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Brief Profile:

Dr. N. Punitha completed her B.E. in Biomedical Engineering and M.E. in Medical Electronics from College of Engineering, Guindy, Anna University. She was awarded the “Gold Medal” by Anna University for being the academic topper during her Post-Graduation in 2015. 

She completed her Ph.D. from Indian Institute of Technology Madras in 2019. Her Ph.D. research was on the analysis of uterine Electromyography signals associated with Term and Preterm contractions using nonlinear algorithms and machine learning techniques. She worked as a Project Officer at Indian Institute of Technology Madras for a period of one and half years. 

Her key research areas include Biomedical Signal Processing, Medical Image Processing, Artificial Intelligence and Machine Learning. 

Journal Publications :

• Punitha N, Vardhini P and Ramakrishnan S (2019), “Multifractal Analysis of Uterine Electromyography Signals for the Assessment of Progression of Pregnancy in Term Conditions”, IEEE Journal of Biomedical and Health Informatics, 23(5), 1972 -1979 
• Punitha N and Ramakrishnan S (2019), “Analysis of uterine EMG signals in Term and Preterm conditions using Generalized Hurst exponent features”, IET Electronics Letters, 55(12), 681-683
• Punitha N and Ramakrishnan S (2019), “Multifractal Analysis of Uterine Electromyography signals to differentiate Term and Preterm conditions”, Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, 233(3), 362-371 
• Vinothini S, Punitha N, Karthick P.A and Ramakrishnan S (2021) “Automated detection of Preterm Condition using Uterine Electromyography based Topological Features”, Biocybernetics and Biomedical Engineering, 41(1), 293-305 
• Vardhini P, Punitha N and Ramakrishnan S (2021) “Analysis of Preterm Pregnancies using Empirical Mode Decomposition based Fractal Features”, Current Directions in Biomedical Engineering, 7(2), 783-786
• Francis S V, Punitha N and Sasikala M (2016), “Cancer detection in rotational breast thermography images using bispectral invariant features”, Journal of Chemical and Pharmaceutical Sciences, 9(4), 2189-2194
• Ajitha R and Punitha N (2022), “Active contour-based segmentation of normal and fetal spina bifida ultrasound images”, Journal of Physics: Conference Series, 2318(1), 012045

International Conferences: 

• Vinothini S, Punitha N and Ramakrishnan S, “Analysis of Electromyography Burst Signals using Topological Feature Extraction for Diagnosis of Preterm Birth”, Proceedings of IEEE Signal Processing in Medicine and Biology Conference (SPMB), Virtual, Dec 5, 2020. 
• Vardhini P, Punitha N, Makaram N and Ramakrishnan S, “Multifractal Analysis of Term and Preterm Uterine EMG Signals Using Wavelet Leaders”, Proceedings of IEEE Life Sciences Conference (LSC), pp. 271-274, Oct 28 – 30, Montreal, Canada, 2018.
• Punitha N and Ramakrishnan S, “Analysis of uterine electromyography signals in preterm condition using multifractal algorithm”, Proceedings of 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’18), Honolulu, HI, USA, Jul 17 – 21, 2018. 
• Punitha N and Ramakrishnan S, “A novel approach to distinguish Term and Preterm conditions using Uterine Electromyography signals”, Diagnostics-4-Future Conference, Konstanz, Germany, Nov 27 – 28, 2019.
• Kanchana D, Punitha N and Ramakrishnan S, “Automated Segmentation of Indirect Immunofluorescence Images using Fast Fuzzy C-Means Algorithm for Keypoint based Differentiation of Homogenous and Speckled Shapes”, Conference on Machine Intelligence in Medical Imaging (C-MIMI), Austin, Texas, Sept 22 – 23, 2019.
• Punitha N and Ramakrishnan S, “Multifractal Analysis of Uterine EMG signals to differentiate Term and Preterm conditions using Hurst exponent, 45th Annual Northeast Bioengineering Conference (NEBEC), New Brunswick, USA, Mar 20-22, 2019.
• Punitha N and Ramakrishnan S, “Multifractal Analysis of Uterine EMG signals for the Assessment of Progression of pregnancy in Term condition using Hurst exponents, 56th Annual Rocky Mountain Bioengineering Symposium and 38th IEEE Great Lakes Biomedical Conference, Milwaukee, USA, Apr 12-14, 2019.
• Punitha N and Ramakrishnan S, “Prediction of term and preterm conditions from Uterine surface Electromyography using Time-Frequency Image based texture features”, Society for Imaging Informatics in Medicine (SIIM), National Harbor, MD, USA, May 31 – Jun 2, 2018.  
• Punitha N and Ramakrishnan S, “Differentiation of term and preterm conditions from Uterine surface Electromyography signals using Time-Frequency Images”, 55th Annual Rocky Mountain Bioengineering Symposium (RMBS), Fargo, ND, USA, Apr 13 – 14, 2018. 
• Kavitha I, Punitha N and Ramakrishnan S, “Color Correction and its Validation in Pressure Ulcer Images for Chronic Wound Assessment”, 55th Annual Rocky Mountain Bioengineering Symposium (RMBS), Fargo, ND, USA, Apr 13 – 14, 2018. 
• Punitha N and Ramakrishnan S, “An approach to classify Dermoscopy images using Dynamic Restricted Boltzmann machine”, Medical Image Perception Conference (MIPS XVII), Houston, Texas, USA, Jul 12 – 15, 2017.

Funded Project:

Title: Development of an Intelligent System to Characterise Uterine Contractions During Pregnancy 

Funding agency: SSN Trust

Amount received: 2.9 Lakhs