Dr. Mohammod Abdul Motin
Designation: Assistant Professor
Academic Institution: RUET, Rajshahi
Research Field: Signal Processing, Machine Learning, Biomedical
Engineering
Research Interest: Signal Processing and Machine Learning for
Healthcare Monitoring
Email: mamotin@eee.ruet.ac.bd
Website (Official) / Website (Personal) / Researchgate / Google Scholars /
LinkedIn

Institutional Contact
Assistant Professor, Department of Electrical & Electronic Engineering, Rajshahi University of
Engineering & Technology, Rajshahi-6204.
Short Biography
Dr Mohammod Abdul Motin completed his PhD with the Department of Electrical and Electronic
Engineering, the University of Melbourne, Victoria, Australia, in 2020. He received the M.Sc. Eng. and
B.Sc. Eng. degree in electrical & electronic engineering from the Rajshahi University of Engineering
and Technology, Rajshahi, Bangladesh, in 2014 and 2011, respectively. He is currently working as an
Assistant Professor at the Department of Electrical & Electronic Engineering, Rajshahi University of
Engineering and Technology, Bangladesh. His research interests include biomedical signal processing
and machine learning, time series analysis, embedded system, neurological disorders monitoring, and
health care monitoring using wearable sensors and devices.
Awards and Recognition
1. Best Paper Award, ICEEE 2021
2. IEEE Upsilon Pi Epsilon Award-2019
3. Honorable Mention-2018 Upsilon Pi Epsilon Honor Society
4. 3rd Place, IEEE R10 SAC PAPER CONTEST 2018 (PG Level)
5. 2nd Place, 2017 IEEE Australia Council Student Paper Competition (PG Level)
6. ISSNIP Travelling Scholarship
7. Melbourne Abroad Travelling Scholarship (MATS)
8. IEEE Lance Stafford Larson Award
9. IEEE Richard E. Merwin Scholarship
10. W. E. and C. H. H. Cook Memorial Award
11. ANZSCON 2017 Travel Grant, IEEE Student Branch, The University of Melbourne, Australia
12. MIRS Scholarship,The University of Melbourne, Australia
13. MIFRS Scholarship, The University of Melbourne, Australia
14. RUET Postgraduate Scholarship (M. Sc. Engineering)
15. Student of the Year Award (3

rd & 4th Year).

Selected publications
1. Mohammod Abdul Motin, Nemuel D. Pah, Sanjay Raghav, and Dinesh K. Kumar: Parkinson’s
Disease Detection Using Smartphone Recorded Phonemes in Real- World Conditions, IEEE
Access, 2022.
2. Nemuel D. Pah, Mohammod Abdul Motin, and Dinesh K. Kumar: “Phonemes Based Detection
of Parkinson’s Disease for Telehealth Applications”, Scientific Reports, 2022.
3. Peters J, Mohammod Abdul Motin, Perju-Dumbrava L, Ali SM, Ding C, Eller M, Raghav S,
Kumar DK, Kempster PA: Computerised analysis of writing and drawing by essential tremor
phenotype, BMJ Neurology Open, 2021.

4. Nemuel D. Pah, Mohammod Abdul Motin, Peter Kempster, and Dinesh K. Kumar: Detecting
effect of levodopa in Parkinson’s disease patients using sustained phonemes, IEEE Journal of
Translational Engineering in Health and Medicine, 2021.
5. Mohammod Abdul Motin, James Peters, Laura Perju-Dumbrava, Catherine Ding, Michael Eller,
Sanjay Raghav, Sheik Mohammed Ali, Peter Kempster, PJ Radcliffe, Dinesh Kumar:
Computerized Screening of Essential Tremor and Level of Severity Using Consumer Tablet,
IEEE Access, 2021.
6. Mohammod Abdul Motin, Chandan Karmakar, Marimuthu Palaniswami, Thomas Penzel: PPG
Based Automatic Sleep-Wake Classification Using Support Vector Machine, Physiological
Measurement, 2020.
7. Mohammod Abdul Motin, Chandan Karmakar, Marimuthu Palaniswami: Selection of Empirical
Mode Decomposition Techniques for Extracting Respiratory Rate from PPG, IEEE Signal
Processing Letter, vol. 26, no. 4, pp. 592-596, 2019.
8. Mohammod Abdul Motin, Chandan Karmakar, Marimuthu Palaniswami: PPG Derived Heart
Rate Estimation during Intensive Physical Exercise using Recursive Wiener Filtering, IEEE
Access, 7, pp.56062-56069, 2019.
9. Mohammod Abdul Motin, Chandan Karmakar, Marimuthu Palaniswami: Ensemble Empirical
Mode Decomposition with Principal Component Analysis: A Novel Approach for Extracting
Respiratory Rate and Heart Rate from Photoplethysmographic Signal. IEEE Journal of
Biomedical and Health Informatics, vol. 22, no. 3, pp. 766-774, 2018.