ABHISHEK CHAKRABORTY

About

I have a strong desire to use technology in a proper way to provide universal healthcare.
The focus of most of my endeavor is concentrated on the development of straightforward and effective automated diagnostic solutions using machine learning and data processing techniques, particularly for smart cardiac monitoring applications.
I have an extensive background in medical informatics, biological equipment, and biological signal processing, as well as research and teaching.
At present, I am still continuing as a research fellow at the Department of Applied Physics, University of Calcutta.
I have twelve research publications in peer-reviewed journals and conference proceedings either written by me or happened due to collaboration with my colleagues.
I am an awardee of the IETE M. N. Saha Memorial Award.
Expertise: Computer-assisted diagnosis; Biomedical data processing; Machine learning; Pattern recognition; Cardiac diagnosis.

Employment

• University of Calcutta - Rajabazar Science College Campus Research Scholar
  2014 - Present
• Dum Dum Motijheel College Lecturer
  2009 - Present

Education

• University of Calcutta PhD
  2015 - 2023

Projects & Funding

Projects & funding information is unavailable.

Publications (13)

• Utility of non-dimensional feature analysis of the PPG signal for automated screening of myocardial infarction (MI)
  Biomedical Signal Processing and Control 2026 DOI: 10.1016/j.bspc.2025.108786
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• Automated Detection of Mental Stress Using Multimodal Characterization of PPG Signal for AI Based Healthcare Applications
  SN Computer Science 2024 DOI: 10.1007/s42979-024-03110-x
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• Efficient detection of cardiac abnormalities via a simplified score-based analysis of the ECG signal
  Journal of Ambient Intelligence and Humanized Computing 2024 DOI: 10.1007/s12652-023-04745-z
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• A simplified PPG based approach for automated recognition of five distinct emotional states
  Multimedia Tools and Applications 2023 DOI: 10.1007/s11042-023-16744-5
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• Efficient and lightweight detection of PPG onset and systolic peaks using implementable time-domain strategies
  Measurement 2022 DOI: 10.1016/j.measurement.2022.111628
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• EEG Based Automated Detection of Six Different Eye Movement Conditions for Implementation in Personal Assistive Application
  Wireless Personal Communications 2022 DOI: 10.1007/s11277-021-09389-w
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• Effortless detection of premature ventricular contraction using computerized analysis of photoplethysmography signal
  Sadhana - Academy Proceedings in Engineering Sciences 2022 DOI: 10.1007/s12046-021-01781-3
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• Accurate detection of dicrotic notch from PPG signal for telemonitoring applications
  International Journal of Biomedical Engineering and Technology 2021 DOI: 10.1504/ijbet.2021.119500
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• PPG-BASED AUTOMATED ESTIMATION OF BLOOD PRESSURE USING PATIENT-SPECIFIC NEURAL NETWORK MODELING
  Journal of Mechanics in Medicine and Biology 2020 DOI: 10.1142/s0219519420500372
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• Automated myocardial infarction identification based on interbeat variability analysis of the photoplethysmographic data
  Biomedical Signal Processing and Control 2020 DOI: 10.1016/j.bspc.2019.101747
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