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Publication

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Journal Papers

  1. T. Paul, O. Hassan, C.S/ McCrae, S.K. Islam, A.S.M. Mosa, “An Explainable Fusion of ECG and SpO2-Based Models for Real-Time Sleep Apnea Detection,” Bioengineering. 2025; 12(4):382. https://doi.org/10.3390/bioengineering12040382
  2. I.A. Udoy, O. Hassan, “AI-Driven Technology in Heart Failure Detection and Diagnosis: A Review of the Advancement in Personalized Healthcare,” Symmetry 2025, 17, 469. https://doi.org/10.3390/sym17030469
  3. T. Paul, O. Hassan, S. K. Islam, A.S.M. Mosa, “Real-Time Obstructive Sleep Apnea Detection from Raw ECG and SpO2 Signal Using Convolutional Neural Network,” AMIA Jt Summits Transl Sci Proc. 2024 May 31;2024:662-669. PMID: 38827094; PMCID: PMC11141842.
  4. T. Paul, O. Hassan, C.S. McCrae, S.K. Islam, A. S. M. Mosa, “Lightweight and Low-Parametric Network for Hardware Inference of Obstructive Sleep Apnea,” Diagnostics. 2024; 14(22):2505. https://doi.org/10.3390/diagnostics14222505
  5. O. Hassan, T. Paul, N. Amin, T. Titirsha, D. Parvin, A. S. M. Mosa, and S. K. Islam, “An Optimized Hardware Inference of SABiNN: Shift-Accumulate Binarized Neural Network for Sleep Apnea Detection”, IEEE Transactions on Instrumentation and Measurements, IEEE, 2023, April.
  6. O. Hassan, T. Paul, M. M. Hossain Shuvo, D. Parvin, R. Thakker, M. Chen, A. S. M. Mosa, and S. K. Islam, “Energy Efficient Deep Learning Inference Embedded on FPGA for Sleep Apnea Detection”, Journal of Signal Processing Systems, Springer, 2022.
  7. D. Parvin, O. Hassan, T. Oh, S. K. Islam, “Design of a Smart Maximum Power Point Tracker (MPPT) for RF Energy Harvester”, International Journal of High-Speed electronics and systems. doi:10.1142/S0129156420400066
  8. T. Oh, D. Parvin, O. Hassan, S. Shamsir, S. K. Islam, “MPPT Integrated DC-DC Boost Converter for RF Energy Harvester”, in IET Circuits, Devices and Systems. doi: 10.1049/iet-cds.2019.0509
  9. M. M. S. Hassan and O. Hassan, “Higher Education and Creation of Jobs in Bangladesh”, European Journal of Teaching and Education.
  10. M. M. S. Hassan and O. Hassan, “The Importance of Changing the Traditional Mode of Higher Education in Bangladesh: Creating huge Job Opportunities for Home and Abroad”, 21st Int. Conf. On Employment, Education, and Entrepreneurship (ICEEE), June 2019.

Book Chapter

  1. S. Shamsir, M. S. Hasan, O. Hassan, P. S. Paul, M. R. Hossain, M. R. Islam, “Semiconductor Device Modeling and Simulation for Electronic Circuit Design”, In Modeling and Simulation in Engineering, IntechOpen, April 29 2020.

Conference Papers

  1. I. A. Udoy, R. Sharmin, M. M. Hossain, S. K. Islam and O. Hassan, “Lightweight Binarized Neural Network for Real-Time Sleep Apnea Detection on Edge Hardware”, 2025 IEEE Medical Measurements & Applications (MeMeA), Chania, Greece, 2025, pp. 1-6, doi: 10.1109/MeMeA65319.2025.11068064.
  2. O. Hassan, M. M. Hossain, T. Paul, S. A. Pullano, and S. K. Islam, “Design of a Power-Efficient Digital Classifier for Neural Network-Based Sleep Apnea Detection System,” 2024 IEEE International Symposium on Medical Measurements and Applications (MeMeA), Eindhoven, Netherlands, 2024, pp. 1-6, doi: 10.1109/MeMeA60663.2024.10596842.
  3. M. G. Bianco et al., “Nailfold Video Capillaroscopy Based on Sidestream Dark Field and Stacking Algorithm,” 2024 IEEE International Symposium on Medical Measurements and Applications (MeMeA), Eindhoven, Netherlands, 2024, pp. 1-4, doi: 10.1109/MeMeA60663.2024.10596745.
  4. O. Hassan, R. Thakker, T. Paul, D. Parvin, and S. K. Islam, “SABiNN: FPGA Implementation of Shift Accumulate Binary Neural Network Model for Real -Time Automatic Detection of Sleep Apnea”, 2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).
  5. O. Hassan, T. Paul, R. Thakker, D. Parvin, M. M. H. Shuvo, A. S. M. Mosa, S. K. Islam, “A Multi-Sensor Based Automatic Sleep Apnea Detection System for Adults Using Neural Network Inference on FPGA “, The 17th Edition IEEE Medical Measurements and Application Conference 2022
  6. D. Parvin, O. Hassan, T. Titirsha and S. K. Islam, “FPGA Implementation of an Energy Efficient Neural Network Model for Maximum Power Point Tracking”, National Radio Science Meeting (USNC-URSI) 2022.
  7. T. Paul, O. Hassan, S. K. Islam and A. S. M. Mosa, “ECG and SpO2 Signal-Based Real-Time Sleep Apnea Detection Using Feed-Forward Artificial Neural Network”, American Medical Informatics Association (AMIA) Symposium, 2022.
  8. M. M. Hossain Shuvo, O. Hassan, D. Parvin, M. Chen and S. K. Islam, “An Optimized Hardware Implementation of Deep Learning Inference for Diabetes Prediction,” 2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2021, pp. 1-6.
  9. D. Parvin, O. Hassan, T. Oh and S. K. Islam, “RF Energy Harvester Integrated Self-Powered Wearable Respiratory Monitoring System,” 2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2021, pp. 1-6,
  10. O. Hassan, D. Parvin and S. K. Islam, “Machine Learning Model Based Digital Hardware System Design for Detection of Sleep Apnea Among Neonatal Infants”, The 63rd Edition of IEEE International Midwest Symposium on Circuits and Systems 2020.
  11. O. Hassan, S. Shamsir and S. K. Islam, “Machine Learning Based Hardware Model for a Biomedical System for Prediction of Respiratory Failure”, The 15th Edition of IEEE International Symposium on Medical Measurements and Applications 2020.
  12. S. Shamsir, O. Hassan and S. K. Islam, “Smart Infant-Monitoring System with Machine Learning Model to Detect Physiological Activities and Ambient Conditions”, IEEE International Instrumentation & Measurement Technology Conference 2020.
  13. Oh. T, O. Hassan, S. Shamsir and S. K. Islam, “DC-DC Boost Converter Design with Maximum Power Point Tracker (MPPT) used in RF- Energy Harvester”, IEEE International Symposium on Medical Measurements and Applications, June 2019.
  14. Oh. T, O. Hassan, S. Shamsir and S. K. Islam, “Low-Power RF Energy Harvester Circuit Design for Wearable Medical Applications” , National Radio Science Meeting (USNC-URSI), Jan 2019

More Information

For more information about the papers, visit: ScholarWorks

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