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Publications

[1]  ASA Huque, KI Ahmed, MA Mukit, R Mostafa, “HMM-based Supervised Machine Learning Framework for the Detection of ECG R Peak Locations,” Innovation and Research in BioMedical engineering (IRBM), vol. 40 (3), pp. 157-‌166, 2019.  (doi: 10.1016/j.irbm.2019.04.004)   [I.F.– 0.934]

[2]  S. Saha, M.S. Hossain, K. Ahmed, R. Mostafa, L. Hadjileontiadis, A. Khandoker and M. Baumert, “Wavelet Entropy-based inter-subject associative cortical source localization for sensorimotor BCI,” Frontiers in Neuroinformatics, 2019.   (doi:10.3389/fninf.2019.00047)   [I.F.– 2.680]

[3]  S. Saha, K. A. Mamun, K. I. Ahmed, R. Mostafa, G. R. Naik, A. H. Khandoker, S. Darvishi, and M. Baumert, “Progress in brain computer interfaces: Challenges and trends,” CoRR, vol. abs/1901.03442, 2019.

[4]  Rahman, M.K.M., Bhuiyan, M.O.S. and Mannan Joadder, M.A. ‘Progressive fusion of feature sets for optimal classification of MI signal,” Accepted for Int. J. Biomedical Engineering and Technology, 2018.

[5]  S. Saha, K. Ahmed, R. Mostafa, A. Khandoker and L. Hadjileontiadis, “Evidence of Variabilities in EEG Dynamics during Motor Imagery-Based Multiclass Brain Computer Interface,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. PP, no. 99, pp. 1-1,2018.   (doi: 10.1109/TNSRE.2017.2778178)   [I.F.– 3.478]

[6]  A.H. Khandoker, V. Luthra, Y. Abouallaban, S. Saha, K. Ahmed, R. Mostafa, N. Chowdhury and H. Jelinek, “Suicidal Ideation Is Associated with Altered Variability of Fingertip Photo-Plethysmogram Signal in Depressed Patients,” Frontiers in Physiology, vol. 8, p. 501, 2017.   (doi: 10.3389/fphys.2017.00501)   [I.F.– 3.201]

[7]  S. Saha, K. Ahmed, R. Mostafa, A. Khandoker and L. Hadjileontiadis, “Enhanced inter-subject brain computer interface with associative sensorimotor oscillations,” Healthcare Technology Letters, vol. 4, no. 1, pp. 39-43, 2017.   (doi: 10.1049/htl.2016.0073)

[8]  M. K. M. Rahman and M. A. M. Joadder. “A Review on the Components of EEG-based Motor Imagery Classification with Quantitative Comparison,” Application and Theory of Computer Technology, ISSN 2514-1694, [S.l.], v. 2, n. 2, p. 1-15, 2017.   (doi:10.22496/atct20170122133)

[9]  A.H. Khandoker, V. Luthra, Y. Abouallaban, S. Saha, K. Ahmed, R. Mostafa, N. Chowdhury and H. Jelinek, “Predicting depressed patients with suicidal ideation from ECG recordings,” Medical & Biological Engineering & Computing, vol. 55, no. 5, pp. 793-805, 2016.   (doi: 10.1007/s11517-016-1557-y)   [I.F.– 1.82]

[1]  M. G. Morshed, M. A. Mukit, K. Ahmed, R. Mostafa, S. Parveen, and A. H. Khandoker, “Heart rate variability analysis for diagnosis of diabetic peripheral neuropathy,” in IEEE TENSYMP 2020June, 2020, Bangladesh.

[2]  T. A. Ahmed, M. A. Mukit, K. Ahmed, R. Mostafa, S. Parveen, and A. H. Khandoker, “Effective segmention on 24-hour holter recording for classifying microvascular complications of T2DM,” in IEEE TENSYMP 2020June, 2020, Bangladesh

[3]  M.S. Hossain, S. Saha, K. Ahmed, R. Mostafa. “cMEM-based motor imagery induced cortical source localization for computationally efficient brain computer interface,” 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC), 2017, doi:10.1109/r10-htc.2017.8289018.

[4]  M. A. M. Joadder and M. K. M. Rahman, “Classification of Motor Imagery signal using wavelet decomposition: A study for optimum parameter settings,” In proc. of International Conference on Medical Engineering, Health Informatics and Technology (MediTec), Dhaka, 2016, pp. 1-6.  (doi: 10.1109/MEDITEC.2016.7835388)

[5]  M. K. M. Rahman, M. A. M. Joadder and T. A. Ashique, “Seizure detection system: A comparative study on features and fusions,” In proc. of International Conference on Medical Engineering, Health Informatics and Technology (MediTec), Dhaka, 2016, pp. 1-6.  doi: 10.1109/MEDITEC.2016.7835389

[6]  S. Saha, K. I. Ahmed and R. Mostafa, “Wavelet coherence based channel selection for classifying single trial motor imagery,” 2016 9th International Conference on Electrical and Computer Engineering (ICECE), Dhaka, Bangladesh, 2016, pp. 467-470. (doi: 10.1109/ICECE.2016.7853958)

[7]  M. S. Hossain, S. Saha, M. A. Habib, A. A. Noman, T. Sharfuddin and K. I. Ahmed, “Application of wavelet-based maximum entropy on the mean in channel optimization for BCI,” 2016 International Conference on Medical Engineering, Health Informatics and Technology (MediTec), Dhaka, Bangladesh, 2016, pp. 1-5. (doi: 10.1109/MEDITEC.2016.7835394)

[8]  A. S. Sabbir, K. M. Bodroddoza, A. Hye, M. F. Ahmed, S. Saha and K. I. Ahmed, “Prototyping Arduino and Android based m-health solution for diabetes mellitus patient,” 2016 International Conference on Medical Engineering, Health Informatics and Technology (MediTec), Dhaka, Bangladesh, 2016, pp. 1-4. (doi: 10.1109/MEDITEC.2016.7835360)

[9]  A. Khandoker, V. Luthra, Y. Abouallaban, S. Saha, K. Ahmed, R. Mostafa, N. Chowdhury and H. Jelinek, “Identifying depressed patients with and without suicidal ideation by finger photo-plethysmography,” 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, 2016, pp. 1842-1845. (doi: 10.1109/EMBC.2016.7591078)

[10] S. Saha, K. I. Ahmed and R. Mostafa, “Unifying sensorimotor dynamics in multiclass brain computer interface,” 2016 5th International Conference on Informatics, Electronics and Vision (ICIEV), Dhaka, 2016, pp. 530-535. (doi: 10.1109/ICIEV.2016.7760060)

[11] A. Khandoker, V. Luthra, Y. Abouallaban, S. Saha, K. Ahmed, R. Mostafa, N. Chowdhury and H. Jelinek, “Reduced variability in pulse wave velocity in depressed patients with suicidal ideation,” 2015 Computing in Cardiology Conference (CinC), 2015, pp. 1061-1064. (doi: 10.1109/CIC.2015.7411097)

[12] S. Saha and K. I. Ahmed, “Efficient event related oscillatory pattern classification for EEG based BCI utilizing spatial brain dynamics,” 8th International Conference on Electrical and Computer Engineering, Dhaka, 2014, pp. 707-710. (doi: 10.1109/ICECE.2014.7027027)

[1]  M.S. Hossain, K. Ahmed, R. Mostafa, A. Khandoker and L. Hadjileontiadis, “Predicting Motor Imagery based Across Subject Brain Computer Interface Performance using Kullback-Leibler Divergence”- In preparation.