About Dr Chandan Karmakar, PhD

 

PERSONAL DETAILS

Name: Chandan Karmakar

Senior Lecturer, Computer Science

School of Information Technology, Deakin University, Burwood, VIC 3125.

GRANTS & AWARDS

  • 2019-21 Discovery Projects on “New Entropy Measures of Short Term Signals for Smart Wearable Devices”. Australian Research Council (DP190101248)

  • 2020-21 Research project with PhiliaLabs PhiliaLabs (https://philialabs.com.au/)

  • 2020 Use of wearable technology in the construction industry with a specific focus on screening workers body temperature. Incolink (https://incolink.org.au/)

  • 2019 Australia–India Early- and Mid-Career Fellowships Australian Academy of Science

  • 2018 Innovation Connection Grant Australian Government (Industry partner: Agersens)

  • 2018 School of Information Technology research Award for excellence in “Research Collaboration and Teamwork” School of Information Technology, Deakin University

  • 2017 Australia-China young scientist exchange program 2017 Australian Academy of Technological Sciences and Engineering

  • 2017 Identifying smoker subgroups with high and low smoking cessation probability SEBE RGS 2018, Deakin University

  • 2016-18 Inter-State Distance Analysis and Its Application to Evaluating the Coupling in Short-Term RR-QT Interval Series, The National Natural Science Foundation of China

  • 2016 Research Visit to Japan 2016-17 Australian Academy of Science

  • 2015-16 Complex network based model for extracting dynamical information from EMR Central Research Grant Scheme, Deakin University

  • 2015 Alfred Deakin Postdoctoral Research Fellowship Deakin University

  • 2015 Research Support Grant Deakin University

  • 2014 Ian Potter Foundation Travel Grant (Travel and Conference Grants) Ian Potter Foundation

  • 2013 Novel multi-scale HRV Analysis Techniques for Tracking CAN in Diabetes The University of Melbourne (Early Career Researcher Grants Scheme)

PUBLICATIONS

Book

  1. A. H. Khandoker, C. Karmakar, M. Brennan, M. Palaniswami, and A. Voss, Poincaré Plot Methods for Heart Rate Variability Analysis, 1. ed., Boston, MA: Springer US, 2013.

Book chapters

  1. C. Karmakar, A. H. Khandoker, H. F. Jelinek, and M. Palaniswami, "Tone-entropy analysis of heart rate variability in cardiac autonomic neuropathy," ECG time series variability analysis: engineering and medicine, pp. 227-248, 2018.

  2. H. F. Jelinek, D. J. Cornforth, A. Koenig, R. Riener, C. Karmakar, M. H. Imam, et al., "Monitoring patients during neurorehabilitation following central or peripheral nervous system injury: dynamic difficulty adaptation," ECG time series variability analysis: engineering and medicine, pp. 281-296, 2018.


Journal articles (peer reviewed)

  1. S. Datta, C. Karmakar, A. Rao, B. Yan and M. Palaniswami, "Upper limb movement profiles during spontaneous motion in acute stroke", Physiological Measurement, 2021.

  2. E. Keenan, C. Karmakar, F. Brownfoot and M. Palaniswami, "Personalized Anatomic Modeling for Noninvasive Fetal ECG: Methodology and Applications", IEEE Transactions on Instrumentation and Measurement, 2021.

  3. C. Karmakar, R. Udhayakumar and M. Palaniswami, "Entropy Profiling: A Reduced-Parametric Measure of Kolmogorov-Sinai Entropy from Short-Term HRV Signal", Entropy, 2020.

  4. S. Datta, C. Karmakar, B. Yan and M. Palaniswami, "Novel Measures of Similarity and Asymmetry in Upper Limb Activities for Identifying Hemiparetic Severity in Stroke Survivors", IEEE Journal of Biomedical and Health Informatics, 2020.

  5. R. Udhayakumar, C. Karmakar, P. Li, X. Wang and M. Palaniswami, "Modified Distribution Entropy as a Complexity Measure of Heart Rate Variability (HRV) Signal", Entropy, 2020.

  6. B. Shi, M. Motin, X. Wang, C. Karmakar and P. Li, "Bivariate Entropy Analysis of Electrocardiographic RRQT Time Series", Entropy, 2020.

  7. S. Datta, C. Karmakar, A. Rao, B. Yan, M. Palaniswami, “Automated Scoring of Hemiparesis in Acute Stroke from Measures of Upper Limb Co-ordination using Wearable Accelerometry”, IEEE Trans. On Neural Systems and Rehabilitation Engineering, 2020.

  8. L Brown, C Karmakar, M Flynn, MA Motin, M Palaniswami, CM Celano, J Huffman, C Bryant,” A Self- Compassion Group Intervention for Patients Living With Chronic Medical Illness: Treatment Development and Feasibility Study.”, The primary care companion for CNS disorders, vol. 21(5), pp. , 2019.

  9. R. K. Udhayakumar, C. Karmakar, and M. Palaniswami, "Multiscale entropy profiling to estimate complexity of heart rate dynamics," Phys. Rev. E, vol. 100, 2019.

  10. A. Habib, C. Karmakar, and J. Yearwood, "Impact of ECG Dataset Diversity on Generalisation of CNN Model for Detecting QRS Complex” IEEE Access, vol. -, pp. -, 2019.

  11. M. A. Motin, C. Karmakar, and M. Palaniswami, "PPG Derived Heart Rate Estimation during Intensive Physical Exercise” IEEE Access, vol. -, pp. -, 2019.

  12. M. A. Motin, C. Karmakar, and M. Palaniswami, " Selection of Empirical Mode Decomposition Techniques for Extracting Breathing Rate from PPG" IEEE Signal Processing Letter, vol. -, pp. -, 2019.

  13. M. Sapina, C. Karmakar, K. Kramaric, M. Garcin, P. Adelson, K. Milas, M. Piric, D. Brdaric and J. Yearwood, “Multi-lag tone–entropy in neonatal stress”, J. R. Soc. Interface 15: 20180420, 2018.

  14. L. Brown, C. Karmakar, R. Grey, R. Jindal, T. Lim, and C. Bryant, "Heart rate variability alterations in late life depression: A meta-analysis," Journal of Affective Disorders, 2018.

  15. R. K. Udhayakumar, C. Karmakar, and M. Palaniswami, "Understanding Irregularity Characteristics of Short-term HRV Signals using Sample Entropy Profile," IEEE Transactions on Biomedical Engineering, vol. 65(11), pp. 2569-2579, 2018.

  16. Karmakar, C., Udhayakumar, R., Li, P. and Palaniswami, M., “Stability, Consistency and Performance of Distribution Entropy in Analysing Short Length Heart Rate Variability (HRV) Signal”, Frontiers in Physiology, 8:720, September, 2017.

  17. Luo, W, Phung, D, Tran, T, Gupta, S, Rana, S, Karmakar, C.K, Shilton, A, Yearwood, J, Dimitrova, N, Ho, TB,Venkatesh, S, Berk, M, & Eysenbach, G, "Guidelines for Developing and Reporting Machine LearningPredictive Models in Biomedical Research: A Multidisciplinary View", Journal of Medical Internet Research,2016, 18, (12), pp. 1.

  18. Fernandes, BS, Steiner, J, Molendijk, ML, Dodd, S, Nardin, P, Gonçalves, C, Jacka, F, Köhler, CA, Karmakar,C.K, Carvalho, AF, & Berk, M, "C-reactive protein concentrations across the mood spectrum in bipolardisorder: a systematic review and meta-analysis", The Lancet Psychiatry, 2016, 3, pp. 1147-1156.

  19. C. Karmakar, Y. Kimura, M. Endo, M. Palaniswami and A. Khandoker, “Analysis of Fetal Heart Rate Asymmetry Before and After 35 weeks of Gestation”, Biomedical Signal Processing and Control, vol. 21, pp.43-48, 2015.

  20. A. Khandoker, C. Karmakar, Y. Kimura, M. Endo, S. Oshio, and M. Palaniswami, “Tone Entropy Analysis of Foetal Heart Rate Variability,” Entropy, vol. 17, no. 3, pp. 1042-1053, 2015.