeh, Kouhyar Tavakolian., “FootAssure: A multimodal, in-home wound detection device for diabetic peripheral neuropathy,” 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021, pp. 4019-4022.
  6. Orangi-Fard N, Akhbardeh A., and Sagreiya H., “Predicting the Risk for ICU Readmission Using Natural Language Processing and Machine Learning”, 5th International Conference on Medical and Health Informatics, Kyoto, Japan, May 2021.
  7. Ray Duran, Fartash Vasefi, Kouhyar Tavakolian, Nicholas MacKinnon, Alireza Akhbardeh, Jianwei Qin, Chansong Hwang, Insuck Baek, Walter F. Schmidt, Moon S. Kim, Rachel B. Isaacs , Ayse Gamze Yilmaz, Rosalee S. Hellberg, “Multimode hyperspectral data fusion for fish species identification using supervised and reinforcement learning”, Proceedings Volume 11421, Sensing for Agriculture and Food Quality and Safety XII; 114210L (2020).
  8. Jianwei Qin, Fartash Vasefi, Rosalee S. Hellberg, Alireza Akhbardeh, Rachel B. Isaacs, Ayse Gamze Yilmaz, Chansong Hwang, Insuck Baek, Walter F. Schmidt, Moon S. Kim, “Inspecting species and freshness of fish fillets using multimode hyperspectral imaging techniques”, Proceedings Volume 11421, Sensing for Agriculture and Food Quality and Safety XII; 1142104 (2020).
  9. Sagreiya, H., Akhbardeh, A., Durot, I., Rubin, D.L. “Machine Learning for Automated Hepatic Fat Quantification.” 2021 TechConnect World Innovation Conference & Expo has been scheduled for October 18-20, 2021, at the Gaylord National Hotel & Conference Center, National Harbor, Maryland, USA.
  10. R. Duran, F. Vasefi, K. Tavakolian, N. MacKinnon, A. Akhbardeh, J. Qin, C. Hwang, I. Baek, W.F. Schmidt, M.S. Kim, R.B. Isaacs, A.G. Yilmaz, and R.S. Hellberg, Multimode hyperspectral data fusion for fish species identification using supervised and reinforcement learning, SPIE Medical Imaging conference, 2020.
  11. J. Chauvin, F. Vasefi, K. Tavakolian, A. Akhbardeh, N. MacKinnon, J. Qin, D.E. Chan, M.S. Kim, Reconstruction of hyperspectral spectra of fish fillets using multi-wavelength imaging and point spectroscopy, SPIE Medical Imaging conference, 2020.
  12. J. Qin, F. Vasefi, R. S. Hellberg, A. Akhbardeh, R.B. Isaacs, A.G. Yilmaz, C. Hwang, I. Baek, W.F. Schmidt, and M.S. Kim, Inspecting species and freshness of fish fillets using multimode hyperspectral imaging techniques, SPIE Medical Imaging conference, 2020.
  13. Sagreiya, H., Akhbardeh, A., Durot, I., Rubin, D.L. Hepatic Fat Quantification using Ultrasound Point Shear Wave Elastography and Machine Learning. Biomedical Engineering Society. Philadelphia, PA. October 2019.
  14. P. N. Werahera, A. Akhbardeh, E.D. Crawford, ClariCore™ Optical Biopsy System for Prostate Cancer Diagnosis: Preliminary Results from a Multicenter Clinical Trial, 27th International Prostate Cancer Update Meeting, January 2017.
  15. N. Alamdari, N. MacKinnon, F. Vasefi, R. Fazel-Rezai, M. Alhashim, A. Akhbardeh, D.L. Farkas, K. Tavakolian, Effect of Lesion Segmentation in Melanoma Diagnosis for a Mobile Health Application, Proc. ASME. 40672; 2017 Design of Medical Devices Conference, April 10, 2017.
  16. Eisenried, N. Austin, B. Carvalho, A. Akhbardeh, D. C. Yeomans, A. Z. Tzabazis, objective measurement of pain perception in laboring women, International Anesthesia Research Society, May 2016.
  17. S. Kakkad, J. Zhang, A. Akhbardeh, D. Jacob, B. Krishnamachary, M. Solaiyappan, M.A. Jacobs, V. Raman, D. Leibfritz, K. Glunde, Z.M. Bhujwalla: Collagen fibers mediate MRI-detected water diffusion and anisotropy in breast cancers. Neoplasia 10/2016; 18(10).
  18. S.M Kakkad, J. Zhang, A. Akhbardeh, D. Jacob, M. Solaiyappan, M. A Jacobs, V. Raman, D. Leibfritz, K. Glunde, Z. M Bhujwalla, In vivo and ex vivo diffusion tensor imaging parameters follow Collagen 1 fiber distribution in breast cancer xenograft mode. Proceedings of the International Society for Magnetic Resonance in Medicine 06/2015.
  19. Akhbardeh A, Parekth VS, Jacobs MA, A Novel 3D Registration Method for Multiparametric Radiological Images, American Association of Physicists in Medicine, 2015, 42(6), pp.3605-3606.
  20. Alamdari N, Tavakolian K, Fazel-Rezai R, Akhbardeh A., Using Electromechanical Signals Recorded from the Body for Respiratory Phase Detection and Respiratory Time Estimation: A Comparative Study, Computer in Cardiology, 2015.
  21. Austin N., Yeomans D.C., Carvalho B., Akhbardeh A., Tzabazis A. Using real-time cerebral hemodynamic response (RTCHR) to objectively measure pain in volunteers and patients – a practicability and correlation analysis study. Educational exabit, Stanford Anesthesia Research Awards Dinner.
  22. Zakeri V., Tavakolian K., Arzanpour S., Zanetti JM., Dumont G., Akhbardeh A., Preliminary results on quantification of seismocardiogram morphological changes, using principal component analysis, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 6092-6095.
  23. Kakkad S., Zhang J., Akhbardeh A., Jacob D., Solaiyappan M., Jacobs MA.,. Raman V, Leibfritz D., Glunde K., Bhujwalla Z.M., Collagen fibers mediate water diffusion and anisotropy, ISMRM, Utah, 2013.
  24. Kakkad S., Akhbardeh A., Zhang J., Glunde K., Solaiyappan M., Bhujwalla Z.M., Diffusion tensor imaging maps to collagen 1 fiber architecture in human breast cancer specimens, 2013 World Molecular Imaging Congress(WMIC 2013).
  25. S. Kakkad, J. Zhang, A. Akhbardeh, M. Solaiyappan, , V. Raman, K. Glunde and Z.M. Bhujwalla, Frankly hypoxic low collagen containing regions of breast cancer xenografts disrupt water diffusion, 2013 World Molecular Imaging Congress(WMIC 2013), Georgia, USA.
  26. Jiang L., Kakkad S.M., Akhbardeh A.,. Greenwood T.R, Solaiyappan M., Glunde K.,. Bhujwalla Z. M,. Li X, Quantitative second harmonic generation (SHG) microscopy of Col1 fiber signatures in human breast cancers predicts lymph node metastasis, 2013 World Molecular Imaging Congress(WMIC 2013).
  27. S. Kakkad, J. Zhang, A. Akhbardeh, M. Solaiyappan, K. Glunde, Venu Raman, D. Leibfritz, and Z.M. Bhujwalla, Water diffusion is disrupted in low collagen containing hypoxic regions of breast cancer xenograft, ISMRM, Australia, 2012.
  28. S. Kakkad, J. Zhang, A. Akhbardeh, M. Solaiyappan, K. Glunde, Venu Raman, D. Leibfritz, and Z.M. Bhujwalla, Mapping collagen 1 fiber architecture to diffusion tensor imaging in human breast tumor specimens, ISMRM, Australia 2012.
  29. Kakkad S., Akhbardeh A., Solaiyappan M., Penet M, Leibfritz D., Glunde K Bhujwalla ZM., Water ‘3-Dimensional Texture Analysis of Collagen Fibers for Functional Characterization of the Tumor Extracellular Matrix’, 2012 World Molecular Imaging Congress, Dublin, Ireland, 2012.
  30. Kakkad S., Zhang J., Akhbardeh A., Solaiyappan M., Glunde K., Raman V., Leibfritz D., and Bhujwalla ZM., Water diffusion is disrupted in low collagen containing hypoxic regions of breast cancer xenograft, American Association for Cancer Research (AACR) 2012.
  31. Jacobs M.A., Macura K., Kamel I., El-Khouli R., Carrino J., Fayad L., Wahl R.,Akhbardeh A.,’ Whole-Body Multiparametric (T1/T2/DWI/DCE) and Multimodality (PET/CT) Imaging Strategy for Identification and Characterization of Metastatic and Other Disease States, RSNA, Chicago, 2011.
  32. Akhbardeh A and Jacobs M.A.,’ Unsupervised Nonlinear Dimensionality Reduction for multiparametric Oncological Image Segmentation’, AAPM meeting, Philadelphia, PA, 2010.
  33. Tavakolian K., Akhbardeh A., Nagi B., Kaminska B., “Estimation of hemodynamic parameters from Seismocardiogram” Computing in Cardiology conference, 2010.
  34. Tavakolian K., Akhbardeh A.,, Blaber A., Kaminska B., “Estimating Cardiac Stroke Volume from the Seismocardiogram Signal” 15th World Congress on Heart Disease,2010.
  35. Tavakolian K., Blaber A., Akhbardeh A.,, Kaminska B., “Noninvasive analysis of stroke volume variability by recording of cardiac mechanical vibrations on the chest”, 15th World Congress on Heart Disease, 2010.
  36. Vasefi F, Akhbardeh A.,. Najiminaini M, Kaminska B., Chapman GH.,. Carson JL, “Correction of artifacts in angular domain imaging”, Biomedical Optics Topical Meeting (BIOMED) at the Biomedical Optics and 3- D Imaging: OSA Optics and Photonics Congress, FL, USA, 2010.
  37. Ngai B., Tavakolian K., Akhbardeh A., Blaber A.P., Kaminska B., Noordergraaf A., “Comparative analysis of seismocardiogram waves with the ultra-low frequency ballistocardiogram”, Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009, pp. 2851 – 2854
  38. Akhbardeh A., Tavakolian K., Gurev V., Lee T., New W., Kaminska B., Trayanova N., “Image-based cardiac mechanics model: Comparative Analysis of Three Different Modalities for Characterization of Seismocardiogram”, Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009.
  39. Akhbardeh A., Vadakkumpadan F., Trayanova N., “Image-based modeling: Locally Homogenized and De-noised Vector Fields for Cardiac Fiber Tracking in DT-MRI Images”, SPIE Medical Imaging, Orlando, Florida, USA, 2009.
  40. Chen X., Akhbardeh A., Akbarian A., Berger RD., and Trayanova NA., “Novel QT Stability Monitoring Algorithm in Clinical ECG Recordings”, Heart Rhythm -30thannual scientific sessions, Boston, MA, 2009.
  41. A. Akhbardeh, X. Chen, B. Tice, N. Trayanova, “ Artificial Neural Network Can Predict APD Spatial Distribution Based on Activation History”, 2009 BMES Annual Meeting.
  42. K. Tavakolian, B. Ngai, A. Akhbardeh, B. Kaminska, A. Blaber, “ Comparative analysis of infrasonic cardiac signals” Computers in Cardiology, 2009, pp. 757 – 760.
  43. K. Tavakolian, A. Akhbardeh, B. Kaminska, “An Objective Approach towards Assessment of the Physiological Age of Heart”, the Twenty-Third AAAI Conference on Artificial Intelligence, Chicago, Illinois, July 13–17, 2008.
  44. A. Akhbardeh, Meltem Izzetoglu, Scott Bunce, Kambiz Pourrezaei, Banu Onaral, “fNIRData Classification Using Wavelet Transforms and Neural Networks for Attention Monitoring”, Biomedical Optics Topical Meeting (BIOMED) at the 2008 Spring Optics and Photonics Congress, Petersburg Bayfront in St. Petersburg, Florida, USA.
  45. A. Akhbardeh, B. Kaminska and K. tavakolian, BSeg++: A Modified Blind Segmentation Method for Ballistocardiogram Cycle Extraction, EMBC 2007, 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society ,Lyon, France,2007.
  46. A. Akhbardeh and A. Akbarian, “Human Computer Interaction- Applying Fuzzy C-Means, Recurrent Neural Network and Wavelet Transforms for Voluntary Eye Blink Detection” The 2007 European Signal Processing Conference (EUSIPCO-2007), September 3-7, 2007, Poland.
  47. A. Akhbardeh, S. Junnila, T. Koivistoinen, and A. Värri, “Applying Biothogonal wavelets and a Novel QuickLearn Algorithm for an Intelligent Ballistocardographic chair,” 2006 IEEE Mountain Workshop on Adaptive and Learning Systems (Smcal’s 2006), Utah State University, College of Engineering, Logan, U.S.A., July 24 – 26, 2006.
  48. S. Junnila, A. Akhbardeh, L. C Barna, Irek Defee, and A. Värri, “A Wireless Ballistocardiographic Chair,” 28th Annual International Conference IEEE Engineering in Medicine and Biology Society, Aug.30-Sept.3, 2006, New York City, New York, USA.
  49. A. Akhbardeh, S. Junnila, M. Koivuluoma, T. Koivistoinen, A. Värri, “Evaluation of heart condition based on Ballistocardiogram classification using compactly supported wavelet transforms and neural networks,” Proceedings of the 2005 IEEE Conference on Control Applications (CCA’05), Toronto, Canada, 29-31 August 2005.
  50. A. Akhbardeh, S. Junnila, M. Koivuluoma, T. Koivistoinen, A. Värri, “Heart Disease Diagnosing Mechatronics based on Static Charge sensitive chair’s measurement, Biorthogonal Wavelets and Neural classifiers,” 2005 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2005) July 24-28, 2005, Monterey, California. , U.S.A.
  51. A. Akhbardeh, S. Junnila, T. Koivistoinen, A. Värri, “ Ballistocardiogram Classification using a Novel Transform socalled AliMap (Combimap) and Biorthogonal Wavelets,” IEEE International Symposium on Intelligent Signal Processing (WISP ’05), 2005, Faro, Portugal.
  52. A. Akhbardeh, M. Koivuluoma, T. Koivistoinen, A. Värri, “Ballistocardiogram Diagnosis using Neural Networks and Shift-Invariant Daubechies Wavelet transform”, 13th European signal Processing conference (Eusipco’05), 2005, Antalya, Turkey.
  53. A. Akhbardeh, M. Koivuluoma, T. Koivistoinen, A. Värri, “BCG Data Discrimination using Neural networks and Daubechies compactly supported Wavelet Transform for Heart Disease Diagnosing”, 2005 International Symposium on Intelligent Control 13th Mediterranean Conference on Control and Automation, June 27-29, 2005, Limassol, Cyprus.
  54. A. Akhbardeh, A. Vahabian, and M. Farrokhi, “EEG Features Extraction using Neuro-Fuzzy Systems and Shift-Invariant Wavelet Transforms for Epileptic Seizure Diagnosing”, Proc. 26th Annual International Conference IEEE Engineering in Medicine and Biology Society, San Francisco, CA, USA, 2004, pp. 498-502.
  55. A. Vahabian, A. Khaki Sedigh, A. Akhbardeh, “Optimal Design of the Variable Structure IMM Tracking Filters Using Genetic Algorithm,” IEEE 2004 CCA/ISIC/CACSD conference, Taiwan, 2004.
  56. A. Fakharian, M. J. Yazdan Panah, and A. Akhbardeh, “Design of a Nonlinear Optimal Controller for Active Suspension System in Order to Vertical Motion Control of Automotive,” 5th international workshop on research and education in Mechatronics (Rem 2004), Poland, 2004.
  57. A. Akhbardeh and M. Farrokhi, “Voluntary and involuntary Eye blinks detection using Neuro-fuzzy systems and EOG signals for human-computer interface aids,” 5th international workshop on research and education in Mechatronics (Rem 2004), Poland, 2004.
  58. A. Akhbardeh, A Värri, “Novel Supervised Fuzzy Adaptive Resonance Theory (SF-ART) Neural Network for Pattern Recognition,” IEEE International Symposium on Intelligent Signal Processing (WISP ’05), 2005, Faro, Portugal.
  59. A. Akhbardeh, M. Koivuluoma, T. Koivistoinen, A. Värri, “BCG Data Clustering using New Method so-called Timefrequency Moments Singular Value Decomposition (TFM-SVD) and Artificial Neural Networks,” 2005 International Symposium on Intelligent Control 13th Mediterranean Conference on Control and Automation, June 27-29, 2005, Limassol, Cyprus.
  60. S. Junnila, A. Akhbardeh, T. Koivistoinen, A. Värri, “ An EmFi-film Sensor based Ballistocardioghraphic Chair: Performance and Cycle extraction method,” 2005 IEEE Workshop on Signal Processing Systems (SIPS’05), 2005, Greece.
  61. M. Rezaei, A. Akhbardeh, M. Hannuksela, and M. Gabbouj, “Fuzzy Rate Controller for Variable Bitrate Video in Mobile Applications,” the 2006 IEEE International Conference on Communications (ICC 2006), Istanbul, Turkey, on 11-15 June 2006.
  62. A. Akhbardeh, A Värri, “Applying Novel QuickLearn Algorithm for Pattern Recognition,” 2006 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2006), October 8-11, 2006, Taipei, Taiwan.
  63. A. Akhbardeh, S. Junnila, T. Koivistoinen, and A. Värri, “Applying Novel Supervised Fuzzy Adaptive Resonance Theory (SF-ART) neural network, Biorthogonal wavelets for Ballistocardiogram diagnosis,” 2006 IEEE Conference on Control Applications, October 4-6, 2006, Munich, Germany.
  64. A. Akhbardeh, S. Junnila, T. Koivistoinen, and A. Värri, “Design an Intelligent Ballistocardiographic Chair using Novel QuickLearn and SF-ART Algorithms and Biorthogonal Wavelets,” 2006 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2006), October 8-11, 2006, Taipei, Taiwan.

Local and national:

  1. A. Akhbardeh, A. Erfaniaan, “Discrimination different patterns of the EOG signal by using adaptive resonance theory networks”, Journal of Tabriz University, Tabriz, Iran, 2003.
  2. A. Akhbardeh, A. Erfaniaan, “Developing a Bioinstrument & computer-based data acquisition system,” technical report, 2000, University of Science & Technology, Tehran.
  3. A. Akhbardeh, “Wavelets theory & applications for Multi-resolution signals and image processing”, Review book, 2000, University of Science & Technology, Tehran.
  4. A. Akhbardeh and A. Erfaniaan, “Detection of left and right hand movement by using EOG signals for human computer interface,” in Proc. Int. CSI Computer Conference, vol. 6, Tabriz, 2001.
  5. A. Akhbardeh, A. Erfaniaan, “Discrimination different patterns of the EOG signal by using adaptive resonance theory networks,” in Proc. the 10th International Conference on Electrical Engineering (ICEE), Tabriz, 2002.